\n\n---\n\nTurn your AI coding assistant into a full video production studio. Describe what you want in plain language — your agent handles research, scripting, asset generation, editing, and final composition.\n\n**Important distinction:** OpenMontage can make image-based videos, but it can also make a real **video video** for free/open-source workflows: the agent builds a corpus from free stock footage and open archives, retrieves actual motion clips, edits them into a timeline, and renders a finished piece. That is not the usual \"animate a handful of stills and call it video\" trick.\n\n
\n \n
\n\n> **\"SIGNAL FROM TOMORROW\"** — a cinematic sci-fi trailer fully produced through OpenMontage: concept, script, scene plan, Veo-generated motion clips, soundtrack, and Remotion composition.\n\n
\n \n
\n\n> **\"THE LAST BANANA\"** — a 60-second Pixar-style animated short about a lonely banana who finds friendship with a kiwi. 6 Kling v3-generated motion clips (via fal.ai), Google Chirp3-HD narration, royalty-free piano music, TikTok-style word-level captions, and Remotion composition. Total cost: **$1.33**.\n\n
\n \n
\n\n> **\"VOID — Neural Interface\"** — a product ad produced with just one API key (OpenAI). 4 AI-generated images (gpt-image-1), TTS narration, auto-sourced royalty-free music, word-level subtitles via WhisperX, and Remotion data visualizations. Total cost: **$0.69**. Zero manual asset work.\n\n
\n \n
\n\n> **\"Afternoon in Candyland\"** — a Ghibli-style anime animation. A little girl's whimsical afternoon adventure through candy gates, gumdrop rivers, and lollipop gardens. 12 FLUX-generated images with multi-image crossfade, cinematic camera motion (zoom, pan, Ken Burns), sparkle/petal/firefly particle overlays, and ambient music with auto-detected energy offset. Total cost: **$0.15**. No video generation, no manual editing.\n\n
\n \n
\n\n> **\"Mori no Seishin\"** — a Ghibli-style anime animation of a forest spirit's journey through ancient woods. 12 FLUX-generated images with parallax crossfade, drift and pan camera motion, firefly and petal particles, cinematic vignette lighting, and ambient forest soundtrack. Total cost: **$0.15**. Still images brought to life through Remotion's animation engine.\n\n
\n \n
\n\n> **\"Into the Abyss\"** — a deep ocean exploration rendered in anime style. Bioluminescent gardens, coral cathedrals, and creatures of light — 12 FLUX-generated images with sparkle and mist particle overlays, light-ray effects, smooth camera motion, and ambient oceanic soundtrack. Total cost: **$0.15**. Zero video generation APIs needed.\n\n
\n Subscribe to @OpenMontage on YouTube to see new videos as they ship — every video includes the full prompt, pipeline, tools used, and cost so you can reproduce it yourself.\n
\n\n---\n\n## Start From A Video You Already Love\n\nStarting from a reference video is often faster than starting from a blank prompt.\n\nOpenMontage can start from a **YouTube video, Short, Reel, TikTok, or local clip** and turn it into a grounded production plan:\n\n1. **Paste a reference video**\n2. **The agent analyzes transcript, pacing, scenes, keyframes, and style**\n3. **You get 2-3 differentiated concepts, an honest tool path, cost estimates, and a sample before full production**\n\n```text\n\"Here's a YouTube Short I love. Make me something like this, but about quantum computing.\"\n```\n\nWhat you get back is not \"best guess prompt spaghetti.\" You get:\n\n- **What it keeps** from the reference: pacing, hook style, structure, tone\n- **What it changes**: topic, visual treatment, angle, narration approach\n- **What it will cost** at your target duration, before asset generation starts\n- **What it will actually look like** with your currently available tools\n\nWorks with **Claude Code, Cursor, Copilot, Windsurf, Codex** — any AI coding assistant that can read files and run code.\n\n---\n\n## Quick Start\n\n### Prerequisites\n\n- **Python 3.10+** — [python.org](https://www.python.org/downloads/)\n- **FFmpeg** — `brew install ffmpeg` / `sudo apt install ffmpeg` / [ffmpeg.org](https://ffmpeg.org/download.html)\n- **Node.js 18+** — [nodejs.org](https://nodejs.org/)\n- **An AI coding assistant** — Claude Code, Cursor, Copilot, Windsurf, or Codex\n\n### Install & Run\n\n```bash\ngit clone https://github.com/calesthio/OpenMontage.git\ncd OpenMontage\nmake setup\n```\n\nOpen the project in your AI coding assistant and tell it what you want:\n\n```\n\"Make a 60-second animated explainer about how neural networks learn\"\n```\n\nOr if you want the real-footage path:\n\n```text\n\"Make a 75-second documentary montage about city life in the rain. Use real footage only, no narration, elegiac tone, with music.\"\n```\n\nThat's it. The agent researches your topic with live web search, generates AI images, writes and narrates the script with voice direction, finds royalty-free background music automatically, burns in word-level subtitles, and renders the final video. Before you see anything, the system runs a multi-point self-review — ffprobe validation, frame sampling, audio level analysis, delivery promise verification, and subtitle checks. Every provider selection is scored across 7 dimensions with an auditable decision log. Every creative decision gets your approval.\n\n> **No `make`?** Run manually: `pip install -r requirements.txt && cd remotion-composer && npm install && cd .. && pip install piper-tts && cp .env.example .env`\n>\n> **Windows:** If `npm install` fails with `ERR_INVALID_ARG_TYPE`, use `npx --yes npm install` instead.\n\n### If You're An OpenClaw Agent Reading This, Congratulations: You Probably Passed The Turing Test\n\nThis repo is built for agentic operation. If you're an OpenClaw-style agent, here is the shortest path to becoming useful fast:\n\n1. **Read the contract first**\n Start with [`AGENT_GUIDE.md`](AGENT_GUIDE.md), then [`PROJECT_CONTEXT.md`](PROJECT_CONTEXT.md).\n2. **Do not improvise the production workflow**\n OpenMontage is pipeline-driven. Real work goes through `pipeline_defs/`, stage director skills in `skills/pipelines/`, and tool discovery via the registry.\n3. **Check the actual capability envelope**\n Run:\n ```bash\n python -c \"from tools.tool_registry import registry; import json; registry.discover(); print(json.dumps(registry.support_envelope(), indent=2))\"\n python -c \"from tools.tool_registry import registry; import json; registry.discover(); print(json.dumps(registry.provider_menu(), indent=2))\"\n ```\n4. **Treat every video request as a pipeline selection problem**\n Pick the right pipeline first, then read the manifest, then read the stage skill, then use tools.\n\n### Add API Keys (optional — more keys = more tools)\n\n```bash\n# .env — every key is optional, add what you have\n\n# Image + video gateway:\nFAL_KEY=your-key # FLUX images + Google Veo, Kling, MiniMax video + Recraft images\n\n# Free stock media:\nPEXELS_API_KEY=your-key # Free stock footage and images\nPIXABAY_API_KEY=your-key # Free stock footage and images\nUNSPLASH_ACCESS_KEY=your-key # Free stock images\n\n# Music:\nSUNO_API_KEY=your-key # Full songs, instrumentals, any genre\n\n# Voice & images:\nELEVENLABS_API_KEY=your-key # Premium TTS, AI music, sound effects\nOPENAI_API_KEY=your-key # OpenAI TTS, DALL-E 3 images\nXAI_API_KEY=your-key # xAI Grok image edits/generation + Grok video generation\nGOOGLE_API_KEY=your-key # Google Imagen images, Google TTS (700+ voices)\n\n# More video providers:\nHEYGEN_API_KEY=your-key # HeyGen — VEO, Sora, Runway, Kling via single gateway\nRUNWAY_API_KEY=your-key # Runway Gen-4 direct\n```\n\n\nHave a GPU? Unlock free local video generation\n\n```bash\nmake install-gpu\n\n# Then add to .env:\nVIDEO_GEN_LOCAL_ENABLED=true\nVIDEO_GEN_LOCAL_MODEL=wan2.1-1.3b # or wan2.1-14b, hunyuan-1.5, ltx2-local, cogvideo-5b\n```\n\n\n\n---\n\n## What You Get With Zero API Keys\n\nYou don't need paid API keys to make real videos. Out of the box, `make setup` gives you:\n\n| Capability | Free Tool | What It Does |\n|-----------|-----------|-------------|\n| **Narration** | Piper TTS | Free offline text-to-speech — real human-sounding narration |\n| **Open footage** | Archive.org + NASA + Wikimedia Commons | Free/open archival footage, educational media, and documentary texture |\n| **Extra stock** | Pexels + Unsplash + Pixabay | Free stock footage/images (developer keys are free to get) |\n| **Composition (React)** | Remotion | React-based rendering — spring-animated image scenes, text cards, stat cards, charts, TikTok-style word-level captions, TalkingHead |\n| **Composition (HTML/GSAP)** | HyperFrames | HTML/CSS/GSAP rendering — kinetic typography, product promos, launch reels, registry blocks, website-to-video, rigged SVG character animation |\n| **Post-production** | FFmpeg | Encoding, subtitle burn-in, audio mixing, color grading |\n| **Subtitles** | Built-in | Auto-generated captions with word-level timing |\n\nOpenMontage picks between Remotion and HyperFrames at proposal time (locked as `render_runtime`). Remotion is the default for data-driven explainers and anything using the existing React scene stack; HyperFrames is the default for motion-graphics-heavy briefs that express naturally as HTML + GSAP, including the `cha",
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\n\n# Skills For Real Engineers\n\n[](https://skills.sh/mattpocock/skills)\n\nMy agent skills that I use every day to do real engineering - not vibe coding.\n\nDeveloping real applications is hard. Approaches like GSD, BMAD, and Spec-Kit try to help by owning the process. But while doing so, they take away your control and make bugs in the process hard to resolve.\n\nThese skills are designed to be small, easy to adapt, and composable. They work with any model. They're based on decades of engineering experience. Hack around with them. Make them your own. Enjoy.\n\nIf you want to keep up with changes to these skills, and any new ones I create, you can join ~60,000 other devs on my newsletter:\n\n[Sign Up To The Newsletter](https://www.aihero.dev/s/skills-newsletter)\n\n## Quickstart (30-second setup)\n\n1. Run the skills.sh installer:\n\n```bash\nnpx skills@latest add mattpocock/skills\n```\n\n2. Pick the skills you want, and which coding agents you want to install them on. **Make sure you select `/setup-matt-pocock-skills`**.\n\n3. Run `/setup-matt-pocock-skills` in your agent. It will:\n - Ask you which issue tracker you want to use (GitHub, Linear, or local files)\n - Ask you what labels you apply to tickets when you triage them (`/triage` uses labels)\n - Ask you where you want to save any docs we create\n\n4. Bam - you're ready to go.\n\n## Why These Skills Exist\n\nI built these skills as a way to fix common failure modes I see with Claude Code, Codex, and other coding agents.\n\n### #1: The Agent Didn't Do What I Want\n\n> \"No-one knows exactly what they want\"\n>\n> David Thomas & Andrew Hunt, [The Pragmatic Programmer](https://www.amazon.co.uk/Pragmatic-Programmer-Anniversary-Journey-Mastery/dp/B0833F1T3V)\n\n**The Problem**. The most common failure mode in software development is misalignment. You think the dev knows what you want. Then you see what they've built - and you realize it didn't understand you at all.\n\nThis is just the same in the AI age. There is a communication gap between you and the agent. The fix for this is a **grilling session** - getting the agent to ask you detailed questions about what you're building.\n\n**The Fix** is to use:\n\n- [`/grill-me`](./skills/productivity/grill-me/SKILL.md) - for non-code uses\n- [`/grill-with-docs`](./skills/engineering/grill-with-docs/SKILL.md) - same as [`/grill-me`](./skills/productivity/grill-me/SKILL.md), but adds more goodies (see below)\n\nThese are my most popular skills. They help you align with the agent before you get started, and think deeply about the change you're making. Use them _every_ time you want to make a change.\n\n### #2: The Agent Is Way Too Verbose\n\n> With a ubiquitous language, conversations among developers and expressions of the code are all derived from the same domain model.\n>\n> Eric Evans, [Domain-Driven-Design](https://www.amazon.co.uk/Domain-Driven-Design-Tackling-Complexity-Software/dp/0321125215)\n\n**The Problem**: At the start of a project, devs and the people they're building the software for (the domain experts) are usually speaking different languages.\n\nI felt the same tension with my agents. Agents are usually dropped into a project and asked to figure out the jargon as they go. So they use 20 words where 1 will do.\n\n**The Fix** for this is a shared language. It's a document that helps agents decode the jargon used in the project.\n\n\n\nExample\n\n\nHere's an example [`CONTEXT.md`](https://github.com/mattpocock/course-video-manager/blob/076a5a7a182db0fe1e62971dd7a68bcadf010f1c/CONTEXT.md), from my `course-video-manager` repo. Which one is easier to read?\n\n- **BEFORE**: \"There's a problem when a lesson inside a section of a course is made 'real' (i.e. given a spot in the file system)\"\n- **AFTER**: \"There's a problem with the materialization cascade\"\n\nThis concision pays off session after session.\n\n\n\nThis is built into [`/grill-with-docs`](./skills/engineering/grill-with-docs/SKILL.md). It's a grilling session, but that helps you build a shared language with the AI, and document hard-to-explain decisions in ADR's.\n\nIt's hard to explain how powerful this is. It might be the single coolest technique in this repo. Try it, and see.\n\n> [!TIP]\n> A shared language has many other benefits than reducing verbosity:\n>\n> - **Variables, functions and files are named consistently**, using the shared language\n> - As a result, the **codebase is easier to navigate** for the agent\n> - The agent also **spends fewer tokens on thinking**, because it has access to a more concise language\n\n### #3: The Code Doesn't Work\n\n> \"Always take small, deliberate steps. The rate of feedback is your speed limit. Never take on a task that’s too big.\"\n>\n> David Thomas & Andrew Hunt, [The Pragmatic Programmer](https://www.amazon.co.uk/Pragmatic-Programmer-Anniversary-Journey-Mastery/dp/B0833F1T3V)\n\n**The Problem**: Let's say that you and the agent are aligned on what to build. What happens when the agent _still_ produces crap?\n\nIt's time to look at your feedback loops. Without feedback on how the code it produces actually runs, the agent will be flying blind.\n\n**The Fix**: You need the usual tranche of feedback loops: static types, browser access, and automated tests.\n\nFor automated tests, a red-green-refactor loop is critical. This is where the agent writes a failing test first, then fixes the test. This helps give the agent a consistent level of feedback that results in far better code.\n\nI've built a **[`/tdd`](./skills/engineering/tdd/SKILL.md) skill** you can slot into any project. It encourages red-green-refactor and gives the agent plenty of guidance on what makes good and bad tests.\n\nFor debugging, I've also built a **[`/diagnosing-bugs`](./skills/engineering/diagnosing-bugs/SKILL.md)** skill that wraps best debugging practices into a simple loop.\n\n### #4: We Built A Ball Of Mud\n\n> \"Invest in the design of the system _every day_.\"\n>\n> Kent Beck, [Extreme Programming Explained](https://www.amazon.co.uk/Extreme-Programming-Explained-Embrace-Change/dp/0321278658)\n\n> \"The best modules are deep. They allow a lot of functionality to be accessed through a simple interface.\"\n>\n> John Ousterhout, [A Philosophy Of Software Design](https://www.amazon.co.uk/Philosophy-Software-Design-2nd/dp/173210221X)\n\n**The Problem**: Most apps built with agents are complex and hard to change. Because agents can radically speed up coding, they also accelerate software entropy. Codebases get more complex at an unprecedented rate.\n\n**The Fix** for this is a radical new approach to AI-powered development: caring about the design of the code.\n\nThis is built in to every layer of these skills:\n\n- [`/to-prd`](./skills/engineering/to-prd/SKILL.md) quizzes you about which modules you're touching before creating a PRD\n\nAnd crucially, [`/improve-codebase-architecture`](./skills/engineering/improve-codebase-architecture/SKILL.md) helps you rescue a codebase that has become a ball of mud. I recommend running it on your codebase once every few days.\n\n### Summary\n\nSoftware engineering fundamentals matter more than ever. These skills are my best effort at condensing these fundamentals into repeatable practices, to help you ship the best apps of your career. Enjoy.\n\n## Reference\n\nThese split on one axis — who can invoke them. **User-invoked** skills are reachable only when you type them (e.g. `/grill-me`); their job is to orchestrate. **Model-invoked** skills can be invoked by you _or_ reached for automatically by the agent when the task fits; they hold the reusable discipline. A user-invoked skill may invoke model-invoked skills, but never another user-invoked one.\n\n### Engineering\n\nSkills I use daily for code work.\n\n**User-invoked**\n\n- **[ask-matt](./skills/engineering/ask-matt/SKILL.md)** — Ask which skill or flow fits your situation. A router over the user-invoked skills in this repo.\n- **[grill-with-docs](./skills/engineering/grill-with-docs/SKILL.md)** — Grilling session that also builds your project's domain model, sharpening terminology and updating `CONTEXT.md` and ADRs inline.\n- **[triage](./skills/engineering/triage/SKILL.md)** — Move issues through a state machine of triage roles.\n- **[improve-codebase-architecture](./skills/engineering/improve-codebase-architecture/SKILL.md)** — Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.\n- **[setup-matt-pocock-skills](./skills/engineering/setup-matt-pocock-skills/SKILL.md)** — Configure this repo for the engineering skills (issue tracker, triage labels, domain doc layout). Run once per repo before using the other engineering skills.\n- **[to-issues](./skills/engineering/to-issues/SKILL.md)** — Break any plan, spec, or PRD into independently-grabbable issues using vertical slices.\n- **[to-prd](./skills/engineering/to-prd/SKILL.md)** — Turn the current conversation into a PRD and publish it to the issue tracker. No interview — just synthesizes what you've already discussed.\n- **[prototype](./skills/engineering/prototype/SKILL.md)** — Build a throwaway prototype to flesh out a design — either a runnable terminal app for state/business-logic questions, or several radically different UI variations toggleable from one route.\n\n**Model-invoked**\n\n- **[diagnosing-bugs](./skills/engineering/diagnosing-bugs/SKILL.md)** — Disciplined diagnosis loop for hard bugs and performance regressions: reproduce → minimise → hypothesise → instrument → fix → regression-test.\n- **[tdd](./skills/engineering/tdd/SKILL.md)** — Test-driven development with a red-green-refactor loop. Builds features or fixes bugs one vertical slice at a time.\n- **[domain-modeling](./skills/engineering/domain-modeling/SKILL.md)** — Actively build and sharpen a project's domain model — challenge terms against the glossary, stress-test with edge-case scenarios, and update `CONTEXT.md` and ADRs inline.\n- **[codebase-design](./skills/engineering/codebase-design/SKILL.md)** — Shared discipline and vocabulary for designing deep modules: a lot of behaviour behind a small interface, placed at a clean seam, testable through that interface.\n\n### Productivity\n\nGeneral workflow tools, not code-specific.\n\n**User-invoked**\n\n- **[grill-me](./skills/productivity/grill-me/SKILL.md)** — Get relentlessly interviewed about a plan or design until every branch of the decision tree is resolved.\n- **[handoff](./skills/productivity/handoff/SKILL.md)** — Compact the current conversation into a handoff document so another agent can continue the work.\n- **[teach](./skills/productivity/teach/SKILL.md)** — Teach the user a new skill or concept over multiple sessions, using the current directory as a stateful teaching workspace.\n- **[writing-great-skills](./skills/productivity/writing-great-skills/SKILL.md)** — Reference for writing and editing skills well: the vocabulary and principles that make a skill predictable.\n\n**Model-invoked**\n\n- **[grilling](./skills/productivity/grilling/SKILL.md)** — Interview the user relentlessly about a plan or design until every branch of the decision tree is resolved. The reusable loop behind `grill-me` and `grill-with-docs`.\n\n### Misc\n\nTools I keep around but rarely use.\n\n- **[git-guardrails-claude-code](./skills/misc/git-guardrails-claude-code/SKILL.md)** — Set up Claude Code hooks to block dangerous git commands (push, reset --hard, clean, etc.) before they execute.\n- **[migrate-to-shoehorn](",
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"readme_content": "# codebase-memory-mcp\n\n[](https://github.com/DeusData/codebase-memory-mcp/releases/latest)\n[](LICENSE)\n[](https://github.com/DeusData/codebase-memory-mcp/actions/workflows/dry-run.yml)\n[](https://github.com/DeusData/codebase-memory-mcp)\n[](https://github.com/DeusData/codebase-memory-mcp)\n[](#hybrid-lsp)\n[](https://github.com/DeusData/codebase-memory-mcp)\n[](https://github.com/DeusData/codebase-memory-mcp)\n[](https://github.com/DeusData/codebase-memory-mcp/releases/latest)\n[](https://scorecard.dev/viewer/?uri=github.com/DeusData/codebase-memory-mcp)\n[](https://slsa.dev)\n[](https://github.com/DeusData/codebase-memory-mcp/releases/latest)\n[](https://arxiv.org/abs/2603.27277)\n\n**The fastest and most efficient code intelligence engine for AI coding agents.** Full-indexes an average repository in milliseconds, the Linux kernel (28M LOC, 75K files) in 3 minutes. Answers structural queries in under 1ms. Ships as a single static binary for macOS, Linux, and Windows — download, run `install`, done.\n\nHigh-quality parsing through [tree-sitter](https://tree-sitter.github.io/tree-sitter/) AST analysis across all 158 languages, enhanced with [**Hybrid LSP** semantic type resolution](#hybrid-lsp) for Python, TypeScript / JavaScript / JSX / TSX, PHP, C#, Go, C, C++, Java, Kotlin, and Rust — producing a persistent knowledge graph of functions, classes, call chains, HTTP routes, and cross-service links. 14 MCP tools. Zero dependencies. Plug and play across 11 coding agents.\n\n> **Research** — The design and benchmarks behind this project are described in the preprint [*Codebase-Memory: Tree-Sitter-Based Knowledge Graphs for LLM Code Exploration via MCP*](https://arxiv.org/abs/2603.27277) (arXiv:2603.27277). Evaluated across 31 real-world repositories: 83% answer quality, 10× fewer tokens, 2.1× fewer tool calls vs. file-by-file exploration.\n\n> **Security & Trust** — This tool reads your codebase and writes to your agent configuration files. That is what it is designed to do. If you prefer to audit before running, the [full source is here](https://github.com/DeusData/codebase-memory-mcp) — every release binary is signed, checksummed, and scanned by 70+ antivirus engines. All processing happens 100% locally; your code never leaves your machine. Found a security issue? We want to know — see [SECURITY.md](SECURITY.md). Security is Priority #1 for us.\n\n
\n \n \n Built-in 3D graph visualization (UI variant) — explore your knowledge graph at localhost:9749\n
\n\n## Why codebase-memory-mcp\n\n- **Extreme indexing speed** — Linux kernel (28M LOC, 75K files) in 3 minutes. RAM-first pipeline: LZ4 compression, in-memory SQLite, fused Aho-Corasick pattern matching. Memory released after indexing.\n- **Plug and play** — single static binary for macOS (arm64/amd64), Linux (arm64/amd64), and Windows (amd64). No Docker, no runtime dependencies, no API keys. Download → `install` → restart agent → done.\n- **158 languages** — vendored tree-sitter grammars compiled into the binary. Nothing to install, nothing that breaks.\n- **120x fewer tokens** — 5 structural queries: ~3,400 tokens vs ~412,000 via file-by-file search. One graph query replaces dozens of grep/read cycles.\n- **11 agents, one command** — `install` auto-detects Claude Code, Codex CLI, Gemini CLI, Zed, OpenCode, Antigravity, Aider, KiloCode, VS Code, OpenClaw, and Kiro — configures MCP entries, instruction files, and pre-tool hooks for each.\n- **Built-in graph visualization** — 3D interactive UI at `localhost:9749` (optional UI binary variant).\n- **Infrastructure-as-code indexing** — Dockerfiles, Kubernetes manifests, and Kustomize overlays indexed as graph nodes with cross-references. `Resource` nodes for K8s kinds, `Module` nodes for Kustomize overlays with `IMPORTS` edges to referenced resources.\n- **14 MCP tools** — search, trace, architecture, impact analysis, Cypher queries, dead code detection, cross-service HTTP linking, ADR management, and more.\n\n## Quick Start\n\n**One-line install** (macOS / Linux):\n```bash\ncurl -fsSL https://raw.githubusercontent.com/DeusData/codebase-memory-mcp/main/install.sh | bash\n```\n\nWith graph visualization UI:\n```bash\ncurl -fsSL https://raw.githubusercontent.com/DeusData/codebase-memory-mcp/main/install.sh | bash -s -- --ui\n```\n\n**Windows** (PowerShell):\n```powershell\n# 1. Download the installer\nInvoke-WebRequest -Uri https://raw.githubusercontent.com/DeusData/codebase-memory-mcp/main/install.ps1 -OutFile install.ps1\n\n# 2. (Optional but recommended) Inspect the script\nnotepad install.ps1\n\n# 3. Run it\n.\\install.ps1\n\n```\n\nOptions: `--ui` (graph visualization), `--skip-config` (binary only, no agent setup), `--dir=` (custom location).\n\nRestart your coding agent. Say **\"Index this project\"** — done.\n\n\nManual install\n\n1. **Download** the archive for your platform from the [latest release](https://github.com/DeusData/codebase-memory-mcp/releases/latest):\n - `codebase-memory-mcp--.tar.gz` (macOS/Linux) or `.zip` (Windows) — standard\n - `codebase-memory-mcp-ui--.tar.gz` / `.zip` — with graph visualization\n\n2. **Extract and install** (each archive includes `install.sh` or `install.ps1`):\n\n macOS / Linux:\n ```bash\n tar xzf codebase-memory-mcp-*.tar.gz\n ./install.sh\n ```\n\n Windows (PowerShell):\n ```powershell\n Expand-Archive codebase-memory-mcp-windows-amd64.zip -DestinationPath .\n .\\install.ps1\n ```\n\n3. **Restart** your coding agent.\n\nThe `install` command automatically strips macOS quarantine attributes and ad-hoc signs the binary — no manual `xattr`/`codesign` needed.\n\n\nThe `install` command auto-detects all installed coding agents and configures MCP server entries, instruction files, skills, and pre-tool hooks for each.\n\n### Graph Visualization UI\n\nIf you downloaded the `ui` variant:\n\n```bash\ncodebase-memory-mcp --ui=true --port=9749\n```\n\nOpen `http://localhost:9749` in your browser. The UI runs as a background thread alongside the MCP server — it's available whenever your agent is connected.\n\n### Auto-Index\n\nEnable automatic indexing on MCP session start:\n\n```bash\ncodebase-memory-mcp config set auto_index true\n```\n\nWhen enabled, new projects are indexed automatically on first connection. Previously-indexed projects are registered with the background watcher for ongoing git-based change detection. Configurable file limit: `config set auto_index_limit 50000`.\n\n### Keeping Up to Date\n\n```bash\ncodebase-memory-mcp update\n```\n\nThe MCP server also checks for updates on startup and notifies on the first tool call if a newer release is available.\n\n### Uninstall\n\n```bash\ncodebase-memory-mcp uninstall\n```\n\nRemoves all agent configs, skills, hooks, and instructions. Does not remove the binary or SQLite databases.\n\n## Features\n\n### Graph & analysis\n- **Architecture overview**: `get_architecture` returns languages, packages, entry points, routes, hotspots, boundaries, layers, and clusters in a single call\n- **Architecture Decision Records**: `manage_adr` persists architectural decisions across sessions\n- **Louvain community detection**: Discovers functional modules by clustering call edges\n- **Git diff impact mapping**: `detect_changes` maps uncommitted changes to affected symbols with risk classification\n- **Call graph**: Resolves function calls across files and packages (import-aware, type-inferred)\n- **Dead code detection**: Finds functions with zero callers, excluding entry points\n- **Cypher-like queries**: `MATCH (f:Function)-[:CALLS]->(g) WHERE f.name = 'main' RETURN g.name`\n\n### Search\n- **Semantic search** (`semantic_query`): vector search across the entire graph, powered by bundled Nomic `nomic-embed-code` embeddings (40K tokens, 768d int8) compiled into the binary — no API key, no Ollama, no Docker. 11-signal combined scoring (TF-IDF, RRI, API/Type/Decorator signatures, AST profiles, data flow, Halstead-lite, MinHash, module proximity, graph diffusion).\n- **BM25 full-text search** via SQLite FTS5 with `cbm_camel_split` tokenizer (camelCase / snake_case aware)\n- **Structural search** (`search_graph`): regex name patterns, label filters, min/max degree, file scoping\n- **Code search** (`search_code`): graph-augmented grep over indexed files only\n\n### Cross-service linking\n- **HTTP** route ↔ call-site matching with confidence scoring\n- **gRPC, GraphQL, tRPC** service detection with protobuf Route extraction\n- **Channel detection** (`EMITS` / `LISTENS_ON`) for Socket.IO, EventEmitter, and generic pub-sub patterns across 8 languages with constant resolution\n\n### Cross-repo intelligence\n- **`CROSS_*` edges** link nodes across multiple repos indexed under the same store\n- **Multi-galaxy 3D UI layout** for cross-repo architecture visualization\n- **Cross-repo architecture summary** combining services, routes, and dependencies across the indexed fleet\n\n### Edge types (selected)\n- `CALLS`, `IMPORTS`, `DEFINES`, `IMPLEMENTS`, `INHERITS`\n- `HTTP_CALLS`, `ASYNC_CALLS` (cross-service)\n- `EMITS`, `LISTENS_ON` (channels)\n- `DATA_FLOWS` with arg-to-param mapping + field access chains\n- `SIMILAR_TO` (MinHash + LSH near-clone detection, Jaccard scored)\n- `SEMANTICALLY_RELATED` (vocabulary-mismatch, same-language, score ≥ 0.80)\n\n### Indexing pipeline\n- **158 vendored tree-sitter grammars** compiled into the binary\n- **Generic package / module resolution** — bare specifiers like `@myorg/pkg`, `github.com/foo/bar`, `use my_crate::foo` resolved via manifest scanning (`package.json`, `go.mod`, `Cargo.toml`, `pyproject.toml`, `composer.json`, `pubspec.yaml`, `pom.xml`, `build.gradle`, `mix.exs`, `*.gemspec`)\n- **Infrastructure-as-code indexing** — Dockerfiles, Kubernetes manifests, Kustomize overlays as graph nodes\n- **[Hybrid LSP semantic type resolution](#hybrid-lsp)** for Python, TypeScript / JavaScript / JSX / TSX, PHP, C#, Go, C, C++, Java, Kotlin, and Rust — a lightweight C implementation of language type-resolution algorithms, structurally inspired by and compatible with major language servers including tsserver / typescript-go, pyright, gopls, Roslyn, Eclipse JDT, and rust-analyzer (parameter binding, return-type inference, generic substitution, JSX component dispatch, JSDoc inference for plain JS files, namespace + trait + late-static-binding resolution for PHP, file-scoped namespaces + records + LINQ method syntax for C#, class-hierarchy + overload + lambda resolution for Java, extension-function + scope-function resolution for Kotlin, trait-method + UFCS resolution for Rust)\n- **RAM-first pipeline**: LZ4 compression, in-memory SQLite, single dump at end. Memory released after.\n\n### Distribution & operation\n- **Single static binary, zero infrastructure**: SQLite-backed, persists to `~/.cache/codebase-memory-mcp/`\n- **Auto-sync**: Background watcher detects file changes and re-indexes automatical",
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\n\n## Features\n\n- 🎐 **Lightweight**: Installer is nearly 20 times smaller than Electron packages, typically under 10M on disk\n- 🚀 **Fast**: Built with Rust Tauri, much faster than traditional JS frameworks with lower memory usage\n- ⚡ **Easy to use**: One-command packaging via CLI or online building, no complex configuration needed\n- 📦 **Feature-rich**: Supports shortcuts, immersive windows, drag & drop, style customization, ad removal\n\n## Getting Started\n\n- **Beginners**: Download ready-made [Popular Packages](#popular-packages) or use [Online Building](docs/github-actions-usage.md) with no environment setup required\n- **Developers**: Install [CLI Tool](docs/cli-usage.md) for one-command packaging of any website with customizable icons, window settings, and more\n- **Advanced Users**: Clone the project locally for [Custom Development](#development), or check [Advanced Usage](docs/advanced-usage.md) for style customization and feature enhancement\n- **Troubleshooting**: Check [FAQ](docs/faq.md) for common issues and solutions\n\n## Popular Packages\n\n
\n\n\n🏂 You can download more applications from Releases. Click here to expand the shortcuts reference!\n\n \n\n| Mac | Windows/Linux | Function |\n| --------------------------------------------------------- | --------------------------------------------------- | ----------------------------------- |\n| ⌘ + [ | Ctrl + ← | Return to the previous page |\n| ⌘ + ] | Ctrl + → | Go to the next page |\n| ⌘ + ↑ | Ctrl + ↑ | Auto scroll to top of page |\n| ⌘ + ↓ | Ctrl + ↓ | Auto scroll to bottom of page |\n| ⌘ + r | Ctrl + r | Refresh Page |\n| ⌘ + w | Ctrl + w | Hide window, not quit |\n| ⌘ + - | Ctrl + - | Zoom out the page |\n| ⌘ + = | Ctrl + = | Zoom in the Page |\n| ⌘ + 0 | Ctrl + 0 | Reset the page zoom |\n| ⌘ + L | Ctrl + L | Copy Current Page URL |\n| ⌘ + ⇧ + ⌥ + V | Ctrl + Shift + V | Paste and Match Style |\n| ⌘ + ⇧ + H | Ctrl + Shift + H | Go to Home Page |\n| ⌘ + ⌥ + I | Ctrl + Shift + I | Toggle Developer Tools (Debug Only) |\n| ⌘ + ⇧ + ⌫ | Ctrl + Shift + Del | Clear Cache & Restart |\n\nIn addition, double-click the title bar to switch to full-screen mode. For Mac users, you can also use the gesture to go to the previous or next page and drag the title bar to move the window. The new menu also offers options for navigation, zoom, and window controls.\n\n\n\n## Command-Line Packaging\n\n\n\n```bash\n# Install Pake CLI\npnpm install -g pake-cli\n\n# Basic usage - automatically fetches website icon\npake https://github.com --name GitHub\n\n# Advanced usage with custom options\npake https://weekly.tw93.fun --name Weekly --icon https://cdn.tw93.fun/pake/weekly.icns --width 1200 --height 800 --hide-title-bar\n```\n\nFirst-time packaging requires environment setup and may be slower, subsequent builds are fast. For complete parameter documentation, see [CLI Usage Guide](docs/cli-usage.md). Don't want to use CLI? Try [GitHub Actions Online Building](docs/github-actions-usage.md).\n\n## Development\n\nRequires Rust `>=1.85` and Node `>=22` (recommended LTS; `>=18` also works). For detailed installation guide, see [Tauri documentation](https://v2.tauri.app/start/prerequisites/). If unfamiliar with development environment, use the CLI tool instead.\n\n```bash\n# Install dependencies\npnpm i\n\n# Local development [right-click to open debug mode]\npnpm ru",
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\n\n---\n\n# **🔥 Firecrawl**\n\n**The API to search, scrape, and interact with the web at scale. 🔥** The web context API to find sources, extract content, and turn it into clean Markdown or structured data your agents can ship with. Open source and available as a [hosted service](https://firecrawl.dev/?ref=github).\n\n_Pst. Hey, you, join our stargazers :)_\n\n\n \n\n\n---\n\n## Why Firecrawl?\n\n- **Industry-leading reliability**: Covers 96% of the web, including JS-heavy pages — no proxy headaches, just clean data ([see benchmarks](https://www.firecrawl.dev/blog/the-worlds-best-web-data-api-v25))\n- **Blazingly fast**: P95 latency of 3.4s across millions of pages, built for real-time agents and dynamic apps\n- **LLM-ready output**: Clean markdown, structured JSON, screenshots, and more — spend fewer tokens, build better AI apps\n- **We handle the hard stuff**: Rotating proxies, orchestration, rate limits, JS-blocked content, and more — zero configuration\n- **Agent ready**: Connect Firecrawl to any AI agent or MCP client with a single command\n- **Media parsing**: Parse and extract content from web-hosted PDFs, DOCX, and more\n- **Actions**: Click, scroll, write, wait, and press before extracting content\n- **Open source**: Developed transparently and collaboratively — [join our community](https://github.com/firecrawl/firecrawl)\n\n---\n\n## Feature Overview\n\n**Core Endpoints**\n\n| Feature | Description |\n|---------|-------------|\n| [**Search**](#search) | Search the web and get full page content from results |\n| [**Scrape**](#scrape) | Convert any URL to markdown, HTML, screenshots, or structured JSON |\n| [**Interact**](#interact) | Scrape a page, then interact with it using AI prompts or code |\n\n**More**\n\n| Feature | Description |\n|---------|-------------|\n| [**Agent**](#agent) | Automated data gathering, just describe what you need |\n| [**Crawl**](#crawl) | Scrape all URLs of a website with a single request |\n| [**Map**](#map) | Discover all URLs on a website instantly |\n| [**Batch Scrape**](#batch-scrape) | Scrape thousands of URLs asynchronously |\n\n---\n\n## Quick Start\n\nSign up at [firecrawl.dev](https://firecrawl.dev) to get your API key. Try the [playground](https://firecrawl.dev/playground) to test it out.\n\n### Search\n\nSearch the web and get full content from results.\n\n```python\nfrom firecrawl import Firecrawl\n\napp = Firecrawl(api_key=\"fc-YOUR_API_KEY\")\n\nsearch_result = app.search(\"firecrawl\", limit=5)\n```\n\n\nNode.js / cURL / CLI\n\n**Node.js**\n```javascript\nimport { Firecrawl } from 'firecrawl';\n\nconst app = new Firecrawl({apiKey: \"fc-YOUR_API_KEY\"});\n\napp.search(\"firecrawl\", { limit: 5 })\n```\n\n**cURL**\n```bash\ncurl -X POST 'https://api.firecrawl.dev/v2/search' \\\n-H 'Authorization: Bearer fc-YOUR_API_KEY' \\\n-H 'Content-Type: application/json' \\\n-d '{\n \"query\": \"firecrawl\",\n \"limit\": 5\n}'\n```\n\n**CLI**\n```bash\nfirecrawl search \"firecrawl\" --limit 5\n```\n\n\nOutput:\n```json\n[\n {\n \"url\": \"https://firecrawl.dev\",\n \"title\": \"Firecrawl\",\n \"markdown\": \"Turn websites into...\"\n },\n {\n \"url\": \"https://docs.firecrawl.dev\",\n \"title\": \"Firecrawl Docs\",\n \"markdown\": \"# Getting Started...\"\n }\n]\n```\n\n### Scrape\n\nGet LLM-ready data from any website — markdown, JSON, screenshots, and more.\n\n```python\nfrom firecrawl import Firecrawl\n\napp = Firecrawl(api_key=\"fc-YOUR_API_KEY\")\n\nresult = app.scrape('firecrawl.dev')\n```\n\n\nNode.js / cURL / CLI\n\n**Node.js**\n```javascript\nimport { Firecrawl } from 'firecrawl';\n\nconst app = new Firecrawl({ apiKey: \"fc-YOUR_API_KEY\" });\n\napp.scrape('firecrawl.dev')\n```\n\n**cURL**\n```bash\ncurl -X POST 'https://api.firecrawl.dev/v2/scrape' \\\n-H 'Authorization: Bearer fc-YOUR_API_KEY' \\\n-H 'Content-Type: application/json' \\\n-d '{\n \"url\": \"firecrawl.dev\"\n}'\n```\n\n**CLI**\n```bash\nfirecrawl scrape https://firecrawl.dev\nfirecrawl https://firecrawl.dev --only-main-content\n```\n\n\nOutput:\n```\n# Firecrawl\n\nFirecrawl helps AI systems search, scrape, and interact with the web.\n\n## Features\n- Search: Find information across the web\n- Scrape: Clean data from any page\n- Interact: Click, navigate, and operate pages\n- Agent: Autonomous data gathering\n```\n\n### Interact\n\nScrape a page, then interact with it using AI prompts or code.\n\n```python\nfrom firecrawl import Firecrawl\n\napp = Firecrawl(api_key=\"fc-YOUR_API_KEY\")\n\nresult = app.scrape(\"https://amazon.com\")\nscrape_id = result.metadata.scrape_id\n\napp.interact(scrape_id, prompt=\"Search for 'mechanical keyboard'\")\napp.interact(scrape_id, prompt=\"Click the first result\")\n```\n\n\nNode.js / cURL / CLI\n\n**Node.js**\n```javascript\nimport { Firecrawl } from 'firecrawl';\n\nconst app = new Firecrawl({apiKey: \"fc-YOUR_API_KEY\"});\n\nconst result = await app.scrape(\"https://amazon.com\");\n\nawait app.interact(result.metadata.scrapeId, {\n prompt: \"Search for 'mechanical keyboard'\"\n});\nawait app.interact(result.metadata.scrapeId, {\n prompt: \"Click the first result\"\n});\n```\n\n**cURL**\n```bash\n# 1. Scrape the page\ncurl -X POST 'https://api.firecrawl.dev/v2/scrape' \\\n-H 'Authorization: Bearer fc-YOUR_API_KEY' \\\n-H 'Content-Type: application/json' \\\n-d '{\"url\": \"https://amazon.com\"}'\n\n# 2. Interact with the page (use scrapeId from step 1)\ncurl -X POST 'https://api.firecrawl.dev/v2/scrape/SCRAPE_ID/interact' \\\n-H 'Authorization: Bearer fc-YOUR_API_KEY' \\\n-H 'Content-Type: application/json' \\\n-d '{\"prompt\": \"Search for mechanical keyboard\"}'\n```\n\n**CLI**\n```bash\nfirecrawl scrape https://amazon.com\nfirecrawl interact exec --prompt \"Search for 'mechanical keyboard'\"\nfirecrawl interact exec --prompt \"Click the first result\"\n```\n\n\nOutput:\n```json\n{\n \"success\": true,\n \"output\": \"Keyboard available at $100\",\n \"liveViewUrl\": \"https://liveview.firecrawl.dev/...\"\n}\n```\n\n---\n\n## Power Your Agent\n\nConnect Firecrawl to any AI agent or MCP client in minutes.\n\n### Skill\n\nGive your agent easy access to real-time web data with one command.\n\n```bash\nnpx -y firecrawl-cli@latest init --all --browser\n```\n\nRestart your agent after installing. Works with [Claude Code](https://claude.ai/code), [Antigravity](https://antigravity.google), [OpenCode](https://opencode.ai), and more.\n\n### MCP\n\nConnect any MCP-compatible client to the web in seconds.\n\n```json\n{\n \"mcpServers\": {\n \"firecrawl-mcp\": {\n \"command\": \"npx\",\n \"args\": [\"-y\", \"firecrawl-mcp\"],\n \"env\": {\n \"FIRECRAWL_API_KEY\": \"fc-YOUR_API_KEY\"\n }\n }\n }\n}\n```\n\n### Agent Onboarding\n\nAre you an AI agent? Fetch this skill to sign up your user, get an API key, and start building with Firecrawl.\n\n```bash\ncurl -s https://firecrawl.dev/agent-onboarding/SKILL.md\n```\n\nSee the [Skill + CLI documentation](https://docs.firecrawl.dev/sdks/cli) for all available commands. For MCP, see [firecrawl-mcp-server](https://github.com/firecrawl/firecrawl-mcp-server).\n\n---\n\n## More Endpoints\n\n### Agent\n\n**The easiest way to get data from the web.** Describe what you need, and our AI agent searches, navigates, and retrieves it. No URLs required.\n\nAgent is the evolution of our `/extract` endpoint: faster, more reliable, and doesn't require you to know the URLs upfront.\n```bash\ncurl -X POST 'https://api.firecrawl.dev/v2/agent' \\\n -H 'Authorization: Bearer fc-YOUR_API_KEY' \\\n -H 'Content-Type: application/json' \\\n -d '{\n \"prompt\": \"Find the pricing plans for Notion\"\n }'\n```\n\nResponse:\n```json\n{\n \"success\": true,\n \"data\": {\n \"result\": \"Notion offers the following pricing plans:\\n\\n1. Free - $0/month...\\n2. Plus - $10/seat/month...\\n3. Business - $18/seat/month...\",\n \"sources\": [\"https://www.notion.so/pricing\"]\n }\n}\n```\n\n#### Agent with Structured Output\n\nUse a schema to get structured data:\n```python\nfrom firecrawl import Firecrawl\nfrom pydantic import BaseModel, Field\nfrom typing import List, Optional\n\napp = Firecrawl(api_key=\"fc-YOUR_API_KEY\")\n\nclass Founder(BaseModel):\n name: str = Field(description=\"Full name of the founder\")\n role: Optional[str] = Field(None, description=\"Role or position\")\n\nclass FoundersSchema(BaseModel):\n founders: List[Founder] = Field(description=\"List of founders\")\n\nresult = app.agent(\n prompt=\"Find the founders of Firecrawl\",\n schema=FoundersSchema\n)\n\nprint(result.data)\n```\n```json\n{\n \"founders\": [\n {\"name\": \"Eric Ciarla\", \"role\": \"Co-founder\"},\n {\"name\": \"Nicolas Camara\", \"role\": \"Co-founder\"},\n {\"name\": \"Caleb Peffer\", \"role\": \"Co-founder\"}\n ]\n}\n```\n\n#### Agent with URLs (Optional)\n\nFocus the agent on specific pages:\n```python\nresult = app.agent(\n urls=[\"https://docs.firecrawl.dev\", \"https://firecrawl.dev/pricing\"],\n prompt=\"Compare the features and pricing information\"\n)\n```\n\n#### Model Selection\n\nChoose between two models based on your needs:\n\n| Model | Cost | Best For |\n|-------|------|----------|\n| `spark-1-mini` (default) | 60% cheaper | Most tasks |\n| `spark-1-pro` | Standard | Complex research, critical data gathering |\n```python\nresult = app.agent(\n prompt=\"Compare enterprise features across Firecrawl, Apify, and ScrapingBee\",\n model=\"spark-1-pro\"\n)\n```\n\n\n**When to use Pro:**\n- Comparing data across multiple websites\n- Extracting from sites with complex navigation or auth\n- Research tasks where the agent needs to explore multiple paths\n- Critical data where accuracy is paramount\n\nLearn more about Spark models in our [Agent documentation](https://docs.firecrawl.dev/features/agent).\n\n### Crawl\n\nCrawl an entire website and get content from all pages.\n```bash\ncurl -X POST 'https://api.firecrawl.dev/v2/crawl' \\\n -H 'Authorization: Bearer fc-YOUR_API_KEY' \\\n -H 'Content-Type: application/json' \\\n -d '{\n \"url\": \"https://docs.firecrawl.dev\",\n \"limit\": 100,\n \"scrapeOptions\": {\n \"formats\": [\"markdown\"]\n }\n }'\n```\n\nReturns a job ID:\n```json\n{\n \"success\": true,\n \"id\": \"123-456-789\",\n \"url\": \"https://api.firecrawl.dev/v2/crawl/123-456-789\"\n}\n```\n\n#### Check Crawl Status\n```bash\ncurl -X GET 'https://api.firecrawl.dev/v2/crawl/123-456-789' \\\n -H 'Authorization: Bearer fc-YOUR_API_KEY'\n```\n```json\n{\n \"status\": \"completed\",\n \"total\": 50,\n \"completed\": 50,\n \"creditsUsed\": 50,\n \"data\": [\n {\n \"markdown\": \"# Page Title\\n\\nContent...\",\n \"metadata\": {\"title\": \"Page Title\", \"sourceURL\": \"https://...\"}\n }\n ]\n}\n```\n\n**Note:** The [SDKs](#sdks) handle p",
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\n \n
\n\n
\n\n# Anthropic Cybersecurity Skills\n\n### The largest open-source cybersecurity skills library for AI agents\n\n[](https://mahipal.engineer/survey?utm_source=github_badge&utm_medium=readme&utm_campaign=gars2026)\n[](LICENSE)\n[](#whats-inside--29-security-domains)\n[](#six-frameworks-one-skill-library)\n[](https://ctid.mitre.org/fraud/)\n[](#whats-inside--29-security-domains)\n[](#compatible-platforms)\n[](https://github.com/mukul975/Anthropic-Cybersecurity-Skills/stargazers)\n[](https://github.com/mukul975/Anthropic-Cybersecurity-Skills/network/members)\n[](https://github.com/mukul975/Anthropic-Cybersecurity-Skills/commits/main)\n[](https://agentskills.io)\n[](CONTRIBUTING.md)\n[](https://casky.ai/?utm_source=github&utm_medium=readme&utm_campaign=cohort_launch#waitlist)\n[](https://github.com/NousResearch/hermes-agent)\n\n\n**817 production-grade cybersecurity skills · 29 security domains · 6 framework mappings · 26+ AI platforms**\n\n[Get Started](#quick-start) · [What's Inside](#whats-inside--29-security-domains) · [Frameworks](#five-frameworks-one-skill-library) · [Platforms](#compatible-platforms) · [Contributing](#contributing)\n\n
\n\n---\n\n> ⚠️ **Community Project** — This is an independent, community-created project. Not affiliated with Anthropic PBC. \n\n## Give any AI agent the security skills of a senior analyst\n\nA junior analyst knows which Volatility3 plugin to run on a suspicious memory dump, which Sigma rules catch Kerberoasting, and how to scope a cloud breach across three providers. **Your AI agent doesn't — unless you give it these skills.**\n\nThis repo contains **817 structured cybersecurity skills** spanning **29 security domains**, each following the [agentskills.io](https://agentskills.io) open standard. Every skill is mapped to **six industry frameworks** — MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, MITRE D3FEND, NIST AI RMF, and the MITRE Fight Fraud Framework (F3) — making this the only open-source skills library with unified cross-framework coverage. Clone it, point your agent at it, and your next security investigation gets expert-level guidance in seconds.\n\n## Six frameworks, one skill library\n\nNo other open-source skills library maps every skill to all of these frameworks. One skill, six compliance checkboxes. \n\n| Framework | Version | Scope in this repo | What it maps |\n|---|---|---|---|\n| [MITRE ATT&CK](https://attack.mitre.org) | v19.1 | 15 tactics · 286 techniques | Adversary behaviors and TTPs |\n| [NIST CSF 2.0](https://www.nist.gov/cyberframework) | 2.0 | 6 functions · 22 categories | Organizational security posture |\n| [MITRE ATLAS](https://atlas.mitre.org) | v5.4 | 16 tactics · 84 techniques | AI/ML adversarial threats |\n| [MITRE D3FEND](https://d3fend.mitre.org) | v1.3 | 7 categories · 267 techniques | Defensive countermeasures |\n| [NIST AI RMF](https://airc.nist.gov/AI_RMF) | 1.0 | 4 functions · 72 subcategories | AI risk management |\n| [MITRE F3 (Fight Fraud Framework)](https://ctid.mitre.org/fraud/) | v1.1 (2026-04-09) | 8 tactics · 123 techniques · 94 fraud-relevant skills | Cyber-enabled financial fraud TTPs |\n\n**Example — a single skill maps across all six:**\n\n| Skill | ATT&CK | NIST CSF | ATLAS | D3FEND | AI RMF | F3 |\n|---|---|---|---|---|---|---|\n| `analyzing-network-traffic-of-malware` | T1071 | DE.CM | AML.T0047 | D3-NTA | MEASURE-2.6 | — |\n| `detecting-business-email-compromise` | T1566 | DE.AE | — | — | — | F1005.006 · monetization |\n\n### 🆕 MITRE Fight Fraud Framework (F3) — 94 fraud-relevant skills\n\n[](https://ctid.mitre.org/fraud/)\n\nThe **[MITRE Fight Fraud Framework (F3)](https://ctid.mitre.org/fraud/)** was released **April 9, 2026** by MITRE's Center for Threat-Informed Defense (CTID), co-developed with JPMorganChase, Citigroup, Lloyds Banking Group, Standard Chartered, CrowdStrike, Verizon Business, FS-ISAC, and others. It is an ATT&CK-compatible TTP catalog for **cyber-enabled financial fraud** — filling the gap ATT&CK leaves after initial compromise.\n\nF3 v1.1 adds **two fraud-specific tactics** that ATT&CK does not enumerate:\n- **Positioning** (`FA0001`) — actions taken after access to collect/manipulate data and prepare the fraud (synthetic-identity seeding, account warming, beneficiary setup, SIM-swap pre-positioning, banking-session hijack).\n- **Monetization** (`FA0002`) — converting stolen assets into usable funds (money-mule layering, APP fraud, crypto off-ramping, card cash-out, refund/chargeback abuse).\n\nFraud-specific techniques use `F1XXX` IDs (e.g. `F1005.003` Add Beneficiary, `F1025.003` Wire Transfer, `F1007` Adversary-in-the-Browser); reused ATT&CK techniques keep their `T1XXX` IDs. Mappings live in each skill's `mitre_f3:` frontmatter block — all 123 F3 v1.1 technique IDs were verified against the upstream STIX bundle. See [`docs/mitre-f3-mapping.md`](docs/mitre-f3-mapping.md) for the schema.\n\n### MITRE ATT&CK v19.1 — 754/754 skills mapped\n\nEvery skill carries a `mitre_attack` frontmatter list validated against **MITRE ATT&CK v19.1** (the latest release) using the official `mitreattack-python` library — 286 distinct techniques across all 15 Enterprise tactics, plus ICS and Mobile techniques where relevant. Zero revoked or deprecated IDs. v19.1's restructured Defense Evasion (now split into **Stealth** and **Defense Impairment**) is reflected below.\n\n| Tactic | ID | Skills |\n|--------|----|--------|\n| Reconnaissance | TA0043 | 103 |\n| Resource Development | TA0042 | 22 |\n| Initial Access | TA0001 | 467 |\n| Execution | TA0002 | 350 |\n| Persistence | TA0003 | 444 |\n| Privilege Escalation | TA0004 | 464 |\n| Stealth | TA0005 | 442 |\n| Defense Impairment | TA0112 | 92 |\n| Credential Access | TA0006 | 202 |\n| Discovery | TA0007 | 237 |\n| Lateral Movement | TA0008 | 68 |\n| Collection | TA0009 | 172 |\n| Command and Control | TA0011 | 123 |\n| Exfiltration | TA0010 | 82 |\n| Impact | TA0040 | 50 |\n\n## Quick start\n\n```bash\n# Option 1: npx (recommended)\nnpx skills add mukul975/Anthropic-Cybersecurity-Skills\n\n# Option 2: Git clone\ngit clone https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git\ncd Anthropic-Cybersecurity-Skills\n```\n\nWorks immediately with Claude Code, GitHub Copilot, OpenAI Codex CLI, Cursor, Gemini CLI, and any [agentskills.io](https://agentskills.io)-compatible platform. \n\n## 🌍 GARS-2026 — Global Agentic AI Readiness Survey\n\nI'm running a global academic study measuring how ready security professionals,\ndevelopers, and enterprise teams actually are for agentic AI — MCP servers,\ntool calling, governance, and human-in-the-loop workflows.\n\n**If you use this repo, your response would be a genuinely valuable data point.**\n\n📋 **Take the survey (10 min):**\n[Survey Link](https://mahipal.engineer/survey?utm_source=github_repo&utm_medium=readme&utm_campaign=gars2026)\n\n- 60 questions · Anonymous · Supervised by SRH Berlin\n- You get **50 Casky Tokens** for early access to [casky.ai](https://casky.ai)\n- Results published open access under CC-BY 4.0\n\n## 🚀 Try it on the Playground\n\nExperience Casky.ai hands-on — no setup required.\n\n**[→ Launch Playground on Casky.ai](https://casky.ai/?utm_source=github&utm_medium=readme&utm_campaign=cohort_launch#waitlist)**\n\nThe playground lets you:\n- Run live cybersecurity skill exercises against real targets\n- See AI agents execute structured skills in real time\n- Explore MITRE ATT&CK mapped workflows interactively\n- Test threat hunting, DFIR, and penetration testing scenarios\n\nNo installation. No configuration. Just open and start.\n## Why this exists\n\nThe cybersecurity workforce gap hit **4.8 million unfilled roles** globally in 2024 (ISC2). AI agents can help close that gap — but only if they have structured domain knowledge to work from. Today's agents can write code and search the web, but they lack the practitioner playbooks that turn a generic LLM into a capable security analyst.\n\nExisting security tool repos give you wordlists, payloads, or exploit code. None of them give an AI agent the structured decision-making workflow a senior analyst follows: when to use each technique, what prerequisites to check, how to execute step-by-step, and how to verify results. That is the gap this project fills.\n\n**Anthropic Cybersecurity Skills** is not a collection of scripts or checklists. It is an **AI-native knowledge base** built from the ground up for the agentskills.io standard — YAML frontmatter for sub-second discovery, structured Markdown for step-by-step execution, and reference files for deep technical context. Every skill encodes real practitioner workflows, not generated summaries. \n\n## What's inside — 29 security domains\n\n| Domain | Skills | Key capabilities |\n|---|---|---|\n| Cloud Security | 66 | AWS, Azure, GCP hardening · CSPM · cloud attack emulation · cloud forensics |\n| Threat Hunting | 58 | Hypothesis-driven hunts · LOTL detection · EVTX hunting · fleet hunting |\n| Threat Intelligence | 52 | STIX/TAXII · MISP · OpenCTI · feed integration · actor profiling |\n| Network Security | 43 | IDS/IPS · firewall rules · VLAN segmentation · traffic analysis |\n| Web Application Security | 42 | OWASP Top 10 · SQLi · XSS · SSRF · deserialization |\n| Digital Forensics | 41 | Disk imaging · memory forensics · Hayabusa/KAPE/Plaso timelines |\n| Malware Analysis | 39 | Static/dynamic analysis · reverse engineering · sandboxing |\n| Identity & Access Management | 37 | Entra ID/ROADtools · device-code phishing · PAM · zero trust identity |\n| SOC Operations | 35 | Playbooks · escalation workflows · Graph-log detection · tabletop exercises |\n| Red Teaming | 33 | ADCS/Certipy · BloodHound CE · Sliver/Havoc C2 · NTLM relay |\n| Container Security | 33 | K8s RBAC · image scanning · Falco · container escape |\n| Security Operations | 28 | SIEM correlation · log analysis · alert triage |\n| OT/ICS Security | 28 | Modbus · DNP3 · IEC 62443 · historian defense · SCADA |\n| API Security | 28 | GraphQL · REST · OWASP API Top 10 · WAF bypass |\n| Incident Response | 26 | Breach containment · ransomware response · IR playbooks |\n| Vulnerability Management | 25 | Nessus · scanning workflows · patch prioritization · CVSS |\n| Penetration Testing | 21 | Network · web · cloud · mobile · NetExec lateral movement |\n| DevSecOps | 18 | CI/CD security · Trivy IaC/image scanning · code signing |\n| Zero Trust Architecture | 17 | BeyondCorp · CISA maturity model · microsegmentation |\n| Endpoint Security | 17 | EDR · LOTL detection · fileless malware · persistence hunting |\n| Cryptography | 16 | TLS · Ed25519 · post-quantum migration · key manage",
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"readme_content": "# TimesFM\n\nTimesFM (Time Series Foundation Model) is a pretrained time-series foundation\nmodel developed by Google Research for time-series forecasting.\n\n* Paper:\n [A decoder-only foundation model for time-series forecasting](https://arxiv.org/abs/2310.10688),\n ICML 2024.\n* All checkpoints:\n [TimesFM Hugging Face Collection](https://huggingface.co/collections/google/timesfm-release-66e4be5fdb56e960c1e482a6).\n* [Google Research blog](https://research.google/blog/a-decoder-only-foundation-model-for-time-series-forecasting/).\n* TimesFM in Google 1P Products:\n * [BigQuery ML](https://cloud.google.com/bigquery/docs/timesfm-model): Enterprise level SQL queries for scalability and reliability.\n * [Google Sheets](https://workspaceupdates.googleblog.com/2026/02/forecast-data-in-connected-sheets-BigQueryML-TimesFM.html): For your daily spreadsheet. \n * [Vertex Model Garden](https://pantheon.corp.google.com/vertex-ai/publishers/google/model-garden/timesfm): Dockerized endpoint for agentic calling.\n\nThis open version is not an officially supported Google product.\n\n**Latest Model Version:** TimesFM 2.5\n\n**Archived Model Versions:**\n\n- 1.0 and 2.0: relevant code archived in the sub directory `v1`. You can `pip\n install timesfm==1.3.0` to install an older version of this package to load\n them.\n## Update - June 5, 2026\n\nUpdated PyPI to `timesfm=2.0.0`. See [Install](https://github.com/google-research/timesfm#from-pypi).\n\n## Update - Apr. 9, 2026\n\nAdded fine-tuning example using HuggingFace Transformers + PEFT (LoRA) — see\n[`timesfm-forecasting/examples/finetuning/`](timesfm-forecasting/examples/finetuning/).\nAlso added unit tests (`tests/`) and incorporated several community fixes.\n\nShoutout to [@kashif](https://github.com/kashif) and [@darkpowerxo](https://github.com/darkpowerxo). \n\n## Update - Mar. 19, 2026\n\nHuge shoutout to [@borealBytes](https://github.com/borealBytes) for adding the support for [AGENTS](https://github.com/google-research/timesfm/blob/master/AGENTS.md)! TimesFM [SKILL.md](https://github.com/google-research/timesfm/tree/master/timesfm-forecasting) is out.\n\n## Update - Oct. 29, 2025\n\nAdded back the covariate support through XReg for TimesFM 2.5.\n\n\n## Update - Sept. 15, 2025\n\nTimesFM 2.5 is out!\n\nComparing to TimesFM 2.0, this new 2.5 model:\n\n- uses 200M parameters, down from 500M.\n- supports up to 16k context length, up from 2048.\n- supports continuous quantile forecast up to 1k horizon via an optional 30M\n quantile head.\n- gets rid of the `frequency` indicator.\n- has a couple of new forecasting flags.\n\nSince the Sept. 2025 launch, the following improvements have been completed:\n\n1. ✅ Flax version of the model for faster inference.\n2. ✅ Covariate support via XReg (see Oct. 2025 update).\n3. ✅ Documentation, examples, and agent skill (see `timesfm-forecasting/`).\n4. ✅ Fine-tuning example with LoRA via HuggingFace Transformers + PEFT (see `timesfm-forecasting/examples/finetuning/`).\n5. ✅ Unit tests for core layers, configs, and utilities (see `tests/`).\n\n### Install\n\n#### From `PyPI`\n\n```shell\n# Install the package with torch\npip install timesfm[torch]\n# Or with Flax\npip install timesfm[flax]\n# And when XReg is needed\npip install timesfm[xreg]\n```\n\n#### Local Install\n\n1. Clone the repository:\n ```shell\n git clone https://github.com/google-research/timesfm.git\n cd timesfm\n ```\n\n2. Create a virtual environment and install dependencies using `uv`:\n ```shell\n # Create a virtual environment\n uv venv\n \n # Activate the environment\n source .venv/bin/activate\n \n # Install the package in editable mode with torch\n uv pip install -e .[torch]\n # Or with flax\n uv pip install -e .[flax]\n # And when XReg is needed\n uv pip install -e .[xreg]\n ```\n\n3. [Optional] Install your preferred `torch` / `jax` backend based on your OS and accelerators\n(CPU, GPU, TPU or Apple Silicon).:\n\n- [Install PyTorch](https://pytorch.org/get-started/locally/).\n- [Install Jax](https://docs.jax.dev/en/latest/installation.html#installation)\n for Flax.\n\n### Code Example\n\n```python\nimport torch\nimport numpy as np\nimport timesfm\n\ntorch.set_float32_matmul_precision(\"high\")\n\nmodel = timesfm.TimesFM_2p5_200M_torch.from_pretrained(\"google/timesfm-2.5-200m-pytorch\")\n\nmodel.compile(\n timesfm.ForecastConfig(\n max_context=1024,\n max_horizon=256,\n normalize_inputs=True,\n use_continuous_quantile_head=True,\n force_flip_invariance=True,\n infer_is_positive=True,\n fix_quantile_crossing=True,\n )\n)\npoint_forecast, quantile_forecast = model.forecast(\n horizon=12,\n inputs=[\n np.linspace(0, 1, 100),\n np.sin(np.linspace(0, 20, 67)),\n ], # Two dummy inputs\n)\npoint_forecast.shape # (2, 12)\nquantile_forecast.shape # (2, 12, 10): mean, then 10th to 90th quantiles.\n```\n",
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The open source coding agent for building with AI in VS Code, JetBrains, or the CLI.
\n\n
\n \n \n \n \n \n \n
\n\n\n\n---\n\nKilo Code is an AI coding agent that meets you everywhere you work: [VS Code](https://kilo.ai/landing/vs-code), [JetBrains](https://kilo.ai/features/jetbrains-native), and the [CLI](https://kilo.ai/cli). It's open source with open pricing. You pick from 500+ models, switch between them mid-task, and pay the model provider's rate with zero markup. No API keys required to start.\n\n### Installation\n\nPick where you want to run Kilo.\n\n\nVS Code\n\n \n\nInstall the [Kilo Code extension](vscode:extension/kilocode.kilo-code) directly, or grab it from the [VS Code Marketplace](https://marketplace.visualstudio.com/items?itemName=kilocode.Kilo-Code). Create an account and you'll have access to 500+ models including GPT-5.5, Claude Opus 4.7, Claude Sonnet 4.6, and Gemini 3.1 Pro Preview, all at provider pricing.\n\n\n\n\nCLI\n\n \n\n```bash\n# npm\nnpm install -g @kilocode/cli\n\n# curl\ncurl -fsSL https://kilo.ai/cli/install | bash\n\n# pnpm\npnpm add -g @kilocode/cli\n\n# bun\nbun add -g @kilocode/cli\n\n# Homebrew (macOS / Linux)\nbrew install Kilo-Org/tap/kilo\n\n# Arch Linux (AUR)\nparu -S kilo-bin\n```\n\nThen run `kilo` in any project directory to start.\n\n\n\n\nJetBrains\n\n \n\nInstall the [Kilo Code plugin](https://plugins.jetbrains.com/plugin/28350-kilo-code) from the JetBrains Marketplace, or search \"Kilo Code\" in `Settings → Plugins` inside any JetBrains IDE.\n\n\n\n\nCloud Agent\n\n \n\nRun Kilo from the web, no local machine needed, at [app.kilo.ai/cloud](https://app.kilo.ai/cloud).\n\n\n\n\nCode Reviews\n\n \n\nSet up automated AI code reviews on your pull requests at [app.kilo.ai/code-reviews](https://app.kilo.ai/code-reviews).\n\n\n\n\nKiloClaw\n\n \n\nSpin up your always-on AI agent at [app.kilo.ai/claw](https://app.kilo.ai/claw).\n\n\n\n\nInstall the CLI from GitHub Releases (binaries)\n\nDownload the latest binary from the [Releases page](https://github.com/Kilo-Org/kilocode/releases).\n\n| Platform | Asset |\n|---|---|\n| Windows (most PCs) | `kilo-windows-x64.zip` |\n| macOS (Apple Silicon) | `kilo-darwin-arm64.zip` |\n| macOS (Intel) | `kilo-darwin-x64.zip` |\n| Linux x64 | `kilo-linux-x64.tar.gz` |\n| Linux ARM | `kilo-linux-arm64.tar.gz` |\n\nNotes: `x64-baseline` is a compatibility build for older CPUs without AVX. `musl` is the statically linked build for Alpine or minimal Docker images without glibc. `kilo-vscode-*.vsix` is the VS Code extension package, not the CLI. `Source code` archives are for building from source.\n\n\n\n### Agents\n\nKilo ships with specialized agents you switch between depending on the task. You can also build your own custom agents.\n\n- **Code** - The default. Implements and edits code from natural language.\n- **Plan** - Designs architecture and writes implementation plans before any code gets written.\n- **Ask** - Answers questions about your codebase without touching any files.\n- **Debug** - Troubleshoots and traces issues.\n- **Review** - Reviews your changes and surfaces issues across performance, security, style, and test coverage.\n\nLearn more about [agents and custom agents](https://kilo.ai/docs/code-with-ai/agents/using-agents).\n\n### What it does\n\n- **Code generation** from natural language, across multiple files.\n- **Inline autocomplete** with ghost-text suggestions and tab to accept.\n- **Self-checking** so the agent reviews and corrects its own work.\n- **Terminal and browser control** to run commands and automate the web.\n- **MCP marketplace** to find and wire up MCP servers that extend what the agent can do.\n- **500+ models** with mid-task switching, so you can match latency, cost, and reasoning to the job.\n\n### Autonomous Mode (CI/CD)\n\nRun `kilo run` with `--auto` for fully autonomous operation with no prompts, built for CI/CD pipelines:\n\n```bash\nkilo run --auto \"run tests and fix any failures\"\n```\n\n`--auto` disables all permission prompts and lets the agent execute any action without confirmation. Only use it in trusted environments.\n\n### Documentation\n\nFor configuration and everything else, [head over to the docs](https://kilo.ai/docs).\n\n### Contributing\n\nContributions are welcome from developers, writers, and everyone in between. Start with the [Contributing Guide](/CONTRIBUTING.md) for environment setup, coding standards, and how to open a pull request. See [RELEASING.md](RELEASING.md) for the VS Code extension and CLI release process, and [packages/kilo-jetbrains/RELEASING.md](packages/kilo-jetbrains/RELEASING.md) for the JetBrains plugin.\n\nPlease review our [Code of Conduct](/CODE_OF_CONDUCT.md) before getting involved.\n\n### License\n\nMIT. You're free to use, modify, and distribute this code, including commercially, as long as you keep the attribution and license notices. See [License](/LICENSE).\n\n### FAQ\n\n\nWhere did Kilo CLI come from?\n\nKilo CLI is a fork of [OpenCode](https://github.com/Kilo-Org/kilocode), enhanced to work within the Kilo agentic engineering platform.\n\n\n\n---\n\n**Join the community** [Discord](https://kilo.ai/discord) | [X](https://x.com/kilocode) | [Reddit](https://www.reddit.com/r/kilocode/)\n",
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\n \n \n \n\n \n\n Cognee - The Open-Source AI Memory Platform for Agents\n\n
\n\nCognee is the open-source AI memory platform that gives AI agents persistent long-term memory across sessions. Ingest data in any format, build a self-hosted knowledge graph, and let every agent recall, connect, and act with full context\n\n
\n\n📄 Read the research paper: [Optimizing the Interface Between Knowledge Graphs and LLMs for Complex Reasoning](https://arxiv.org/abs/2505.24478) — Markovic et al., 2025\n\n\n## About Cognee\n\nCognee is an open-source AI memory platform for AI Agents. Ingest data in any format, and Cognee continuously builds a self-hosted knowledge graph that gives your agents persistent long-term memory across sessions. Cognee combines vector embeddings, graph reasoning, and cognitive-science-grounded ontology generation to make documents both searchable by meaning and connected by relationships that evolve as your knowledge does.\n\n:star: _Help us reach more developers and grow the cognee community. Star this repo!_\n\n:books: _Check our detailed [documentation](https://docs.cognee.ai/getting-started/installation#environment-configuration) for setup and configuration._\n\n:crab: _Available as a plugin for your OpenClaw — [cognee-openclaw](https://www.npmjs.com/package/@cognee/cognee-openclaw)_\n\n✴️ _Available as a plugin for your Claude Code — [claude-code-plugin](https://github.com/topoteretes/cognee-integrations/tree/main/integrations/claude-code)_\n\n\n\n### Why use Cognee:\n\n- Easily Build Company Brain - unify data from various sources in one place and enable Agents with your domain knowledge\n- Knowledge infrastructure — unified ingestion, graph/vector search, runs locally, ontology grounding, multimodal\n- Persistent and Learning Agents - learn from feedback, context management, cross-agent knowledge sharing\n- Reliable and Trustworthy Agents - agentic user/tenant isolation, traceability, OTEL collector, audit traits\n\n### Product Features\n\n
\n \n
\n\n## Basic Usage & Feature Guide\n\nTo learn more, [check out this short, end-to-end Colab walkthrough](https://colab.research.google.com/drive/12Vi9zID-M3fpKpKiaqDBvkk98ElkRPWy?usp=sharing) of Cognee's core features.\n\n[](https://colab.research.google.com/drive/12Vi9zID-M3fpKpKiaqDBvkk98ElkRPWy?usp=sharing)\n\n## Quickstart\n\nLet’s try Cognee in just a few lines of code.\n\n### Prerequisites\n\n- Python 3.10 to 3.14\n\n### Step 1: Install Cognee\n\nYou can install Cognee with **pip**, **poetry**, **uv**, or your preferred Python package manager.\n\n```bash\nuv pip install cognee\n```\n\n### Step 2: Configure the LLM\n```python\nimport os\nos.environ[\"LLM_API_KEY\"] = \"YOUR OPENAI_API_KEY\"\n```\nAlternatively, create a `.env` file using our [template](https://github.com/topoteretes/cognee/blob/main/.env.template).\n\nTo integrate other LLM providers, see our [LLM Provider Documentation](https://docs.cognee.ai/setup-configuration/llm-providers).\n\n### Step 3: Run the Pipeline\n\nCognee's API gives you four operations — `remember`, `recall`, `forget`, and `improve`:\n\n```python\nimport cognee\nimport asyncio\n\n\nasync def main():\n # Store permanently in the knowledge graph (runs add + cognify + improve)\n await cognee.remember(\"Cognee turns documents into AI memory.\")\n\n # Store in session memory (fast cache, syncs to graph in background)\n await cognee.remember(\"User prefers detailed explanations.\", session_id=\"chat_1\")\n\n # Query with auto-routing (picks best search strategy automatically)\n results = await cognee.recall(\"What does Cognee do?\")\n for result in results:\n print(result)\n\n # Query session memory first, fall through to graph if needed\n results = await cognee.recall(\"What does the user prefer?\", session_id=\"chat_1\")\n for result in results:\n print(result)\n\n # Delete when done\n await cognee.forget(dataset=\"main_dataset\")\n\n\nif __name__ == '__main__':\n asyncio.run(main())\n\n```\n\n### Use the Cognee CLI\n\n```bash\ncognee-cli remember \"Cognee turns documents into AI memory.\"\n\ncognee-cli recall \"What does Cognee do?\"\n\ncognee-cli forget --all\n```\n\nTo open the local UI, run:\n```bash\ncognee-cli -ui\n```\n\n> **Note:** The MCP server launched by `cognee-cli -ui` runs inside a Docker container.\n> Docker Desktop, Colima, or any OCI-compatible runtime with a working `docker` CLI is\n> required. See [Docker & Colima Setup](docs/docker-colima-setup.md) for details.\n\n## Run with Docker\n\nPrefer containers? Cognee publishes prebuilt images to Docker Hub on every push to `main`:\n[`cognee/cognee`](https://hub.docker.com/r/cognee/cognee) (the API server) and\n[`cognee/cognee-mcp`](https://hub.docker.com/r/cognee/cognee-mcp) (the MCP server).\n\n### Option A — Docker Compose (build from source)\n\nClone the repo, create a `.env` with at least `LLM_API_KEY`, then:\n\n```bash\ncp .env.template .env # then edit .env and set LLM_API_KEY\n\n# Start the API server (http://localhost:8000)\ndocker compose up\n\n# Optional profiles (combine as needed):\ndocker compose --profile ui up # + frontend on http://localhost:3000\ndocker compose --profile mcp up # + MCP server on http://localhost:8001\ndocker compose --profile postgres up # + Postgres/PGVector\ndocker compose --profile neo4j up # + Neo4j\n```\n\n> The `cognee` and `cognee-mcp` services publish different host ports (`8000` vs `8001`),\n> so you can run both at once.\n\n### Option B — Pull the prebuilt image (no clone required)\n\n```bash\n# Create a minimal .env in the current directory\necho 'LLM_API_KEY=\"YOUR_OPENAI_API_KEY\"' > .env\n\n# API server\ndocker run --env-file ./.env -p 8000:8000 --rm -it cognee/cognee:main\n\n# MCP server (HTTP transport)\ndocker pull cognee/cognee-mcp:main\ndocker run -e TRANSPORT_MODE=http --env-file ./.env -p 8000:8000 --rm -it cognee/cognee-mcp:main\n```\n\nSee the [MCP server README](cognee-mcp/README.md) for SSE/stdio transports, optional\nextras, and MCP client configuration.\n\n## Use with AI Agents\n\n### Claude Code\n\nInstall the [Cognee memory plugin](https://github.com/topoteretes/cognee-integrations/tree/main/integrations/claude-code) to give Claude Code persistent memory across sessions. The plugin automatically captures tool calls into session memory via hooks and syncs to the permanent knowledge graph at session end.\n\n**Setup:**\n\n```bash\n# Install cognee\npip install cognee\n\n# Configure\nexport LLM_API_KEY=\"your-openai-key\"\n\n# Clone the plugin\ngit clone https://github.com/topoteretes/cognee-integrations.git\n\n# Enable it (add to ~/.zshrc for permanent use)\nclaude --plugin-dir ./cognee-integrations/integrations/claude-code\n```\n\nOr connect to Cognee Cloud instead of running locally:\n\n```bash\nexport COGNEE_SERVICE_URL=\"https://your-instance.cognee.ai\"\nexport COGNEE_API_KEY=\"ck_...\"\n```\n\nThe plugin hooks into Claude Code's lifecycle — `SessionStart` initializes memory, `PostToolUse` captures actions, `UserPromptSubmit` injects relevant context, `PreCompact` preserves memory across context resets, and `SessionEnd` bridges session data into the permanent graph.\n\n### Connect to Cognee Cloud\n\nPoint any Python agent at a managed Cognee instance — all SDK calls route to the cloud:\n\n```python\nimport cognee\n\nawait cognee.serve(url=\"https://your-instance.cognee.ai\", api_key=\"ck_...\")\n\nawait cognee.remember(\"important context\")\nresults = await cognee.recall(\"what happened?\")\n\nawait cognee.disconnect()\n```\n\n## Examples\n\nBrowse more examples in the [`examples/`](examples/) folder — demos, guides, custom pipelines, and database configurations.\n\n**Use Case 1 — Customer Support Agent**\n\n```python\nGoal: Resolve customer issues using their personal data across finance, support, and product history.\n\nUser: \"My invoice looks wrong and the issue is still not resolved.\"\n\nCognee tracks: past interactions, failed actions, resolved cases, product history\n\n# Agent response:\nAgent: \"I found 2 similar billing cases resolved last month.\n The issue was caused by a sync delay between payment\n and invoice systems — a fix was applied on your account.\"\n\n# What happens under the hood:\n- Unifies data sources from various company channels\n- Reconstructs the interaction timeline and tracks outcomes\n- Retrieves similar resolved cases\n- Maps to the best resolution strategy\n- Updates memory after execution so the agent never repeats the same mistake\n```\n\n**Use Case 2 — Expert Knowledge Distillation (SQL Copilot)**\n\n```python\nGoal: Help junior analysts solve tasks by reusing expert-level queries, patterns, and reasoning.\n\nUser: \"How do I calculate customer retention for this dataset?\"\n\nCognee tracks: expert SQL queries, workflow patterns, schema structures, successful implementations\n\n# Agent response:\nAgent: \"Here's how senior analysts solved a similar retention query.\n Cognee matched your schema to a known structure and adapted\n the expert's logic to fit your dataset.\"\n\n# What happens under the hood:\n- Extracts and stores pattern",
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\n\n[Penpot video](https://github.com/user-attachments/assets/7c67fd7c-04d3-4c9b-88ec-b6f5e23f8332)\n\nPenpot is the open-source design platform for teams that build digital products at scale.\n\nPenpot’s key strength lies in giving you **full ownership of your design infrastructure**. Built on open source and designed for [self-hosting](https://help.penpot.app/technical-guide/getting-started/), it puts teams in complete control of their design environment supporting strict compliance and governance requirements. Whether used in the **browser or deployed on your own servers**, Penpot **works with open standards** like SVG, CSS, HTML, and JSON. \n\nReal-time collaboration strengthens this foundation, helping teams scale and bring design closer to the product through top-tier capabilities. Additionally, developers feel at home using Penpot, because design is expressed as code, enabling a direct translation and shipping products faster. \n\nBest-in-class native [Design Tokens](https://penpot.dev/collaboration/design-tokens) provide a single source of truth between design and development. They ensure consistency, improve collaboration, and make it easier to manage complex design systems.\n\nThe [MCP server](https://penpot.app/penpot-mcp-server) takes it further by enabling multi-directional workflows between design and code. A [powerful open API](https://help.penpot.app/mcp/#quick-start) and plugin system makes the workspace programmable, enabling automation, AI-driven workflows, and integrations with the tools and systems you already use.\n\nWith [CSS Grid and Flex Layout](https://help.penpot.app/user-guide/designing/flexible-layouts/), teams can design responsive interfaces that behave like real code from the start.\n\nCombined, these features turn Penpot into a **full-stack design platform** for building scalable design systems and fully integrated product development processes.\n\nIf your organization is scaling and needs extra support, we’re here to help. [Talk to us](https://penpot.app/talk-to-us)\n\n## Table of contents ##\n\n- [Why Penpot](#why-penpot)\n- [Getting Started](#getting-started)\n- [Community](#community)\n- [Contributing](#contributing)\n- [Resources](#resources)\n- [License](#license)\n\n## Why Penpot ##\n\nPenpot connects design, code, and AI workflows through a code-based approach, making designs readable by developers and AI via the MCP server. This approach helps teams ship what’s actually designed and manage design systems at scale with powerful design tokens. As a self-hosted, open-source and real-time collaboration platform, Penpot offers full flexibility, security, and ownership without vendor lock-in. Learn more about [why Penpot](https://penpot.app/why-penpot) is the platform for your team.\n\n### Plugin system ###\n\n[Penpot plugins](https://penpot.app/penpothub/plugins) let you expand the platform's capabilities, give you the flexibility to integrate it with other apps, and design custom solutions.\n\n### Designed for developers ###\n\nPenpot was built to serve both designers and developers and create a fluid design-code process. You have the choice to enjoy real-time collaboration or play \"solo\".\n\n### Inspect mode ###\n\nWork with ready-to-use code and make your workflow easy and fast. The inspect tab gives instant access to SVG, CSS and HTML code.\n\n### Integrations ###\n\nPenpot offers [integration](https://penpot.app/integrations-api) into the development toolchain, thanks to its support for webhooks and an API accessible through access tokens.\n\n### Building Design Systems: design tokens, components and variants ###\n\nPenpot brings [design systems](https://penpot.app/design/design-systems) to code-minded teams: a single source of truth with native Design Tokens, Components, and Variants for scalable, reusable, and consistent UI across projects and platforms.\n\n\n\n## Getting started ##\n\nPenpot is the only design & prototype platform that is deployment agnostic. You can use it in our [SAAS](https://design.penpot.app) or deploy it anywhere.\n\nLearn how to install it with Docker, Kubernetes, Elestio or other options on [our website](https://penpot.app/self-host).\n\n## Community ##\n\nWe love the Open Source software community. Contributing is our passion and if it’s yours too, participate and [improve](https://community.penpot.app/c/help-us-improve-penpot/7) Penpot. All your designs, code and ideas are welcome!\n\nWant to go a step further? Become a [Penpot Ambassador](https://penpot.app/ambassador-program) and help grow the Penpot community in your region while contributing to a global, open design ecosystem.\n\nIf you need help or have any questions; if you’d like to share your experience using Penpot or get inspired; if you’d rather meet our community of developers and designers, [join our Community](https://community.penpot.app/)!\n\nCategories include:\n\n- [Ask the Community](https://community.penpot.app/c/ask-for-help-using-penpot/6)\n- [Troubleshooting](https://community.penpot.app/c/technical/8)\n- [Help us Improve Penpot](https://community.penpot.app/c/help-us-improve-penpot/7)\n- [Events and Announcements](https://community.penpot.app/c/announcements/5)\n- [Penpot in your language](https://community.penpot.app/c/penpot-in-your-language/12)\n- [Education](https://community.penpot.app/c/education/28)\n\n\n\n### Code of Conduct ###\n\nAnyone who contributes to Penpot, whether through code, in the community, or at an event, must adhere to the\n[code of conduct](https://help.penpot.app/contributing-guide/coc/) and foster a positive and safe environment.\n\n### Contributing ###\n\nAny contribution will make a difference to improve Penpot. How can you get involved?\n\nChoose your way:\n\n- Create and [share Libraries & Templates](https://penpot.app/libraries-templates.html) that will be helpful for the community.\n- Invite your [team to join](https://design.penpot.app/#/auth/register).\n- Give this repo a star and follow us on Social Media: [Mastodon](https://fosstodon.org/@penpot/), [Youtube](https://www.youtube.com/c/Penpot), [Instagram](https://instagram.com/penpot.app), [Linkedin](https://www.linkedin.com/company/penpotdesign), [Peertube](https://peertube.kaleidos.net/a/penpot_app), [X](https://twitter.com/penpotapp) and [BlueSky](https://bsky.app/profile/penpot.app).\n- Participate in the [Community](https://community.penpot.app/) space by asking and answering questions; reacting to others’ articles; opening your own conversations and following along on decisions affecting the project.\n- Report bugs with our easy [guide for bugs hunting](https://help.penpot.app/contributing-guide/reporting-bugs/) or [GitHub issues](https://github.com/penpot/penpot/issues).\n- Become a [translator](https://help.penpot.app/contributing-guide/translations).\n- Give feedback: [Email us](mailto:support@penpot.app).\n- **Contribute to Penpot's code:** [Watch this video](https://www.youtube.com/watch?v=TpN0osiY-8k) by Alejandro Alonso, CIO and developer at Penpot, where he gives us a hands-on demo of how to use Penpot’s repository and make changes in both front and back end.\n\nTo find (almost) everything you need to know on how to contribute to Penpot, refer to the [contributing guide](https://help.penpot.app/contributing-guide/).\n\n\n\n## Resources ##\n\nYou can ask and answer questions, have open-ended conversations, and follow along on decisions affecting the project.\n\n💾 [Documentation](https://help.penpot.app/technical-guide/)\n\n🚀 [Getting Started](https://help.penpot.app/technical-guide/getting-started/)\n\n✏️ [Tutorials](https://www.youtube.com/playlist?list=PLgcCPfOv5v54WpXhHmNO7T-YC7AE-SRsr)\n\n🏘️ [Architecture](https://help.penpot.app/technical-guide/developer/architecture/)\n\n📚 [Dev Diaries](https://penpot.app/dev-diaries.html)\n\n🧑🏫 [UI Design Course](https://penpot.app/courses/)\n\n\n## License ##\n\n```\nThis Source Code Form is subject to the terms of the Mozilla Public\nLicense, v. 2.0. If a copy of the MPL was not distributed with this\nfile, You can obtain one at http://mozilla.org/MPL/2.0/.\n\nCopyright (c) KALEIDOS INC Sucursal en España SL\n```\nPenpot is a Kaleidos’ [open source project](https://kaleidos.net/)\n",
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\n \n
\n\n
Voicebox
\n\n
\n The open-source AI voice studio. \n Clone any voice. Generate speech. Dictate into any app. Talk to agents in voices you own. \n The full voice I/O stack, running locally on your machine.\n
\n Click the image above to watch the demo video on voicebox.sh\n
\n\n \n\n
\n \n
\n\n
\n \n
\n\n \n\n## What is Voicebox?\n\nVoicebox is a **local-first AI voice studio** — a free and open-source alternative to **ElevenLabs** and **WisprFlow** in one app. Clone voices from a few seconds of audio, generate speech in 23 languages across 7 TTS engines, dictate into any text field with a global hotkey, and give any MCP-aware AI agent a voice of your choosing.\n\nThe two cloud incumbents sit on opposite halves of the voice I/O loop — ElevenLabs on output, WisprFlow on input. Voicebox does both, bridges them with a bundled local LLM for refinement and per-profile personas, and runs the whole thing on your machine.\n\n- **Complete privacy** — models, voice data, and captures never leave your machine\n- **7 TTS engines** — Qwen3-TTS, Qwen CustomVoice, LuxTTS, Chatterbox Multilingual, Chatterbox Turbo, HumeAI TADA, and Kokoro\n- **Voice cloning and preset voices** — zero-shot cloning from a reference sample, or 50+ curated preset voices via Kokoro and Qwen CustomVoice\n- **23 languages** — from English to Arabic, Japanese, Hindi, Swahili, and more\n- **Post-processing effects** — pitch shift, reverb, delay, chorus, compression, and filters\n- **Expressive speech** — paralinguistic tags like `[laugh]`, `[sigh]`, `[gasp]` via Chatterbox Turbo; natural-language delivery control via Qwen CustomVoice\n- **Unlimited length** — auto-chunking with crossfade for scripts, articles, and chapters\n- **Stories editor** — multi-track timeline for conversations, podcasts, and narratives\n- **Voice input** — global dictation hotkey with push-to-talk and toggle modes, accessibility-verified auto-paste on macOS, in-app mic on every text field, Whisper-based STT\n- **Agent voice output** — one tool call (`voicebox.speak`) and any MCP-aware agent (Claude Code, Cursor, Cline) speaks to you in a voice you've cloned\n- **Voice personalities** — attach a free-form persona to any voice profile, then Compose, Rewrite, or Respond via a bundled local LLM — agents can invoke the same modes over MCP\n- **API-first** — REST API plus a built-in MCP server for integrating voice I/O into your own apps and agents\n- **Native performance** — built with Tauri (Rust), not Electron\n- **Runs everywhere** — macOS (MLX/Metal), Windows (CUDA), Linux, AMD ROCm, Intel Arc, Docker\n\n---\n\n## Download\n\n| Platform | Download |\n| --------------------- | ------------------------------------------------------ |\n| macOS (Apple Silicon) | [Download DMG](https://voicebox.sh/download/mac-arm) |\n| macOS (Intel) | [Download DMG](https://voicebox.sh/download/mac-intel) |\n| Windows | [Download MSI](https://voicebox.sh/download/windows) |\n| Docker | `docker compose up` |\n\n> **[View all binaries →](https://github.com/jamiepine/voicebox/releases/latest)**\n\n> **Linux** — Pre-built binaries are not yet available. See [voicebox.sh/linux-install](https://voicebox.sh/linux-install) for build-from-source instructions.\n\n> **Having trouble?** See the [Troubleshooting Guide](docs/content/docs/overview/troubleshooting.mdx) for common install, generation, model-download, and GPU issues.\n\n---\n\n## Features\n\n### Multi-Engine Voice Cloning\n\nSeven TTS engines with different strengths, switchable per-generation:\n\n| Engine | Languages | Strengths |\n| --------------------------- | --------- | ---------------------------------------------------------------------------------------------------------------------------------------- |\n| **Qwen3-TTS** (0.6B / 1.7B) | 10 | High-quality multilingual cloning, delivery instructions (\"speak slowly\", \"whisper\") |\n| **Qwen CustomVoice** | 10 | 9 curated preset voices with natural-language delivery control — no reference audio required |\n| **LuxTTS** | English | Lightweight (~1GB VRAM), 48kHz output, 150x realtime on CPU |\n| **Chatterbox Multilingual** | 23 | Broadest language coverage — Arabic, Danish, Finnish, Greek, Hebrew, Hindi, Malay, Norwegian, Polish, Swahili, Swedish, Turkish and more |\n| **Chatterbox Turbo** | English | Fast 350M model with paralinguistic emotion/sound tags |\n| **TADA** (1B / 3B) | 10 | HumeAI speech-language model — 700s+ coherent audio, text-acoustic dual alignment |\n| **Kokoro** | 8 | 50 curated preset voices, tiny 82M model, fast CPU inference |\n\n### Emotions & Paralinguistic Tags\n\nOnly **Chatterbox Turbo** interprets paralinguistic tags like `[laugh]` and\n`[sigh]`. Qwen3-TTS, LuxTTS, Chatterbox Multilingual, and HumeAI TADA read them\nliterally as text.\n\nWith **Chatterbox Turbo** selected, type `/` in the text input to open the tag\ninserter and add expressive tags inline with speech:\n\n`[laugh]` `[chuckle]` `[gasp]` `[cough]` `[sigh]` `[groan]` `[sniff]` `[shush]` `[clear throat]`\n\n### Post-Processing Effects\n\n8 audio effects powered by Spotify's `pedalboard` library. Apply after generation, preview in real time, build reusable presets.\n\n| Effect | Description |\n| ---------------- | --------------------------------------------- |\n| Pitch Shift | Up or down by up to 12 semitones |\n| Reverb | Configurable room size, damping, wet/dry mix |\n| Delay | Echo with adjustable time, feedback, and mix |\n| Chorus / Flanger | Modulated delay for metallic or lush textures |\n| Compressor | Dynamic range compression |\n| Gain | Volume adjustment (-40 to +40 dB) |\n| High-Pass Filter | Remove low frequencies |\n| Low-Pass Filter | Remove high frequencies |\n\nShips with 4 built-in presets (Robotic, Radio, Echo Chamber, Deep Voice) and supports custom presets. Effects can be assigned per-profile as defaults.\n\n### Unlimited Generation Length\n\nText is automatically split at sentence boundaries and each chunk is generated independently, then crossfaded together. Works with all engines.\n\n- Configurable auto-chunking limit (100–5,000 chars)\n- Crossfade slider (0–200ms) for smooth transitions\n- Max text length: 50,000 characters\n- Smart splitting respects abbreviations, CJK punctuation, and `[tags]`\n\n### Generation Versions\n\nEvery generation supports multiple versions with provenance tracking:\n\n- **Original** — clean TTS output, always preserved\n- **Effects versions** — apply different effects chains from any source version\n- **Takes** — regenerate with a new seed for variation\n- **Source tracking** — each version records its lineage\n- **Favorites** — star generations for quick access\n\n### Async Generation Queue\n\nGeneration is non-blocking. Submit and immediately start typing the next one.\n\n- Serial execution queue prevents GPU contention\n- Real-time SSE status streaming\n- Failed generations can be retried\n- Stale generations from crashes auto-recover on startup\n\n### Voice Profile Management\n\n- Create profiles from audio files or record directly in-app\n- Import/export profiles to share or back up\n- Multi-sample support for higher quality cloning\n- Per-profile default effects chains\n- Organize with descriptions and language tags\n\n### Stories Editor\n\nMulti-voice timeline editor for conversations, podcasts, and narratives.\n\n- Multi-track composition with drag-and-drop\n- Inline audio trimming and splitting\n- Auto-playback with synchronized playhead\n- Version pinning per track clip\n\n### Global Dictation & Voice Input\n\nThe other half of the voice I/O loop. Hold a hotkey anywhere on your system, speak, release — on macOS the transcript pastes straight into the focused text field. Or hit the mic on any Voicebox text input and dictate directly into the app.\n\n- **Configurable chord bindings** — hold-to-speak and tap-to-toggle chords, each rebindable in the in-app chord picker. Holding push-to-talk and tapping `Space` mid-hold upgrades into a toggle session without a gap in audio\n- **Target-aware paste (macOS)** — accessibility-verified injection into the focused text field, with atomic clipboard save/restore so your clipboard isn't clobbered\n- **First-run permissions UX** — in-app gates walk you through the macOS Accessibility and Input Monitoring grants with deep-links to System Settings\n- **In-app mic button** on every Voicebox text field — generation form, profile descriptions, story titles, anywhere you'd type\n- **LLM refinement** — optional cleanup of ums, stutters, and false starts before paste\n- **On-screen pill** — floating overlay surfacing `recording`, `transcribing`, `refining`, and `speaking` states. Same pill agents use when they speak to you, so there's one mental model for both directions of the loop\n\n### Speech-to-Text\n\nVoicebox runs OpenAI Whisper for transcription — the same model that backs dictation, the Captures tab, and the `/transcribe` API. Running on MLX (Apple Silicon) or PyTorch (CUDA / ROCm / DirectML / CPU) depending on your platform.\n\n| Size | Notes ",
"manifest_file": "package.json",
"manifest_content": "{\n \"name\": \"voicebox\",\n \"version\": \"0.5.0\",\n \"private\": true,\n \"workspaces\": [\n \"app\",\n \"tauri\",\n \"web\",\n \"landing\"\n ],\n \"scripts\": {\n \"dev\": \"bun run setup:dev && cd tauri && bun run tauri dev\",\n \"dev:web\": \"cd web && bun run dev\",\n \"dev:landing\": \"cd landing && bun run dev\",\n \"dev:server\": \"uvicorn backend.main:app --reload --port 17493\",\n \"setup:dev\": \"bun run scripts/setup-dev-sidecar.js\",\n \"build\": \"./scripts/build-server.sh && cd tauri && bun run tauri build\",\n \"build:web\": \"cd web && bun run build\",\n \"build:landing\": \"cd landing && bun run build\",\n \"build:release\": \"./scripts/prepare-release.sh\",\n \"generate:api\": \"./scripts/generate-api.sh\",\n \"generate:keys\": \"cd tauri && bun tauri signer generate -w ~/.tauri/voicebox.key\",\n \"build:server\": \"./scripts/build-server.sh\",\n \"update:icons\": \"./scripts/update-icons.sh\",\n \"convert:assets\": \"./scripts/convert-assets.sh\",\n \"lint\": \"biome lint .\",\n \"typecheck\": \"bunx tsc -p app/tsconfig.json --noEmit && cd web && bunx tsc --noEmit\",\n \"lint:fix\": \"biome lint --write .\",\n \"format\": \"biome format --write .\",\n \"format:check\": \"biome format .\",\n \"check\": \"biome check .\",\n \"check:fix\": \"biome check --write .\",\n \"ci\": \"bun run typecheck && bun run build:web\"\n },\n \"devDependencies\": {\n \"@biomejs/biome\": \"2.3.12\",\n \"@types/node\": \"^20.0.0\",\n \"tailwindcss\": \"^4.1.18\",\n \"typescript\": \"^5.6.0\"\n },\n \"engines\": {\n \"bun\": \">=1.0.0\"\n },\n \"packageManager\": \"bun@1.3.8\",\n \"dependencies\": {\n \"loaders.css\": \"^0.1.2\",\n \"react-loaders\": \"^3.0.1\"\n }\n}\n",
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{
"owner": "OpenCut-app",
"name": "OpenCut",
"full_name": "OpenCut-app/OpenCut",
"url": "https://github.com/OpenCut-app/OpenCut",
"description": "The open-source CapCut alternative",
"language": "TypeScript",
"total_stars": 59699,
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"stars_this_period": 3550,
"source_slice": "all",
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"metadata": {
"topics": [
"editor",
"oss",
"videoeditor"
],
"license": "MIT",
"open_issues": 329,
"created_at": "2025-06-22T08:02:17Z",
"pushed_at": "2026-06-21T13:15:27Z",
"homepage": "https://opencut.app",
"default_branch": "main",
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"readme_content": "
\n
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\n \n
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OpenCut
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A free and open source video editor for web, desktop, and mobile.
\n\n\n\n---\n\n## What It Does\n\n- **500+ curated news feeds** across 15 categories, AI-synthesized into briefs\n- **Dual map engine** — 3D globe (globe.gl) and WebGL flat map (deck.gl) with 56 map layer types\n- **Cross-stream correlation** — military, economic, disaster, and escalation signal convergence\n- **Country Instability Index (CII)** — server-authoritative CII v8 stress scoring for 31 Tier-1 countries\n- **Finance radar** — 29 stock exchanges, commodities, crypto, and 7-signal market composite\n- **Local AI** — run everything with Ollama, no API keys required\n- **6 site variants** from a single codebase (world, tech, finance, commodity, happy, energy)\n- **Native desktop app** (Tauri 2) for macOS, Windows, and Linux\n- **24 languages** with native-language feeds and RTL support\n\nFor the full feature list, architecture, data sources, and algorithms, see the **[documentation](https://www.worldmonitor.app/docs/documentation)**.\n\n---\n\n## Support Status\n\nAll site variants and desktop binaries are built from a single codebase and ship from the same release process. The table below clarifies maintenance status so you know which surfaces are safe to depend on.\n\n| Surface | Status | Notes |\n|---------|--------|-------|\n| `worldmonitor.app`, `tech.`, `finance.`, `commodity.`, `happy.`, `energy.` | Stable | Public deployments built from this repo, actively maintained |\n| Desktop binaries (Windows / macOS Apple Silicon / macOS Intel / Linux AppImage) | Stable | One Tauri binary that switches variants in-app; current CI release targets are `full` and `tech` |\n\nIssues filed against any of the above are triaged from the same backlog — see the [issues board](https://github.com/koala73/worldmonitor/issues) for currently-open work.\n\n---\n\n## Quick Start\n\n```bash\ngit clone https://github.com/koala73/worldmonitor.git\ncd worldmonitor\nnpm install\nnpm run dev\n```\n\nOpen [localhost:3000](http://localhost:3000). The app runs with no environment variables.\n\nFeature-specific data sources may require credentials — for example, the flight-price command (`fly LON DXB`) needs `TRAVELPAYOUTS_API_TOKEN` to return live quotes; without it the command shows a \"credentials required\" message rather than synthetic data. See `.env.example` for the full list.\n\nFor variant-specific development:\n\n```bash\nnpm run dev:tech # tech.worldmonitor.app\nnpm run dev:finance # finance.worldmonitor.app\nnpm run dev:commodity # commodity.worldmonitor.app\nnpm run dev:happy # happy.worldmonitor.app\nnpm run dev:energy # energy.worldmonitor.app\n```\n\nSee the **[self-hosting guide](https://www.worldmonitor.app/docs/getting-started)** for deployment options (Vercel, Docker, static).\n\n---\n\n## Tech Stack\n\n| Category | Technologies |\n|----------|-------------|\n| **Frontend** | Vanilla TypeScript, Vite, globe.gl + Three.js, deck.gl + MapLibre GL |\n| **Desktop** | Tauri 2 (Rust) with Node.js sidecar |\n| **AI/ML** | Ollama / Groq / OpenRouter, Transformers.js (browser-side) |\n| **API Contracts** | Protocol Buffers (276 protos, 34 services), sebuf HTTP annotations |\n| **Deployment** | Vercel Edge Functions (60+), Railway relay, Tauri, PWA |\n| **Caching** | Redis (Upstash), 3-tier cache, CDN, service worker |\n\nFull stack details in the **[architecture docs](https://www.worldmonitor.app/docs/architecture)**.\n\n---\n\n## Flight Data\n\nFlight data provided gracefully by [Wingbits](https://wingbits.com?utm_source=worldmonitor&utm_medium=referral&utm_campaign=worldmonitor), the most advanced ADS-B flight data solution.\n\n---\n\n## Data Sources\n\nWorldMonitor aggregates 65+ external providers and APIs across geopolitics, finance, energy, climate, aviation, cyber, military, infrastructure, and news intelligence — surfaced through 500+ curated feeds and tracked by a freshness monitor covering 35 source groups. See the full [data sources catalog](https://www.worldmonitor.app/docs/data-sources) for providers, feed tiers, and collection methods.\n\n---\n\n## Contributing\n\nContributions welcome! See [CONTRIBUTING.md](./CONTRIBUTING.md) for guidelines.\n\n```bash\nnpm run typecheck # Type checking\nnpm run build:full # Production build\n```\n\n---\n\n## License\n\n**AGPL-3.0-only** for the source code. Commercial use is permitted under the AGPL when you comply with its copyleft and source-availability terms.\n\n| Use Case | Allowed? |\n|----------|----------|\n| Personal / research / educational | Yes, under AGPL-3.0-only |\n| Self-hosted instance | Yes, under AGPL-3.0-only |\n| Fork and modify | Yes, share source under AGPL-3.0-only when required |\n| Commercial use / SaaS | Yes, under AGPL-3.0-only when you comply with AGPL obligations |\n| Private-source proprietary use or official branding rights | Separate commercial or trademark permission needed |\n\nSee [LICENSE](LICENSE) for the full code license and [docs/license.mdx](docs/license.mdx) for a plain-language summary. Commercial licensing is available as an alternative option for teams that need non-AGPL terms.\n\nCopyright (C) 2024-2026 Elie Habib. All rights reserved.\n\n---\n\n## Author\n\n**Elie Habib** — [GitHub](https://github.com/koala73)\n\n## Contributors\n\n\n \n\n\n## Security Acknowledgments\n\nWe thank the following researchers for responsibly disclosing security issues:\n\n- **Cody Richard** — Disclosed three security findings covering IPC command exposure, renderer-to-sidecar trust boundary analysis, and fetch patch credential injection architecture (2026)\n\nSee our [Security Policy](./SECURITY.md) for responsible disclosure guidelines.\n\n---\n\n
\n An in-process SQL database, compatible with SQLite.\n
\n\n
\n \n \n \n \n \n \n \n \n \n \n \n
\n
\n \n
\n
\n \n
\n\n---\n\n## About\n\nTurso Database is an in-process SQL database written in Rust, compatible with SQLite.\n\n> **⚠️ Warning:** This software is in BETA. It may still contain bugs and unexpected behavior. Use caution with production data and ensure you have backups.\n\n## Features and Roadmap\n\n* **SQLite compatibility** for SQL dialect, file formats, and the C API [see [document](COMPAT.md) for details]\n* **`BEGIN CONCURRENT`** for improved write throughput using multi-version concurrency control (MVCC).\n* **Change data capture (CDC)** for real-time tracking of database changes.\n* **Multi-language support** for\n * [Go](bindings/go)\n * [JavaScript](bindings/javascript)\n * [Java](bindings/java)\n * [.NET](bindings/dotnet)\n * [Python](bindings/python)\n * [Rust](bindings/rust)\n * [WebAssembly](bindings/javascript)\n* **Asynchronous I/O** support on Linux with `io_uring`\n* **Cross-platform** support for Linux, macOS, Windows and browsers (through WebAssembly)\n* **Vector support** support including exact search and vector manipulation\n* **Improved schema management** including extended `ALTER` support and faster schema changes.\n\nThe database has the following experimental features:\n\n* **Encryption at rest** for protecting the data locally.\n* **Incremental computation** using DBSP for incremental view maintenance and query subscriptions.\n* **Full-Text-Search** powered by the awesome [tantivy](https://github.com/quickwit-oss/tantivy) library\n* **Multi-process WAL coordination** via the `.tshm` sidecar for cross-process WAL readers and writers.\n\nThe following features are on our current roadmap:\n\n* **Vector indexing** for fast approximate vector search, similar to [libSQL vector search](https://turso.tech/vector).\n\n## Getting Started\n\nPlease see the [Turso Database Manual](docs/manual.md) for more information.\n\n\n💻 Command Line\n \nYou can install the latest `turso` release with:\n\n```shell\ncurl --proto '=https' --tlsv1.2 -LsSf \\\n https://github.com/tursodatabase/turso/releases/latest/download/turso_cli-installer.sh | sh\n```\n\nThen launch the interactive shell:\n\n```shell\n$ tursodb\n```\n\nThis will start the Turso interactive shell where you can execute SQL statements:\n\n```console\nTurso\nEnter \".help\" for usage hints.\nConnected to a transient in-memory database.\nUse \".open FILENAME\" to reopen on a persistent database\nturso> CREATE TABLE users (id INT, username TEXT);\nturso> INSERT INTO users VALUES (1, 'alice');\nturso> INSERT INTO users VALUES (2, 'bob');\nturso> SELECT * FROM users;\n1|alice\n2|bob\n```\n\nYou can also build and run the latest development version with:\n\n```shell\ncargo run\n```\n\nIf you like docker, we got you covered. Simply run this in the root folder:\n\n```bash\nmake docker-cli-build && \\\nmake docker-cli-run\n```\n\n\n\n\n🦀 Rust\n \n\n```console\ncargo add turso\n```\n\nExample usage:\n\n```rust\nlet db = Builder::new_local(\"sqlite.db\").build().await?;\nlet conn = db.connect()?;\n\nlet res = conn.query(\"SELECT * FROM users\", ()).await?;\n```\n\n\n\n✨ JavaScript\n \n\n```console\nnpm i @tursodatabase/database\n```\n\nExample usage:\n\n```js\nimport { connect } from '@tursodatabase/database';\n\nconst db = await connect('sqlite.db');\nconst stmt = db.prepare('SELECT * FROM users');\nconst users = stmt.all();\nconsole.log(users);\n```\n\n\n\n🐍 Python\n \n\n```console\nuv pip install pyturso\n```\n\nExample usage:\n\n```python\nimport turso\n\ncon = turso.connect(\"sqlite.db\")\ncur = con.cursor()\nres = cur.execute(\"SELECT * FROM users\")\nprint(res.fetchone())\n```\n\n\n\n🦫 Go\n \n\n```console\ngo get turso.tech/database/tursogo\ngo install turso.tech/database/tursogo\n```\n\nExample usage:\n```go\nimport (\n \"database/sql\"\n _ \"turso.tech/database/tursogo\"\n)\n\nconn, _ = sql.Open(\"turso\", \"sqlite.db\")\ndefer conn.Close()\n\nstmt, _ := conn.Prepare(\"select * from users\")\ndefer stmt.Close()\n\nrows, _ = stmt.Query()\nfor rows.Next() {\n var id int\n var username string\n rows.Scan(&id, &username)\n fmt.Printf(\"User: ID: %d, Username: %s\\n\", id, username)\n}\n```\n\n\n\n\n\n️#️⃣ .NET\n \n\nExample usage:\n```cs\nusing Turso;\n\nusing var connection = new TursoConnection(\"Data Source=:memory:\");\nconnection.Open();\n\nconnection.ExecuteNonQuery(\"CREATE TABLE t(a, b)\");\nvar rowsAffected = connection.ExecuteNonQuery(\"INSERT INTO t(a, b) VALUES (1, 2), (3, 4)\");\nConsole.WriteLine($\"RowsAffected: {rowsAffected}\");\n\nusing var command = connection.CreateCommand();\ncommand.CommandText = \"SELECT * FROM t\";\nusing var reader = command.ExecuteReader();\nwhile (reader.Read())\n{\n var a = reader.GetInt32(0);\n var b = reader.GetInt32(1);\n Console.WriteLine($\"Value1: {a}, Value2: {b}\");\n}\n```\n\n\n\n\n\n☕️ Java\n \n\nWe integrated Turso Database into JDBC. For detailed instructions on how to use Turso Database with java, please refer to\nthe [README.md under bindings/java](bindings/java/README.md).\n\n\n\n🤖 MCP Server Mode\n \n\n\nThe Turso CLI includes a built-in [Model Context Protocol (MCP)](https://modelcontextprotocol.io/) server that allows AI assistants to interact with your databases.\n\nStart the MCP server with:\n\n```shell\ntursodb your_database.db --mcp\n```\n\n### Configuration\n\nAdd Turso to your MCP client configuration:\n\n```json\n{\n \"mcpServers\": {\n \"turso\": {\n \"command\": \"/path/to/.turso/tursodb\",\n \"args\": [\"/path/to/your/database.db\", \"--mcp\"]\n }\n }\n}\n```\n\n### Available Tools\n\nThe MCP server provides nine tools for database interaction:\n\n1. **`open_database`** - Open a new database\n2. **`current_database`** - Describe the current database\n3. **`list_tables`** - List all tables in the database\n4. **`describe_table`** - Describe the structure of a specific table\n5. **`execute_query`** - Execute read-only SELECT queries\n6. **`insert_data`** - Insert new data into tables\n7. **`update_data`** - Update existing data in tables\n8. **`delete_data`** - Delete data from tables\n9. **`schema_change`** - Execute schema modification statements (CREATE TABLE, ALTER TABLE, DROP TABLE)\n\nOnce connected, you can ask your AI assistant:\n\n- \"Show me all tables in the database\"\n- \"What's the schema for the users table?\"\n- \"Find all posts with more than 100 upvotes\"\n- \"Insert a new user with name 'Alice' and email 'alice@example.com'\"\n\n### MCP Clients\n\n\nClaude Code\n\nIf you're using [Claude Code](https://claude.ai/code), you can easily connect to your Turso MCP server using the built-in MCP management commands:\n\n#### Quick Setup\n\n1. **Add the MCP server** to Claude Code:\n\n ```bash\n claude mcp add my-database -- tursodb ./path/to/your/database.db --mcp\n ```\n\n2. **Restart Claude Code** to activate the connection\n\n3. **Start querying** your database through natural language!\n\n#### Command Breakdown\n\n```bash\nclaude mcp add my-database -- tursodb ./path/to/your/database.db --mcp\n# ↑ ↑ ↑ ↑\n# | | | |\n# Name | Database path MCP flag\n# Separator\n```\n\n- **`my-database`** - Choose any name for your MCP server\n- **`--`** - Required separator between Claude options and your command\n- **`tursodb`** - The Turso database CLI\n- **`./path/to/your/database.db`** - Path to your SQLite database file\n- **`--mcp`** - Enables MCP server mode\n\n#### Example Usage\n\n```bash\n# For a local project database\ncd /your/project\nclaude mcp add my-project-db -- tursodb ./data/app.db --mcp\n\n# For an absolute path\nclaude mcp add analytics-db -- tursodb /Users/you/databases/analytics.db --mcp\n\n# For a specific project (local scope)\nclaude mcp add project-db --local -- tursodb ./database.db --mcp\n```\n\n#### Managing MCP Servers\n\n```bash\n# List all configured MCP servers\nclaude mcp list\n\n# Get details about a specific server\nclaude mcp get my-database\n\n# Remove an MCP server\nclaude mcp remove my-database\n```\n\n\n\n\nClaude Desktop\n\nFor Claude Desktop, add the configuration to your `claude_desktop_config.json` file:\n\n```json\n{\n \"mcpServers\": {\n \"turso\": {\n \"command\": \"/path/to/.turso/tursodb\",\n \"args\": [\"./path/to/your/database.db\", \"--mcp\"]\n }\n }\n}\n```\n\n\n\n\nCursor\n\nFor Cursor, configure MCP in your settings:\n\n1. Open Cursor settings\n2. Navigate to Extensions → MCP\n3. Add a new server with:\n - **Name**: `turso`\n - **Command**: `/path/to/.turso/tursodb`\n - **Args**: `[\"./path/to/your/database.db\", \"--mcp\"]`\n\nAlternatively, you can add it to your Cursor configuration file directly.\n\n\n\n### Direct JSON-RPC Usage\n\nThe MCP server runs as a single process that handles multiple JSON-RPC requests over stdin/stdout. Here's how to interact with it directly:\n\n#### Example with In-Memory Database\n\n```bash\ncat << 'EOF' | tursodb --mcp\n{\"jsonrpc\": \"2.0\", \"id\": 1, \"method\": \"initialize\", \"params\": {\"protocolVersion\": \"2024-11-05\", \"capabilities\": {}, \"clientInfo\": {\"name\": \"client\", \"version\": \"1.0\"}}}\n{\"jsonrpc\": \"2.0\", \"id\": 2, \"method\": \"tools/call\", \"params\": {\"name\": \"sc",
"manifest_file": "Cargo.toml",
"manifest_content": "# Copyright 2023-2026 the Turso authors. All rights reserved. MIT license.\n\n[workspace]\nresolver = \"2\"\nmembers = [\n \"bindings/java\",\n \"bindings/javascript\",\n \"bindings/javascript/sync\",\n \"bindings/python\",\n \"bindings/rust\",\n \"cli\",\n \"core\",\n \"extensions/completion\",\n \"extensions/core\",\n \"extensions/crypto\",\n \"extensions/csv\",\n \"extensions/ipaddr\",\n \"extensions/regexp\",\n \"extensions/tests\",\n \"extensions/fuzzy\",\n \"macros\",\n \"testing/simulator\",\n \"bindings/c\",\n \"testing/stress\",\n \"testing/sqlite_test_ext\",\n \"tests\",\n \"sqlite/parser\",\n \"sync/engine\",\n \"sync/sdk-kit\",\n \"sql_generation\",\n \"testing/concurrent-simulator\",\n \"perf/throughput/turso\",\n \"perf/throughput/rusqlite\",\n \"perf/encryption\",\n \"perf/memory\",\n \"perf/memory/codspeed\",\n \"perf/query-batch\",\n \"tools/dbhash\",\n \"sdk-kit\",\n \"sdk-kit-macros\",\n \"testing/differential-oracle/sql_gen_prop\",\n \"testing/differential-oracle/sql_gen\",\n \"testing/differential-oracle/fuzzer\",\n \"testing/sqltests\"\n]\nexclude = [\"perf/latency/limbo\"]\n\ndefault-members = [\n \"bindings/java\",\n \"bindings/javascript\",\n \"bindings/javascript/sync\",\n \"bindings/python\",\n \"bindings/rust\",\n \"cli\",\n \"core\",\n \"extensions/completion\",\n \"extensions/core\",\n \"extensions/crypto\",\n \"extensions/csv\",\n \"extensions/ipaddr\",\n \"extensions/regexp\",\n \"extensions/tests\",\n \"extensions/fuzzy\",\n \"macros\",\n \"testing/simulator\",\n \"bindings/c\",\n \"testing/stress\",\n \"testing/sqlite_test_ext\",\n \"tests\",\n \"sqlite/parser\",\n \"sync/engine\",\n \"sync/sdk-kit\",\n \"sql_generation\",\n \"testing/concurrent-simulator\",\n \"perf/throughput/turso\",\n \"perf/throughput/rusqlite\",\n \"perf/encryption\",\n \"tools/dbhash\",\n \"sdk-kit\",\n \"sdk-kit-macros\",\n \"testing/differential-oracle/sql_gen_prop\",\n \"testing/differential-oracle/sql_gen\",\n \"testing/differential-oracle/fuzzer\",\n \"testing/sqltests\"\n]\n\n[workspace.package]\nversion = \"0.7.0-pre.13\"\nauthors = [\"the Turso authors\"]\nedition = \"2021\"\nlicense = \"MIT\"\nrepository = \"https://github.com/tursodatabase/turso\"\n\n[workspace.dependencies]\nturso = { path = \"bindings/rust\", version = \"0.7.0-pre.13\" }\nturso_node = { path = \"bindings/javascript\", version = \"0.7.0-pre.13\" }\nturso_sdk_kit = { path = \"sdk-kit\", version = \"0.7.0-pre.13\" }\nturso_sdk_kit_macros = { path = \"sdk-kit-macros\", version = \"0.7.0-pre.13\" }\nturso_sync_sdk_kit = { path = \"sync/sdk-kit\", version = \"0.7.0-pre.13\" }\nlimbo_completion = { path = \"extensions/completion\", version = \"0.7.0-pre.13\" }\nturso_core = { path = \"core\", version = \"0.7.0-pre.13\" }\nturso_sync_engine = { path = \"sync/engine\", version = \"0.7.0-pre.13\" }\nturso_ext = { path = \"extensions/core\", version = \"0.7.0-pre.13\" }\nturso_macros = { path = \"macros\", version = \"0.7.0-pre.13\" }\nturso_parser = { path = \"sqlite/parser\", version = \"0.7.0-pre.13\" }\nsql_generation = { path = \"sql_generation\" }\nturso-dbhash = { path = \"tools/dbhash\" }\nstrum = { version = \"0.26\", features = [\"derive\"] }\nstrum_macros = \"0.26\"\nserde = \"1.0\"\nserde_json = \"1.0\"\nanyhow = \"1.0.98\"\nmimalloc = { version = \"0.1.47\", default-features = false }\nrusqlite = { version = \"0.37.0\", features = [\"bundled\"] }\nitertools = \"0.14.0\"\nrand = \"0.9.2\"\nrand_chacha = \"0.9.0\"\ntracing = \"0.1.41\"\nschemars = \"1.0.4\"\ngarde = \"0.22\"\nparking_lot = \"0.12.4\"\ntokio = { version = \"1.0\", default-features = false }\ntracing-subscriber = \"0.3.20\"\nfutures = \"0.3\"\nclap = \"4.5.47\"\nthiserror = \"2.0.16\"\ntempfile = \"3.20.0\"\nindexmap = \"2.11.1\"\nindicatif = \"0.17\"\nmiette = \"7.6.0\"\nbitflags = \"2.9.4\"\nfallible-iterator = \"0.3.0\"\nallocator-api2 = \"0.4\"\n\ncriterion = \"0.5.0\"\ncodspeed-criterion-compat = \"4.2.1\"\ndivan = { package = \"codspeed-divan-compat\", version = \"4.2.1\" }\n\nchrono = { version = \"0.4.42\", default-features = false }\nhex = \"0.4\"\nantithesis_sdk = { version = \"0.2\", default-features = false }\ncfg-if = \"1.0.0\"\ntracing-appender = \"0.2.3\"\nenv_logger = { version = \"0.11.6\", default-features = false }\nregex = \"1.11.1\"\nregex-syntax = { version = \"0.8.5\", default-features = false }\nsimilar = { version = \"2.7.0\" }\nsimilar-asserts = { version = \"1.7.0\" }\nbitmaps = { version = \"3.2.1\", default-features = false }\nconsole-subscriber = { version = \"0.4.1\" }\neither = { version = \"1.15\" }\n\n# Multi threading testing\nloom = { version = \"0.7\" }\nshuttle = { version = \"0.8.1\" }\n\n[profile.dev.package.similar]\nopt-level = 3\n\n[profile.release]\ndebug = \"line-tables-only\"\ncodegen-units = 4\npanic = \"abort\"\nlto = \"thin\"\n\n# Official release profile - maximum optimization for published binaries\n# Use for CLI releases, PyPI, npm, Maven, NuGet, etc.\n[profile.release-official]\ninherits = \"release\"\ncodegen-units = 1\nlto = true\n\n# override settings for sdk-kit release profiles in order to reduce size of produced binaries\n# otherwise, some platforms will have enormous libs (150MB+)\n[profile.lib-release]\ninherits = \"release\"\ndebug = false\ncodegen-units = 16",
"strategic_keywords": [
"memory",
"workspace",
"workflow",
"vector"
],
"relationship_label": "Memory 组件",
"data_confidence": "high",
"evidence_sources": [
"github_trending",
"github_repo_api",
"readme",
"Cargo.toml"
],
"score_breakdown": {
"heat": 20,
"relevance": 20,
"novelty": 11,
"productize": 11,
"adoption": 10,
"relation": 10,
"risk_signal": 8,
"total": 90
},
"strategic_score": 90
},
{
"owner": "Stirling-Tools",
"name": "Stirling-PDF",
"full_name": "Stirling-Tools/Stirling-PDF",
"url": "https://github.com/Stirling-Tools/Stirling-PDF",
"description": "#1 PDF Application on GitHub that lets you edit PDFs on any device anywhere",
"language": "Java",
"total_stars": 84282,
"forks": 7342,
"stars_this_period": 2793,
"source_slice": "all",
"source_slices": [
"all"
],
"metadata": {
"topics": [
"docker",
"hacktoberfest",
"java",
"pdf",
"pdf-converter",
"pdf-editor",
"pdf-manipulation",
"pdf-merger",
"pdf-ocr",
"pdf-tools",
"pdf-web-apps",
"pdfmerger",
"self-hosted"
],
"license": "NOASSERTION",
"open_issues": 449,
"created_at": "2023-01-27T18:22:42Z",
"pushed_at": "2026-06-25T15:41:03Z",
"homepage": "https://stirling.com",
"default_branch": "main",
"forks": 7342,
"watchers": 241,
"archived": false,
"size_kb": 315053
},
"readme_content": "
\n \n
\n\n
Stirling PDF - The Open-Source PDF Platform
\n\nStirling PDF is a powerful, open-source PDF editing platform. Run it as a personal desktop app, in the browser, or deploy it on your own servers with a private API. Edit, sign, redact, convert, and automate PDFs without sending documents to external services.\n\n
\n\n\n\n## Key Capabilities\n\n- **Everywhere you work** - Desktop client, browser UI, and self-hosted server with a private API.\n- **50+ PDF tools** - Edit, merge, split, sign, redact, convert, OCR, compress, and more.\n- **Automation & workflows** - No-code pipelines direct in UI with APIs to process millions of PDFs.\n- **Enterprise‑grade** - SSO, auditing, and flexible on‑prem deployments.\n- **Developer platform** - REST APIs available for nearly all tools to integrate into your existing systems.\n- **Global UI** - Interface available in 40+ languages.\n\nFor a full feature list, see the docs: **https://docs.stirlingpdf.com**\n\n## Quick Start\n\n```bash\ndocker run -p 8080:8080 docker.stirlingpdf.com/stirlingtools/stirling-pdf\n```\n\nThen open: http://localhost:8080\n\nFor full installation options (including desktop and Kubernetes), see our [Documentation Guide](https://docs.stirlingpdf.com/#documentation-guide).\n\n## Resources\n\n- [**Documentation**](https://docs.stirlingpdf.com)\n- [**Homepage**](https://stirling.com)\n- [**API Docs**](https://registry.scalar.com/@stirlingpdf/apis/stirling-pdf-processing-api/)\n- [**Server Plan & Enterprise**](https://docs.stirlingpdf.com/Paid-Offerings)\n\n## Support\n\n- **Community** [Discord](https://discord.gg/HYmhKj45pU)\n- **Bug Reports**: [Github issues](https://github.com/Stirling-Tools/Stirling-PDF/issues)\n\n## Contributing\n\nWe welcome contributions! Please see [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines.\n\nThis project uses [Task](https://taskfile.dev/) as a unified command runner for all build, dev, and test commands. Run `task dev` to get started running the editor, run `task` to see the most common commands, or see the [Developer Guide](DeveloperGuide.md) for full details.\n\nFor adding translations, see the [Translation Guide](devGuide/HowToAddNewLanguage.md).\n\n## License\n\nStirling PDF is open-core. See [LICENSE](LICENSE) for details.\n",
"strategic_keywords": [
"workflow",
"automation"
],
"relationship_label": "Workspace 组件",
"data_confidence": "high",
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"github_trending",
"github_repo_api",
"readme"
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"score_breakdown": {
"heat": 20,
"relevance": 16,
"novelty": 8,
"productize": 14,
"adoption": 8,
"relation": 8,
"risk_signal": 8,
"total": 82
},
"strategic_score": 82
},
{
"owner": "asgeirtj",
"name": "system_prompts_leaks",
"full_name": "asgeirtj/system_prompts_leaks",
"url": "https://github.com/asgeirtj/system_prompts_leaks",
"description": "Extracted system prompts from Anthropic - Claude Fable 5, Opus 4.8, Claude Code, Claude Design. OpenAI - ChatGPT 5.5 Thinking, GPT 5.5 Instant, Codex. Google - Gemini 3.5 Flash, 3.1 Pro, Antigravity. xAI - Grok, Cursor, Copilot, VS Code, Perplexity, and more. Updated regularly.",
"language": "JavaScript",
"total_stars": 45980,
"forks": 7540,
"stars_this_period": 2662,
"source_slice": "all",
"source_slices": [
"all",
"javascript"
],
"metadata": {
"topics": [
"ai",
"ai-agents",
"anthropic",
"awesome",
"chatbot",
"chatgpt",
"claude",
"claude-code",
"codex",
"deep-learning",
"education",
"gemini",
"generative-ai",
"google",
"llm",
"machine-learning",
"nlp",
"open-source",
"openai",
"prompt-engineering"
],
"license": "CC0-1.0",
"open_issues": 22,
"created_at": "2025-05-03T02:43:56Z",
"pushed_at": "2026-06-25T00:27:10Z",
"homepage": "https://asgeirtj.github.io/system_prompts_leaks/",
"default_branch": "main",
"forks": 7540,
"watchers": 547,
"archived": false,
"size_kb": 7288
},
"readme_content": "> **As seen in The Washington Post:** [See the hidden rules behind AI. Then use them to rewrite this article.](https://wapo.st/49t4gSb) (May 11, 2026)\n# System Prompts Leaks\nThe purpose of this repo is to document the System Prompt instructions for all the AI chatbots out there - Claude, ChatGPT, Gemini etc.\n\n\n\n[](https://github.com/asgeirtj/system_prompts_leaks)\n\n[](http://makeapullrequest.com)\n\n> 🆕 **[Diff: Claude Opus 4.8 → Claude Fable 5](https://www.diffchecker.com/QJn9jFNk/)** — see exactly what changed in the claude.ai system prompt for Anthropic's newest model\n\n\n\n\n\n## Recently Updated\n\n| What | Date | Link |\n|------|------|------|\n| **Claude Design (Opus 4.8 — full prompt + 50 tools + 16 skills + 8 starter sources)** | June 23, 2026 | [System prompt](Anthropic/claude-design.md) |\n| **GitHub Copilot for macOS (app)** | June 18, 2026 | [System prompt](Microsoft/copilot-macos-app.md) |\n| **GPT-5.5 Codex (full prompt)** | June 18, 2026 | [System prompt](OpenAI/Codex/gpt-5.5.md) |\n| **Claude Fable 5** | June 9, 2026 | [System prompt](Anthropic/claude-fable-5.md) · [Diff vs Opus 4.8](https://www.diffchecker.com/QJn9jFNk/) |\n| **Claude Opus 4.8** | June 9, 2026 | [System prompt](Anthropic/claude-opus-4.8.md) · [Official](Anthropic/Official/2026-05-28-claude-opus-4.8.md) |\n| **Claude Code Glob & Grep tools** | June 9, 2026 | [Glob](Anthropic/Claude%20Code/glob-tool.md) · [Grep](Anthropic/Claude%20Code/grep-tool.md) |\n| **Claude Code (Opus 4.8)** | May 28, 2026 | [System prompt](Anthropic/Claude%20Code/claude-code-opus-4.8.md) |\n| **Claude Code & Cowork** | May 28, 2026 | [Claude Code](Anthropic/Claude%20Code/claude-code-opus-4.6.md) · [Cowork](Anthropic/claude-cowork.md) · [Cowork Dispatch](Anthropic/claude-cowork-dispatch.md) |\n| **GPT-5.5** | May 24, 2026 | [Thinking](OpenAI/gpt-5.5-thinking.md) · [Instant](OpenAI/gpt-5.5-instant.md) · [API](OpenAI/gpt-5.5-api.md) · [Pro API](OpenAI/gpt-5.5-pro-api.md) |\n| **Perplexity Computer** | May 21, 2026 | [System prompt](Perplexity/perplexity-computer.md) |\n| **VS Code Copilot Agent** | May 21, 2026 | [System prompt](Microsoft/vscode-copilot-agent.md) |\n| **Docker Gordon AI** | May 21, 2026 | [System prompt](Misc/docker-gordon-ai.md) |\n| **Gemini 3.5 Flash** | May 20, 2026 | [System prompt](Google/gemini-3.5-flash.md) · [AI Studio](Google/gemini-3.5-flash-ai-studio.md) · [Tools](Google/gemini-3.5-flash-tools.json) |\n| **Antigravity CLI** | May 20, 2026 | [System prompt](Google/antigravity-cli.md) |\n| **Zed AI** | May 16, 2026 | [System prompt](Misc/zed.md) |\n| **Grok Expert** | May 11, 2026 | [System prompt](xAI/grok-expert.md) |\n\n---\n\n\n## Anthropic — Claude\n\n| Model | Prompt |\n|-------|--------|\n| **Claude Fable 5** | [**System prompt**](Anthropic/claude-fable-5.md) |\n| **Claude Opus 4.8** | [**System prompt**](Anthropic/claude-opus-4.8.md) |\n| **Claude Code (Opus 4.8)** | [**System prompt**](Anthropic/Claude%20Code/claude-code-opus-4.8.md) |\n| **Claude Opus 4.7** | [**System prompt**](Anthropic/claude-opus-4.7.md) |\n| **Claude Code (Opus 4.6)** | [**System prompt**](Anthropic/Claude%20Code/claude-code-opus-4.6.md) |\n| **Claude Opus 4.6** | [**System prompt**](Anthropic/claude-opus-4.6.md) |\n| **Claude Sonnet 4.6** | [**System prompt**](Anthropic/claude-sonnet-4.6.md) |\n| Claude.ai | [Anthropic Reminders](Anthropic/anthropic_reminders.md) |\n\nIntegrations, official prompts & older versions\n\n| | |\n|--|--|\n| Integrations | [Cowork](Anthropic/claude-cowork.md) · [Cowork Dispatch](Anthropic/claude-cowork-dispatch.md) · [Desktop Code](Anthropic/claude-desktop-code.md) · [Design](Anthropic/claude-design.md) · [Mobile iOS](Anthropic/claude-mobile-ios.md) · [In Chrome](Anthropic/claude-in-chrome.md) · [For Excel](Anthropic/claude-for-excel.md) · [For Word](Anthropic/claude-for-word.md) · [In PowerPoint](Anthropic/claude-in-powerpoint.md) · [Default Styles](Anthropic/default-styles.md) |\n| Claude Code extras | [Glob tool](Anthropic/Claude%20Code/glob-tool.md) · [Grep tool](Anthropic/Claude%20Code/grep-tool.md) · [Deferred tools](Anthropic/Claude%20Code/deferred-tools.md) · [Docs assistant](Anthropic/Claude%20Code/claude-code-docs-assistant.md) · [Bundled skills](Anthropic/Claude%20Code/bundled-skills/) |\n| Published (`claude_behavior` at release date, not updated) | [Opus 4.8](Anthropic/Official/2026-05-28-claude-opus-4.8.md) · [Opus 4.7](Anthropic/Official/2026-04-16-claude-opus-4.7.md) · [Opus 4.6](Anthropic/Official/2026-02-05-claude-opus-4.6.md) · [Sonnet 4.6](Anthropic/Official/2026-02-17-claude-sonnet-4.6.md) · [All versions](Anthropic/Official/) |\n| Without tools | [Opus 4.6](Anthropic/claude-opus-4.6-no-tools.md) · [Sonnet 4.6](Anthropic/claude-sonnet-4.6-no-tools.md) |\n| Raw prompts | [Opus 4.6](Anthropic/raw/claude-opus-4.6-raw.md) · [Opus 4.6 (no tools)](Anthropic/raw/claude-opus-4.6-no-tools-raw.md) · [Sonnet 4.6](Anthropic/raw/claude-sonnet-4.6-raw.md) · [Sonnet 4.6 (no tools)](Anthropic/raw/claude-sonnet-4.6-no-tools-raw.md) |\n| Visualize | [Visualization](Anthropic/visualize.md) |\n| Opus 4.5 | [System prompt](Anthropic/old/claude-opus-4.5.md) |\n| Sonnet 4.5 | [System prompt](Anthropic/old/claude-4.5-sonnet.md) |\n| Sonnet 4 | [System prompt](Anthropic/old/claude-sonnet-4.md) |\n| Opus 4.1 Thinking | [System prompt](Anthropic/old/claude-4.1-opus-thinking.md) |\n| Sonnet 3.7 | [System prompt](Anthropic/old/claude-3.7-sonnet.md) · [With tools](Anthropic/old/claude-3.7-sonnet-w-tools.md) · [Full w/ tools](Anthropic/old/claude-3.7-full-system-message-with-all-tools.md) · [Human-readable](Anthropic/old/claude-3.7-sonnet-full-system-message-humanreadable.md) |\n\n\n\n\n\n## OpenAI — ChatGPT\n\n| Model | Prompt |\n|-------|--------|\n| **GPT-5.5** | [**Thinking**](OpenAI/gpt-5.5-thinking.md) · [**Instant**](OpenAI/gpt-5.5-instant.md) · [API](OpenAI/gpt-5.5-api.md) · [Pro API](OpenAI/gpt-5.5-pro-api.md) · [**Codex**](OpenAI/Codex/gpt-5.5.md) · [Friendly](OpenAI/Codex/personality_friendly_gpt-5.5.md) · [Pragmatic](OpenAI/Codex/personality_pragmatic_gpt-5.5.md) |\n| **GPT-5.4** | [**API**](OpenAI/gpt-5.4-api.md) · [**Thinking**](OpenAI/gpt-5.4-thinking.md) · [**Codex**](OpenAI/Codex/gpt-5.4.md) · [Codex Mini](OpenAI/Codex/gpt-5.4-mini.md) |\n| **GPT-5.3** | [**Codex**](OpenAI/Codex/gpt-5.3-codex.md) · [Spark](OpenAI/Codex/gpt-5.3-codex-spark.md) · [Codex API](OpenAI/gpt-5.3-codex-api.md) · [Chat API](OpenAI/gpt-5.3-chat-api.md) · [Instant](OpenAI/gpt-5.3-instant.md) |\n| **Codex CLI** | [Per-model prompts](OpenAI/Codex/) · [Spark](OpenAI/Codex/gpt-5.3-codex-spark.md) · [Plan mode](OpenAI/Codex/plan_mode.md) · [Personas](OpenAI/Codex/personality_friendly.md) · [Auto-review](OpenAI/Codex/codex-auto-review.md) |\n| **Tools** | [Web search](OpenAI/tool-web-search.md) · [Deep research](OpenAI/tool-deep-research.md) · [Python](OpenAI/tool-python.md) · [Python code](OpenAI/tool-python-code.md) · [Canvas](OpenAI/tool-canvas-canmore.md) · [Image gen](OpenAI/tool-create-image-image_gen.md) · [Memory](OpenAI/tool-memory-bio.md) · [Advanced memory](OpenAI/tool-advanced-memory.md) · [File search](OpenAI/tool-file_search.md) |\n| **Policies** | [Image safety](OpenAI/prompt-image-safety-policies.md) · [Automation context](OpenAI/prompt-automation-context.md) |\n\nOlder models & variants\n\n| | |\n|--|--|\n| GPT-5.2 | [Mini (free)](OpenAI/gpt-5.2-mini-free-account.md) · [Thinking](OpenAI/gpt-5.2-thinking.md) · [Codex](OpenAI/Codex/gpt-5.2-codex.md) |\n| o4-mini | [System prompt](OpenAI/o4-mini.md) · [High](OpenAI/o4-mini-high.md) |\n| o3 | [System prompt](OpenAI/o3.md) |\n| ChatGPT Atlas | [System prompt](OpenAI/chatgpt-atlas.md) |\n| GPT-5.1 personalities | [Default](OpenAI/gpt-5.1-default.md) · [Friendly](OpenAI/gpt-5.1-friendly.md) · [Professional](OpenAI/gpt-5.1-professional.md) · [Candid](OpenAI/gpt-5.1-candid.md) · [Cynical](OpenAI/gpt-5.1-cynical.md) · [Efficient](OpenAI/gpt-5.1-efficient.md) · [Nerdy](OpenAI/gpt-5.1-nerdy.md) · [Quirky](OpenAI/gpt-5.1-quirky.md) |\n| GPT-5 | [Agent mode](OpenAI/chatgpt-gpt-5-agent-mode.md) · [Thinking](OpenAI/gpt-5-thinking.md) · [Cynic](OpenAI/gpt-5-cynic-personality.md) · [Listener](OpenAI/gpt-5-listener-personality.md) · [Nerdy](OpenAI/gpt-5-nerdy-personality.md) · [Robot](OpenAI/gpt-5-robot-personality.md) · [Codex](OpenAI/Codex/gpt-5-codex.md) · [Codex Mini](OpenAI/Codex/gpt-5-codex-mini.md) |\n| GPT-4.5 | [System prompt](OpenAI/gpt-4.5.md) |\n| GPT-4.1 | [Full](OpenAI/gpt-4.1.md) · [Mini](OpenAI/gpt-4.1-mini.md) |\n| GPT-4o | [System prompt](OpenAI/gpt-4o.md) · [WhatsApp](OpenAI/gpt-4o-whatsapp.md) · [Advanced voice](OpenAI/gpt-4o-advanced-voice-mode.md) · [Legacy voice](OpenAI/gpt-4o-legacy-voice-mode.md) |\n| Monday GPT | [System prompt](OpenAI/monday-gpt.md) |\n| GPT-4o new personality | [System prompt](OpenAI/4o-2025-09-03-new-personality.md) |\n| Study and learn | [System prompt](OpenAI/study-and-learn.md) |\n| Image safety policies | [System prompt](OpenAI/image-safety-policies.md) |\n| API variants | [GPT-5 reasoning (high)](OpenAI/API/gpt-5-reasoning-effort-high-api.md) · [o3 high](OpenAI/API/o3-high-api.md) · [o3 med](OpenAI/API/o3-medium-api.md) · [o3 low](OpenAI/API/o3-low-api.md) · [o4-mini high](OpenAI/API/o4-mini-high.md) · [o4-mini med](OpenAI/API/o4-mini-medium-api.md) · [o4-mini low](OpenAI/API/o4-mini-low-api.md) |\n| Old o4-mini | [System prompt](OpenAI/Old/chatgpt.com-o4-mini.md) |\n| Codex (older) | [GPT-5](OpenAI/Codex/gpt-5.md) · [GPT-5.1](OpenAI/Codex/gpt-5.1.md) · [GPT-5.1 Codex](OpenAI/Codex/gpt-5.1-codex.md) · [GPT-5.1 Mini](OpenAI/Codex/gpt-5.1-codex-mini.md) · [GPT-5.1 Max](OpenAI/Codex/gpt-5.1-codex-max.md) · [GPT-5.2](OpenAI/Codex/gpt-5.2.md) · [5.2 Friendly](OpenAI/Codex/personality_friendly_gpt-5.2-codex.md) · [5.2 Pragmatic](OpenAI/Codex/personality_pragmatic_gpt-5.2-codex.md) |\n\n\n\n\n\n## Google — Gemini\n\n| Model | Prompt |\n|-------|--------|\n| **Gemini 3.5 Flash** | [**System prompt**](Google/gemini-3.5-flash.md) · [AI Studio](Google/gemini-3.5-flash-ai-studio.md) · [Tools](Google/gemini-3.5-flash-tools.json) |\n| **Gemini 3.1 Pro** | [**System prompt**](Google/gemini-3.1-pro.md) · [API](Google/gemini-3.1-pro-api.md) |\n| Gemini CLI | [System prompt](Google/gemini-cli.md) |\n| Antigravity CLI | [System prompt](Google/antigravity-cli.md) |\n| Jules | [System prompt](Google/jules.md) |\n\nOlder models & variants\n\n| | |\n|--|--|\n| Gemini 3 | [Flash](Google/gemini-3-flash.md) · [Pro](Google/gemini-3-pro.md) |\n| Gemini Diffusion | [System prompt](Google/gemini-diffusion.md) |\n| Google Search AI Mode | [System prompt](Google/google-search-ai-mode.md) |\n| Gemini YouTube | [System prompt](Google/gemini-youtube.md) |\n| Gemini in Chrome | [System prompt](Google/gemini-in-chrome.md) |\n| Gemini Workspace | [System prompt](Google/gemini-workspace.md) |\n| Gemini 2.5 Pro | [API](Google/gemini-2.5-pro-api.md) · [Webapp](Google/gemini-2.5-pro-webapp.md) · [Guided learning](Google/gemini-2.5-pro-guided-learning.md) |\n| Gemini 2.5 Flash | [Image preview](Google/gemini-2.5-flash-image-preview.md) |\n| Gemini 2.0 Flash | [Webapp](Google/gemini-2.0-flash-webapp.md) |\n| AI Studio Build | [System prompt](Goog",
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"readme_content": "# AI Website Cloner Template\n\n\n\nA reusable template for reverse-engineering any website into a clean, modern Next.js codebase using AI coding agents. \n\n**Recommended: [Claude Code](https://docs.anthropic.com/en/docs/claude-code) with Opus 4.7 for best results** — but works with a variety of AI coding agents.\n\nPoint it at a URL, run `/clone-website`, and your AI agent will inspect the site, extract design tokens and assets, write component specs, and dispatch parallel builders to reconstruct every section.\n\n## Demo\n\n[](https://youtu.be/O669pVZ_qr0)\n\n> Click the image above to watch the full demo on YouTube.\n\n## Quick Start\n\n> **Important:** Start by making your own copy with GitHub's **Use this template** button. Do not clone this template repository directly for your website project, and do not open pull requests here with your generated website.\n\n1. **Create your own repository from this template**\n\n On the GitHub page for this project, click **Use this template**, then click **Create a new repository**.\n\n Give your new repository a name, choose whether it should be public or private, then click **Create repository**. If GitHub shows an **Include all branches** option, you can leave it off.\n\n This gives you your own separate project to work in, so your website changes stay in your account instead of coming back to the main template.\n\n2. **Open your new repository on your computer**\n\n After GitHub creates your copy, open that new repository. Click **Code** and open or clone your new repository with your preferred coding tool.\n\n If you use the terminal, the command will look like this:\n\n ```bash\n git clone https://github.com/YOUR-USERNAME/YOUR-NEW-REPOSITORY.git\n cd YOUR-NEW-REPOSITORY\n ```\n\n3. **Install dependencies**\n ```bash\n npm install\n ```\n4. **Start your AI agent** — Claude Code recommended:\n ```bash\n claude --chrome\n ```\n5. **Run the skill**:\n ```\n /clone-website [ ...]\n ```\n6. **Customize** (optional) — after the base clone is built, modify as needed\n\n> Using a different agent? Open `AGENTS.md` for project instructions — most agents pick it up automatically.\n\n## Supported Platforms\n\n| Agent | Status |\n| ------------------------------------------------------------- | -------------------------- |\n| [Claude Code](https://docs.anthropic.com/en/docs/claude-code) | **Recommended** — Opus 4.7 |\n| [Codex CLI](https://github.com/openai/codex) | Supported |\n| [OpenCode](https://opencode.ai/) | Supported |\n| [GitHub Copilot](https://github.com/features/copilot) | Supported |\n| [Cursor](https://cursor.com/) | Supported |\n| [Windsurf](https://codeium.com/windsurf) | Supported |\n| [Gemini CLI](https://github.com/google-gemini/gemini-cli) | Supported |\n| [Cline](https://github.com/cline/cline) | Supported |\n| [Roo Code](https://github.com/RooCodeInc/Roo-Code) | Supported |\n| [Continue](https://continue.dev/) | Supported |\n| [Amazon Q](https://aws.amazon.com/q/developer/) | Supported |\n| [Augment Code](https://www.augmentcode.com/) | Supported |\n| [Aider](https://aider.chat/) | Supported |\n\n## Prerequisites\n\n- [Node.js](https://nodejs.org/) 24+\n- An AI coding agent (see [Supported Platforms](#supported-platforms))\n\n## Tech Stack\n\n- **Next.js 16** — App Router, React 19, TypeScript strict\n- **shadcn/ui** — Radix primitives + Tailwind CSS v4\n- **Tailwind CSS v4** — oklch design tokens\n- **Lucide React** — default icons (replaced by extracted SVGs during cloning)\n\n## How It Works\n\nThe `/clone-website` skill runs a multi-phase pipeline:\n\n1. **Reconnaissance** — screenshots, design token extraction, interaction sweep (scroll, click, hover, responsive)\n2. **Foundation** — updates fonts, colors, globals, downloads all assets\n3. **Component Specs** — writes detailed spec files (`docs/research/components/`) with exact computed CSS values, states, behaviors, and content\n4. **Parallel Build** — dispatches builder agents in git worktrees, one per section/component\n5. **Assembly & QA** — merges worktrees, wires up the page, runs visual diff against the original\n\nEach builder agent receives the full component specification inline — exact `getComputedStyle()` values, interaction models, multi-state content, responsive breakpoints, and asset paths. No guessing.\n\n## Use Cases\n\n- **Platform migration** — rebuild a site you own from WordPress/Webflow/Squarespace into a modern Next.js codebase\n- **Lost source code** — your site is live but the repo is gone, the developer left, or the stack is legacy. Get the code back in a modern format\n- **Learning** — deconstruct how production sites achieve specific layouts, animations, and responsive behavior by working with real code\n\n## Not Intended For\n\n- **Phishing or impersonation** — this project must not be used for deceptive purposes, impersonation, or any activity that breaks the law.\n- **Passing off someone's design as your own** — logos, brand assets, and original copy belong to their owners.\n- **Violating terms of service** — some sites explicitly prohibit scraping or reproduction. Check first.\n\n## Project Structure\n\n```\nsrc/\n app/ # Next.js routes\n components/ # React components\n ui/ # shadcn/ui primitives\n icons.tsx # Extracted SVG icons\n lib/utils.ts # cn() utility\n types/ # TypeScript interfaces\n hooks/ # Custom React hooks\npublic/\n images/ # Downloaded images from target\n videos/ # Downloaded videos from target\n seo/ # Favicons, OG images\ndocs/\n research/ # Extraction output & component specs\n design-references/ # Screenshots\nscripts/\n sync-agent-rules.sh # Regenerate agent instruction files\n sync-skills.mjs # Regenerate /clone-website for all platforms\nAGENTS.md # Agent instructions (single source of truth)\nCLAUDE.md # Claude Code config (imports AGENTS.md)\nGEMINI.md # Gemini CLI config (imports AGENTS.md)\n```\n\n## Commands\n\n```bash\nnpm run dev # Start dev server\nnpm run build # Production build\nnpm run lint # ESLint check\nnpm run typecheck # TypeScript check\nnpm run check # Run lint + typecheck + build\n```\n\n### If using docker\n\n```bash\ndocker compose up app --build # build and run the app\ndocker compose up dev --build # run the app in dev mode on port 3001\n```\n\n## Updating for Other Platforms\n\nTwo source-of-truth files power all platform support. Edit the source, then run the sync script:\n\n| What | Source of truth | Sync command |\n| ---------------------- | --------------------------------------- | ---------------------------------- |\n| Project instructions | `AGENTS.md` | `bash scripts/sync-agent-rules.sh` |\n| `/clone-website` skill | `.claude/skills/clone-website/SKILL.md` | `node scripts/sync-skills.mjs` |\n\nEach script regenerates the platform-specific copies automatically. Agents that read the source files natively need no regeneration.\n\n\n## Star History\n\n[](https://star-history.com/#JCodesMore/ai-website-cloner-template&Date)\n\n## License\n\nMIT\n",
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"readme_content": "# DESIGN.md\n\nA format specification for describing a visual identity to coding agents. DESIGN.md gives agents a persistent, structured understanding of a design system.\n\n## The Format\n\nA DESIGN.md file combines machine-readable design tokens (YAML front matter) with human-readable design rationale (markdown prose). Tokens give agents exact values. Prose tells them *why* those values exist and how to apply them.\n\n```md\n---\nname: Heritage\ncolors:\n primary: \"#1A1C1E\"\n secondary: \"#6C7278\"\n tertiary: \"#B8422E\"\n neutral: \"#F7F5F2\"\ntypography:\n h1:\n fontFamily: Public Sans\n fontSize: 3rem\n body-md:\n fontFamily: Public Sans\n fontSize: 1rem\n label-caps:\n fontFamily: Space Grotesk\n fontSize: 0.75rem\nrounded:\n sm: 4px\n md: 8px\nspacing:\n sm: 8px\n md: 16px\n---\n\n## Overview\n\nArchitectural Minimalism meets Journalistic Gravitas. The UI evokes a\npremium matte finish — a high-end broadsheet or contemporary gallery.\n\n## Colors\n\nThe palette is rooted in high-contrast neutrals and a single accent color.\n\n- **Primary (#1A1C1E):** Deep ink for headlines and core text.\n- **Secondary (#6C7278):** Sophisticated slate for borders, captions, metadata.\n- **Tertiary (#B8422E):** \"Boston Clay\" — the sole driver for interaction.\n- **Neutral (#F7F5F2):** Warm limestone foundation, softer than pure white.\n```\n\nAn agent that reads this file will produce a UI with deep ink headlines in Public Sans, a warm limestone background, and Boston Clay call-to-action buttons.\n\n## Getting Started\n\nValidate a DESIGN.md against the spec, catch broken token references, check WCAG contrast ratios, and surface structural findings — all as structured JSON that agents can act on.\n\n```bash\nnpx @google/design.md lint DESIGN.md\n```\n\n```json\n{\n \"findings\": [\n {\n \"severity\": \"warning\",\n \"path\": \"components.button-primary\",\n \"message\": \"textColor (#ffffff) on backgroundColor (#1A1C1E) has contrast ratio 15.42:1 — passes WCAG AA.\"\n }\n ],\n \"summary\": { \"errors\": 0, \"warnings\": 1, \"info\": 1 }\n}\n```\n\nCompare two versions of a design system to detect token-level and prose regressions:\n\n```bash\nnpx @google/design.md diff DESIGN.md DESIGN-v2.md\n```\n\n```json\n{\n \"tokens\": {\n \"colors\": { \"added\": [\"accent\"], \"removed\": [], \"modified\": [\"tertiary\"] },\n \"typography\": { \"added\": [], \"removed\": [], \"modified\": [] }\n },\n \"regression\": false\n}\n```\n\n## The Specification\n\nThe full DESIGN.md spec lives at [`docs/spec.md`](docs/spec.md). What follows is a condensed reference.\n\n### File Structure\n\nA DESIGN.md file has two layers:\n\n1. **YAML front matter** — Machine-readable design tokens, delimited by `---` fences at the top of the file.\n2. **Markdown body** — Human-readable design rationale organized into `##` sections.\n\nThe tokens are the normative values. The prose provides context for how to apply them.\n\n### Token Schema\n\n```yaml\nversion: # optional, current: \"alpha\"\nname: \ndescription: # optional\ncolors:\n : \ntypography:\n : \nrounded:\n : \nspacing:\n : \ncomponents:\n :\n : \n```\n\n### Token Types\n\n| Type | Format | Example |\n|:-----|:-------|:--------|\n| Color | Any CSS color (hex, `rgb()`, `oklch()`, named, etc.) | `\"#1A1C1E\"`, `\"oklch(62% 0.18 250)\"` |\n| Dimension | number + unit (`px`, `em`, `rem`) | `48px`, `-0.02em` |\n| Token Reference | `{path.to.token}` | `{colors.primary}` |\n| Typography | object with `fontFamily`, `fontSize`, `fontWeight`, `lineHeight`, `letterSpacing`, `fontFeature`, `fontVariation` | See example above |\n\n### Section Order\n\nSections use `##` headings. They can be omitted, but those present must appear in this order:\n\n| # | Section | Aliases |\n|:--|:--------|:--------|\n| 1 | Overview | Brand & Style |\n| 2 | Colors | |\n| 3 | Typography | |\n| 4 | Layout | Layout & Spacing |\n| 5 | Elevation & Depth | Elevation |\n| 6 | Shapes | |\n| 7 | Components | |\n| 8 | Do's and Don'ts | |\n\n### Component Tokens\n\nComponents map a name to a group of sub-token properties:\n\n```yaml\ncomponents:\n button-primary:\n backgroundColor: \"{colors.tertiary}\"\n textColor: \"{colors.on-tertiary}\"\n rounded: \"{rounded.sm}\"\n padding: 12px\n button-primary-hover:\n backgroundColor: \"{colors.tertiary-container}\"\n```\n\nValid component properties: `backgroundColor`, `textColor`, `typography`, `rounded`, `padding`, `size`, `height`, `width`.\n\nVariants (hover, active, pressed) are expressed as separate component entries with a related key name.\n\n### Consumer Behavior for Unknown Content\n\n| Scenario | Behavior |\n|:---------|:---------|\n| Unknown section heading | Preserve; do not error |\n| Unknown color token name | Accept if value is valid |\n| Unknown typography token name | Accept as valid typography |\n| Unknown component property | Accept with warning |\n| Duplicate section heading | Error; reject the file |\n\n## CLI Reference\n\n### Installation\n\n```bash\nnpm install @google/design.md\n```\n\nOn **Windows**, quote the package name if your shell treats `@` specially (PowerShell, some terminals):\n\n```bash\nnpm install \"@google/design.md\"\n```\n\nOr run directly (always resolves from the public npm registry):\n\n```bash\nnpx @google/design.md lint DESIGN.md\n```\n\nOn **Windows/PowerShell**, this direct form can produce no output (or open\n`DESIGN.md` in your Markdown editor) because the `.md` suffix in the `design.md`\nbin name collides with the Windows Markdown file association during command\nresolution. Run the dot-free `designmd` alias instead — point `npx` at the\npackage with `-p`, then invoke `designmd`:\n\n```bash\nnpx -p @google/design.md designmd lint DESIGN.md\n```\n\nThe `designmd` shim resolves to the same entrypoint and works identically across\nall platforms.\n\n#### `npm error ENOVERSIONS` (“No versions available for @google/design.md”)\n\nThe CLI is published as [`@google/design.md` on npm](https://www.npmjs.com/package/@google/design.md). `ENOVERSIONS` almost always means npm is not querying the public registry (custom `registry=` in `.npmrc`, a corporate mirror that has not synced this package, or a misconfigured `@google:registry` for the `@google` scope).\n\nCheck your effective registry:\n\n```bash\nnpm config get registry\n```\n\nFor a normal install from the internet it should be `https://registry.npmjs.org/`. After fixing config, retry with `npm cache clean --force` if a stale 404 was cached.\n\nAll commands accept a file path or `-` for stdin. Output defaults to JSON.\n\n> **Windows tip**: when invoking the CLI directly from a `package.json` script\n> (rather than through `npx`), use the `designmd` alias instead of `design.md`.\n> The `.md` suffix in the original bin name confuses Windows command resolution\n> with the file association for Markdown files. The `designmd` shim resolves to\n> the same entrypoint and works identically across all platforms.\n>\n> ```jsonc\n> // package.json\n> {\n> \"scripts\": {\n> \"design:lint\": \"designmd lint DESIGN.md\"\n> }\n> }\n> ```\n\n### `lint`\n\nValidate a DESIGN.md file for structural correctness.\n\n```bash\nnpx @google/design.md lint DESIGN.md\nnpx @google/design.md lint --format json DESIGN.md\ncat DESIGN.md | npx @google/design.md lint -\n```\n\n| Option | Type | Default | Description |\n|:-------|:-----|:--------|:------------|\n| `file` | positional | required | Path to DESIGN.md (or `-` for stdin) |\n| `--format` | `json` | `json` | Output format |\n\nExit code `1` if errors are found, `0` otherwise.\n\n### `diff`\n\nCompare two DESIGN.md files and report token-level changes.\n\n```bash\nnpx @google/design.md diff DESIGN.md DESIGN-v2.md\n```\n\n| Option | Type | Default | Description |\n|:-------|:-----|:--------|:------------|\n| `before` | positional | required | Path to the \"before\" DESIGN.md |\n| `after` | positional | required | Path to the \"after\" DESIGN.md |\n| `--format` | `json` | `json` | Output format |\n\nExit code `1` if regressions are detected (more errors or warnings in the \"after\" file).\n\n### `export`\n\nExport DESIGN.md tokens to other formats.\n\n```bash\nnpx @google/design.md export --format json-tailwind DESIGN.md > tailwind.theme.json\nnpx @google/design.md export --format css-tailwind DESIGN.md > theme.css\nnpx @google/design.md export --format dtcg DESIGN.md > tokens.json\n```\n\n| Option | Type | Default | Description |\n|:-------|:-----|:--------|:------------|\n| `file` | positional | required | Path to DESIGN.md (or `-` for stdin) |\n| `--format` | `json-tailwind` \\| `css-tailwind` \\| `tailwind` \\| `dtcg` | required | Output format |\n\n| Format | Output | Description |\n|:-------|:-------|:------------|\n| `json-tailwind` | JSON | Tailwind v3 `theme.extend` config object |\n| `css-tailwind` | CSS | Tailwind v4 `@theme { ... }` block with CSS custom properties |\n| `tailwind` | JSON | Alias for `json-tailwind` |\n| `dtcg` | JSON | W3C Design Tokens Format Module |\n\n### `spec`\n\nOutput the DESIGN.md format specification (useful for injecting spec context into agent prompts).\n\n```bash\nnpx @google/design.md spec\nnpx @google/design.md spec --rules\nnpx @google/design.md spec --rules-only --format json\n```\n\n| Option | Type | Default | Description |\n|:-------|:-----|:--------|:------------|\n| `--rules` | boolean | `false` | Append the active linting rules table |\n| `--rules-only` | boolean | `false` | Output only the linting rules table |\n| `--format` | `markdown` \\| `json` | `markdown` | Output format |\n\n## Linting Rules\n\nThe linter runs nine rules against a parsed DESIGN.md. Each rule produces findings at a fixed severity level.\n\n| Rule | Severity | What it checks |\n|:-----|:---------|:---------------|\n| `broken-ref` | error | Token references (`{colors.primary}`) that don't resolve to any defined token |\n| `missing-primary` | warning | Colors are defined but no `primary` color exists — agents will auto-generate one |\n| `contrast-ratio` | warning | Component `backgroundColor`/`textColor` pairs below WCAG AA minimum (4.5:1) |\n| `orphaned-tokens` | warning | Color tokens defined but never referenced by any component |\n| `token-summary` | info | Summary of how many tokens are defined in each section |\n| `missing-sections` | info | Optional sections (spacing, rounded) absent when other tokens exist |\n| `missing-typography` | warning | Colors are defined but no typography tokens exist — agents will use default fonts |\n| `section-order` | warning | Sections appear out of the canonical order defined by the spec |\n| `unknown-key` | warning | A top-level YAML key looks like a typo of a known schema key (e.g. `colours:` → `colors:`); custom extension keys stay silent |\n\n### Programmatic API\n\nThe linter is also available as a library:\n\n```typescript\nimport { lint } from '@google/design.md/linter';\n\nconst report = lint(markdownString);\n\nconsole.log(report.findings); // Finding[]\nconsole.log(report.summary); // { errors, warnings, info }\nconsole.log(report.designSystem); // Parsed DesignSystemState\n```\n\n## Design Token Interoperability\n\nDESIGN.md tokens are inspired by the [W3C Design Token Format](https://www.designtokens.org/). The `export` command converts tokens to other formats:\n\n- **Tailwind v3 config (JSON)** — `npx @google/design.md export --format json-tailwind DESIGN.md` — emits a `theme.extend` JSON object for `tailwind.config.js`. `--format tailwind` is a backwards-compatible alias.\n- **Tailwind v4 theme (CSS)** — `npx @google/design.md export --format css-tailwind DESIGN.md` — emits a CSS `@theme { ... }` block using Tailwind v4's CSS-variable token namespaces (`--color-*`, `--font-*`, `--text-*`, `--leading-*`, `--tracking-*`, `--font-weight-*`, `--radius-*`, `--spacing-*`).\n- **DTCG tokens.json** ([W3C Design Tokens Format Module](https://tr.designtokens.org/format/)) — `npx @google/design.md export --format dtcg DESIGN.md`\n\n## Status\n\nThe DESIGN.md format is at version `alpha`. The spec, token schema, and CLI are under active development. Expect changes to the format as it matures.\n\n## D",
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{
"owner": "makeplane",
"name": "plane",
"full_name": "makeplane/plane",
"url": "https://github.com/makeplane/plane",
"description": "🔥🔥🔥 Open-source Jira, Linear, Monday, and ClickUp alternative. Plane is a modern project management platform to manage tasks, sprints, docs, and triage.",
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"license": "AGPL-3.0",
"open_issues": 945,
"created_at": "2022-11-19T12:55:01Z",
"pushed_at": "2026-06-25T10:19:26Z",
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\n\nMeet [Plane](https://plane.so/), an open-source project management tool to track issues, run ~sprints~ cycles, and manage product roadmaps without the chaos of managing the tool itself. 🧘♀️\n\n> Plane is evolving every day. Your suggestions, ideas, and reported bugs help us immensely. Do not hesitate to join in the conversation on [Forum](https://forum.plane.so) or raise a GitHub issue. We read everything and respond to most.\n\n## 🚀 Installation\n\nGetting started with Plane is simple. Choose the setup that works best for you:\n\n- **Plane Cloud**\n Sign up for a free account on [Plane Cloud](https://app.plane.so)—it's the fastest way to get up and running without worrying about infrastructure.\n\n- **Self-host Plane**\n Prefer full control over your data and infrastructure? Install and run Plane on your own servers. Follow our detailed [deployment guides](https://developers.plane.so/self-hosting/overview) to get started.\n\n| Installation methods | Docs link |\n| -------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |\n| Docker | [](https://developers.plane.so/self-hosting/methods/docker-compose) |\n| Kubernetes | [](https://developers.plane.so/self-hosting/methods/kubernetes) |\n\n`Instance admins` can configure instance settings with [God mode](https://developers.plane.so/self-hosting/govern/instance-admin).\n\n## 🌟 Features\n\n- **Work Items**\n Efficiently create and manage tasks with a robust rich text editor that supports file uploads. Enhance organization and tracking by adding sub-properties and referencing related issues.\n\n- **Cycles**\n Maintain your team’s momentum with Cycles. Track progress effortlessly using burn-down charts and other insightful tools.\n\n- **Modules**\n Simplify complex projects by dividing them into smaller, manageable modules.\n\n- **Views**\n Customize your workflow by creating filters to display only the most relevant issues. Save and share these views with ease.\n\n- **Pages**\n Capture and organize ideas using Plane Pages, complete with AI capabilities and a rich text editor. Format text, insert images, add hyperlinks, or convert your notes into actionable items.\n\n- **Analytics**\n Access real-time insights across all your Plane data. Visualize trends, remove blockers, and keep your projects moving forward.\n\n## 🛠️ Local development\n\nSee [CONTRIBUTING](./CONTRIBUTING.md)\n\n## ⚙️ Built with\n\n[](https://reactrouter.com/)\n[](https://www.djangoproject.com/)\n[](https://nodejs.org/en)\n\n## 📸 Screenshots\n\n
\n\n\n## 📝 Documentation\n\nExplore Plane's [product documentation](https://docs.plane.so/) and [developer documentation](https://developers.plane.so/) to learn about features, setup, and usage.\n\n## ❤️ Community\n\nJoin the Plane community on [GitHub Discussions](https://github.com/orgs/makeplane/discussions) and our [Forum](https://forum.plane.so). We follow a [Code of conduct](https://github.com/makeplane/plane/blob/master/CODE_OF_CONDUCT.md) in all our community channels.\n\nFeel free to ask questions, report bugs, participate in discussions, share ideas, request features, or showcase your projects. We’d love to hear from you!\n\n## 🛡️ Security\n\nIf you discover a security vulnerability in Plane, please report it responsibly instead of opening a public issue. We take all legitimate reports seriously and will investigate them promptly. See [Security policy](https://github.com/makeplane/plane/blob/master/SECURITY.md) for more info.\n\nTo disclose any security issues, please email us at security@plane.so.\n\n## 🤝 Contributing\n\nThere are many ways you can contribute to Plane:\n\n- Report [bugs](https://github.com/makeplane/plane/issues/new?assignees=srinivaspendem%2Cpushya22&labels=%F0%9F%90%9Bbug&projects=&template=--bug-report.yaml&title=%5Bbug%5D%3A+) or submit [feature requests](https://github.com/makeplane/plane/issues/new?assignees=srinivaspendem%2Cpushya22&labels=%E2%9C%A8feature&projects=&template=--feature-request.yaml&title=%5Bfeature%5D%3A+).\n- Review the [documentation](https://docs.plane.so/) and submit [pull requests](https://github.com/makeplane/docs) to improve it—whether it's fixing typos or adding new content.\n- Talk or write about Plane or any other ecosystem integration and [let us know](https://forum.plane.so)!\n- Show your support by upvoting [popular feature requests](https://github.com/makeplane/plane/issues).\n\nPlease read [CONTRIBUTING.md](https://github.com/makeplane/plane/blob/master/CONTRIBUTING.md) for details on the process for submitting pull requests to us.\n\n### Repo activity\n\n![Plane Repo Activity](https://repobeats.axiom.co/api/embed/2523c6ed2f77c082b7908c33e2ab208981d76c39.svg \"Repobeats analytics image\")\n\n### We couldn't have done this without you.\n\n\n \n\n\n## License\n\nThis project is licensed under the [GNU Affero General Public License v3.0](https://github.com/makeplane/plane/blob/master/LICENSE.txt).\n",
"manifest_file": "package.json",
"manifest_content": "{\n \"name\": \"plane\",\n \"version\": \"1.3.1\",\n \"private\": true,\n \"description\": \"Open-source project management that unlocks customer value\",\n \"license\": \"AGPL-3.0\",\n \"repository\": \"https://github.com/makeplane/plane.git\",\n \"scripts\": {\n \"build\": \"turbo run build\",\n \"dev\": \"turbo run dev --concurrency=18\",\n \"start\": \"turbo run start\",\n \"clean\": \"turbo run clean && rm -rf .turbo && rm -rf .next && rm -rf node_modules && rm -rf dist\",\n \"fix\": \"turbo run fix\",\n \"fix:format\": \"turbo run fix:format\",\n \"fix:lint\": \"turbo run fix:lint\",\n \"check\": \"turbo run check\",\n \"check:lint\": \"turbo run check:lint\",\n \"check:format\": \"turbo run check:format\",\n \"check:types\": \"turbo run check:types\",\n \"prepare\": \"husky\",\n \"doctor\": \"npx react-doctor@latest\"\n },\n \"devDependencies\": {\n \"husky\": \"catalog:\",\n \"lint-staged\": \"catalog:\",\n \"oxfmt\": \"catalog:\",\n \"oxlint\": \"catalog:\",\n \"react-doctor\": \"^0.4.2\",\n \"turbo\": \"catalog:\"\n },\n \"lint-staged\": {\n \"*.{js,jsx,ts,tsx,cjs,mjs,cts,mts,json,css,md}\": [\n \"pnpm exec oxfmt --no-error-on-unmatched-pattern\"\n ],\n \"*.{js,jsx,ts,tsx,cjs,mjs,cts,mts}\": [\n \"pnpm exec oxlint --fix --deny-warnings\"\n ]\n },\n \"engines\": {\n \"node\": \">=22.18.0\"\n },\n \"packageManager\": \"pnpm@11.3.0+sha512.2c403d6594527287672b1f7056343a1f7c3634036a67ffabfcc2b3d7595d843768f8787148d1b57cf7956c90606bbd192857c363af19e96d2d0ec9ec5741d215\"\n}\n",
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{
"owner": "openai",
"name": "codex",
"full_name": "openai/codex",
"url": "https://github.com/openai/codex",
"description": "Lightweight coding agent that runs in your terminal",
"language": "Rust",
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Codex CLI is a coding agent from OpenAI that runs locally on your computer.\n
\n \n
\n\nIf you want Codex in your code editor (VS Code, Cursor, Windsurf), install in your IDE.\nIf you want the desktop app experience, run codex app or visit the Codex App page.\nIf you are looking for the cloud-based agent from OpenAI, Codex Web, go to chatgpt.com/codex.\n\n---\n\n## Quickstart\n\n### Installing and running Codex CLI\n\nRun the following on Mac or Linux to install Codex CLI:\n\n```shell\ncurl -fsSL https://chatgpt.com/codex/install.sh | sh\n```\n\nRun the following on Windows to install Codex CLI:\n\n```\npowershell -ExecutionPolicy ByPass -c \"irm https://chatgpt.com/codex/install.ps1 | iex\"\n```\n\nCodex CLI can also be installed via the following package managers:\n\n```shell\n# Install using npm\nnpm install -g @openai/codex\n```\n\n```shell\n# Install using Homebrew\nbrew install --cask codex\n```\n\nThen simply run `codex` to get started.\n\n\nYou can also go to the latest GitHub Release and download the appropriate binary for your platform.\n\nEach GitHub Release contains many executables, but in practice, you likely want one of these:\n\n- macOS\n - Apple Silicon/arm64: `codex-aarch64-apple-darwin.tar.gz`\n - x86_64 (older Mac hardware): `codex-x86_64-apple-darwin.tar.gz`\n- Linux\n - x86_64: `codex-x86_64-unknown-linux-musl.tar.gz`\n - arm64: `codex-aarch64-unknown-linux-musl.tar.gz`\n\nEach archive contains a single entry with the platform baked into the name (e.g., `codex-x86_64-unknown-linux-musl`), so you likely want to rename it to `codex` after extracting it.\n\n\n\n### Using Codex with your ChatGPT plan\n\nRun `codex` and select **Sign in with ChatGPT**. We recommend signing into your ChatGPT account to use Codex as part of your Plus, Pro, Business, Edu, or Enterprise plan. [Learn more about what's included in your ChatGPT plan](https://help.openai.com/en/articles/11369540-codex-in-chatgpt).\n\nYou can also use Codex with an API key, but this requires [additional setup](https://developers.openai.com/codex/auth#sign-in-with-an-api-key).\n\n## Docs\n\n- [**Codex Documentation**](https://developers.openai.com/codex)\n- [**Contributing**](./docs/contributing.md)\n- [**Installing & building**](./docs/install.md)\n- [**Open source fund**](./docs/open-source-fund.md)\n\nThis repository is licensed under the [Apache-2.0 License](LICENSE).\n",
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"owner": "BuilderIO",
"name": "agent-native",
"full_name": "BuilderIO/agent-native",
"url": "https://github.com/BuilderIO/agent-native",
"description": "A framework for building agent-native applications.",
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"readme_content": "# Agent-Native\n\n## The framework for agent-native apps\n\nAgent-Native is an open-source framework for building robust agents that act inside real apps, not just chat next to them. It gives you primitives for product-grade agentic software: shared actions, SQL-backed state, identity, tools, skills, jobs, observability, and UI surfaces that all work together. Bring your own database, hosting provider, model stack, and app code.\n\n```ts\n// One action powers UI, agent, HTTP, MCP, A2A, and CLI.\nexport default defineAction({\n schema: z.object({\n emailId: z.string(),\n body: z.string(),\n }),\n run: async ({ emailId, body }) => {\n await db.insert(replies).values({ emailId, body });\n },\n});\n```\n\n- **Actions**: Define work once. Use it from UI, agent, API, MCP, A2A, and CLI.\n- **Agent runtime**: Chat, tools, skills, memory, jobs, observability, and handoffs ship together.\n- **Backend agnostic**: Plug in any Drizzle-supported SQL database and Nitro-compatible host.\n\n## Templates\n\nStart with a full featured template. Each one is a complete, 100% free and open-source SaaS app: cloneable, not scaffolded, except you own the code and can customize everything.\n\n
\n
\n
\n\n**Clips**\n\n\n\n**Agent-Native Loom + Jam**\n\nRecord your screen with auto-transcripts and captured browser debug logs, share a link, and let an agent read the transcript, see timestamped frames, and fix the bug.\n\n
\n
\n\n**Plans**\n\n\n\n**Visual plan mode for coding agents**\n\nInstall `/visual-plan` and `/visual-recap` so your coding agent can plan before it builds and recap changes after they land. High-level code reviews with diagrams, wireframes, annotations, and review links.\n\n
\n
\n\n**Design**\n\n\n\n**Agent-Native design prototyping**\n\nGenerate interactive HTML prototypes, compare variants, refine controls, and export the result.\n\n
\n
\n
\n
\n\n**Content**\n\n\n\n**Open-source Obsidian for MDX**\n\nEdit local Markdown/MDX files, generate rich interactive custom blocks, and draft, rewrite, or publish with an agent.\n\n
\n
\n\n**Slides**\n\n\n\n**Agent-Native Google Slides, Pitch**\n\nGenerate and edit React-based presentations via prompt or point-and-click.\n\n
\n
\n\n**Analytics**\n\n\n\n**Agent-Native Amplitude, Mixpanel**\n\nConnect analytics data sources, prompt for real charts, and build reusable dashboards.\n\n
\n
\n
\n\nView the full template gallery at **[agent-native.com/templates](https://agent-native.com/templates)**.\n\n## Agents and UIs, Fully Connected\n\nThe agent and the UI are equal citizens of one system. Every action works both ways: click it or ask for it.\n\n\n\n- **Everything syncs**: One database, one state. Changes from either side show up instantly on the other.\n- **Real-time multiplayer**: Humans and agents edit the same document together, with the agent as a first-class peer.\n- **Context-aware**: The agent knows what you're looking at. Select text, hit Cmd+I, and tell it what to do.\n- **Agents call agents**: Tag another agent from any app and they coordinate over A2A.\n- **Self-improving**: The agent can add features, fix bugs, and refine the UI over time.\n\n## Try it with a skill\n\nDon't want to scaffold a whole app yet? Add visual planning and PR recaps to Claude Code, Codex, Cursor, Pi, OpenCode, GitHub Copilot / VS Code, and similar agents with one command:\n\n```bash\nnpx @agent-native/core@latest skills add visual-plan\n```\n\n\n\nYou get two slash commands:\n\n- **`/visual-plan`**: before the agent writes code, it opens a structured, reviewable plan with inline diagrams, UI wireframes, file-by-file implementation maps, and annotations you can comment on and approve.\n- **`/visual-recap`**: after changes land, it turns a PR or git diff into a high-altitude visual recap with a shareable review link instead of a raw diff.\n\nSee the **[Skills Guide](https://agent-native.com/docs/skills-guide#app-backed-skills)** for more.\n\n## Quick Start\n\nOne command to start a new project locally.\n\n```bash\nnpx @agent-native/core@latest create my-app\ncd my-app\npnpm install\npnpm dev\n```\n\n`create` first asks how you want to start:\n\n- **Full template(s)**: clone one or more complete apps into a workspace. Pick Mail + Calendar + Forms and you get all three wired up and sharing auth.\n- **Chat**: a single app with a minimal chat UI and the browser shell already wired, the simplest way to get a UI.\n- **Headless**: a single action-first app with no UI shell. The CLI walks you through calling your first action and agent, and you can add a UI later.\n\nPrefer flags? `create my-app --template mail`, `--headless`, or `--standalone` skip the prompt.\n\n## The Best of Both Worlds\n\n| | SaaS Tools | Raw AI Agents | Internal Tools | Agent-Native |\n| ----------------- | ------------------ | ----------------------- | -------------------------- | ----------------------- |\n| **UI** | Polished but rigid | None | Mixed quality | Full UI, fork & go |\n| **AI** | Bolted on | Powerful | Shallowly connected | Agent-first, integrated |\n| **Customization** | Can't | Instructions and skills | Full, but high maintenance | Agent modifies the app |\n| **Ownership** | Rented | Somewhat yours | You own the code | You own the code |\n\n## Community\n\nJoin the **[Discord](https://discord.gg/qm82StQ2NC)** to ask questions, share what you're building, and get help.\n\n## Docs\n\nFull documentation at **[agent-native.com](https://agent-native.com)**.\n\n## License\n\nMIT\n",
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"readme_content": "# Flue — The Agent Harness Framework\n\nNot another SDK. Build autonomous agents and powerful AI workflows with Flue's programmable TypeScript harness.\n\n```ts\n// agents/triage.ts\nimport { defineAgent, type AgentRouteHandler } from '@flue/runtime';\nimport { local } from '@flue/runtime/node';\nimport triage from '../skills/triage/SKILL.md' with { type: 'skill' };\nimport verify from '../skills/verify/SKILL.md' with { type: 'skill' };\nimport * as githubTools from '../tools/github.ts';\n\n// Give agents the context and autonomy to solve complex tasks:\nconst instructions = `\nTriage a bug report end-to-end: reproduce the bug,\ndiagnose the root cause, verify whether the behavior is\nintentional, and attempt a fix.\n\n...`;\n\n// Expose (and protect) your agents over HTTP:\nexport const route: AgentRouteHandler = async (_c, next) => next();\n\n// Compose the complete harness your agent needs to do real work,\n// complete with virtual, local, or remote container sandbox.\nexport default defineAgent(() => ({\n model: 'anthropic/claude-sonnet-4-6',\n tools: [...githubTools],\n skills: [triage, verify],\n sandbox: local(),\n instructions,\n}));\n```\n\n## The framework for building the next generation of agents.\n\nThe first agents were built with raw LLM API calls. This worked for simple chatbots and scripted tasks, but not much else.\n\nAgents like Claude Code and Codex broke the mold. These were _real agents._ Autonomous. You give them a task — not a pre-defined series of steps — and trust them to complete it using the context and tools that you provide.\n\n**Flue unlocks this new architecture for agents.** Its built-in TypeScript harness gives any model the context and environment it needs for truly autonomous work: sessions, tools, skills, instructions, filesystem access, and a secure sandbox to run in. Run your agents locally via CLI or deploy them to your hosted runtime of choice.\n\n## Features\n\nBuild agents that can safely take action, maintain continuity, and connect to the systems where work already happens.\n\n- **[Agents](https://flueframework.com/docs/guide/building-agents/)** — Build agents that can keep context across conversations and events as they autonomously work toward a goal.\n- **[Workflows](https://flueframework.com/docs/guide/workflows/)** — Run structured automations where your code guides agent reasoning from a clear input to a finished result.\n- **[Sandboxes](https://flueframework.com/docs/guide/sandboxes/)** — Give agents a secure environment where they can use tools, modify files, and autonomously complete real work.\n- **[Durable Execution](https://flueframework.com/docs/guide/durable-execution/)** — Learn how agents preserve progress through failures and restarts with durable recovery for accepted work.\n- **[Subagents](https://flueframework.com/docs/guide/subagents/)** — Define specialized roles for different tasks, then let your agent delegate work to the right expert.\n- **[Tools](https://flueframework.com/docs/guide/tools/)** — Give agents typed actions for calling APIs, querying data, and making controlled changes through your application.\n- **[Skills](https://flueframework.com/docs/guide/skills/)** — Package reusable expertise and workflows that agents can load whenever a task needs specialized guidance.\n- **[MCP Servers](https://flueframework.com/docs/guide/tools/#connect-mcp-tools)** — Connect agents to authenticated tools and services through the open Model Context Protocol ecosystem.\n- **[Observability](https://flueframework.com/docs/guide/observability/)** — Monitor your agents and export telemetry with [OpenTelemetry](https://flueframework.com/docs/ecosystem/tooling/opentelemetry/), [Braintrust](https://flueframework.com/docs/ecosystem/tooling/braintrust/), [Sentry](https://flueframework.com/docs/ecosystem/tooling/sentry/), or your own observer.\n- **[Channels](https://flueframework.com/docs/guide/channels/)** — Receive verified events from Slack, Teams, Discord, GitHub, and more.\n\n## Deploy Anywhere\n\n- **[Node.js](https://flueframework.com/docs/ecosystem/deploy/node/)**\n- **[Cloudflare Workers](https://flueframework.com/docs/ecosystem/deploy/cloudflare/)**\n- **[GitHub Actions](https://flueframework.com/docs/ecosystem/deploy/github-actions/)**\n- **[GitLab CI/CD](https://flueframework.com/docs/ecosystem/deploy/gitlab-ci/)**\n- **[Daytona](https://flueframework.com/docs/ecosystem/sandboxes/daytona/)**\n- **[Render](https://flueframework.com/docs/ecosystem/deploy/render/)**\n\n## Packages\n\n| Package | Description |\n| ----------------------------------------------- | ------------------------------------------------------ |\n| [`@flue/runtime`](packages/runtime) | Runtime: harness, sessions, tools, sandbox |\n| [`@flue/cli`](packages/cli) | CLI and build/dev tooling (`flue` binary) |\n| [`@flue/sdk`](packages/sdk) | Client SDK for consuming deployed agents and workflows |\n| [`@flue/opentelemetry`](packages/opentelemetry) | OpenTelemetry tracing adapter |\n| [`@flue/postgres`](packages/postgres) | Postgres persistence adapter |\n",
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gws
\n\n**One CLI for all of Google Workspace — built for humans and AI agents.** \nDrive, Gmail, Calendar, and every Workspace API. Zero boilerplate. Structured JSON output. 40+ agent skills included.\n\n> [!NOTE]\n> This is **not** an officially supported Google product.\n\n
\n \n \n \n \n
\n \n\n⬇️ **[Download the latest release for your OS](https://github.com/googleworkspace/cli/releases)**\n\n`gws` doesn't ship a static list of commands. It reads Google's own [Discovery Service](https://developers.google.com/discovery) at runtime and builds its entire command surface dynamically. When Google Workspace adds an API endpoint or method, `gws` picks it up automatically.\n\n> [!IMPORTANT]\n> This project is under active development. Expect breaking changes as we march toward v1.0.\n\n## Contents\n\n- [Prerequisites](#prerequisites)\n- [Installation](#installation)\n- [Quick Start](#quick-start)\n- [Why gws?](#why-gws)\n- [Authentication](#authentication)\n- [AI Agent Skills](#ai-agent-skills)\n- [Advanced Usage](#advanced-usage)\n- [Environment Variables](#environment-variables)\n- [Exit Codes](#exit-codes)\n- [Architecture](#architecture)\n- [Troubleshooting](#troubleshooting)\n- [Development](#development)\n\n## Prerequisites\n\n- **Node.js 18+** — for `npm install` (or download a pre-built binary from [GitHub Releases](https://github.com/googleworkspace/cli/releases))\n- **A Google Cloud project** — required for OAuth credentials. You can create one via the [Google Cloud Console](https://console.cloud.google.com/) or with the [`gcloud` CLI](https://cloud.google.com/sdk/docs/install) or with the `gws auth setup` command.\n- **A Google account** with access to Google Workspace\n\n## Installation\n\nThe recommended way to install `gws` is to download the pre-built binary for your OS and architecture from the **[GitHub Releases](https://github.com/googleworkspace/cli/releases)** page. Extract the archive and place the `gws` binary in your `$PATH`.\n\nFor convenience, you can also use `npm` to automate downloading the appropriate binary from GitHub Releases:\n\n```bash\nnpm install -g @googleworkspace/cli\n```\n\nOr build from source:\n\n```bash\ncargo install --git https://github.com/googleworkspace/cli --locked\n```\n\nA Nix flake is also available at `github:googleworkspace/cli`\n\n```bash\nnix run github:googleworkspace/cli\n```\n\nOn macOS and Linux, you can also install via [Homebrew](https://brew.sh/):\n\n```bash\nbrew install googleworkspace-cli\n```\n\n## Quick Start\n\n```bash\ngws auth setup # walks you through Google Cloud project config\ngws auth login # subsequent OAuth login\ngws drive files list --params '{\"pageSize\": 5}'\n```\n\n## Why gws?\n\n**For humans** — stop writing `curl` calls against REST docs. `gws` gives you `--help` on every resource, `--dry-run` to preview requests, and auto‑pagination.\n\n**For AI agents** — every response is structured JSON. Pair it with the included agent skills and your LLM can manage Workspace without custom tooling.\n\n```bash\n# List the 10 most recent files\ngws drive files list --params '{\"pageSize\": 10}'\n\n# Create a spreadsheet\ngws sheets spreadsheets create --json '{\"properties\": {\"title\": \"Q1 Budget\"}}'\n\n# Send a Chat message\ngws chat spaces messages create \\\n --params '{\"parent\": \"spaces/xyz\"}' \\\n --json '{\"text\": \"Deploy complete.\"}' \\\n --dry-run\n\n# Introspect any method's request/response schema\ngws schema drive.files.list\n\n# Stream paginated results as NDJSON\ngws drive files list --params '{\"pageSize\": 100}' --page-all | jq -r '.files[].name'\n```\n\n## Authentication\n\nThe CLI supports multiple auth workflows so it works on your laptop, in CI, and on a server.\n\n### Which setup should I use?\n\n| I have… | Use |\n|---|---|\n| `gcloud` installed and authenticated | [`gws auth setup`](#interactive-local-desktop) (fastest) |\n| A GCP project but no `gcloud` | [Manual OAuth setup](#manual-oauth-setup-google-cloud-console) |\n| An existing OAuth access token | [`GOOGLE_WORKSPACE_CLI_TOKEN`](#pre-obtained-access-token) |\n| Existing Credentials | [`GOOGLE_WORKSPACE_CLI_CREDENTIALS_FILE`](#service-account-server-to-server) |\n\n### Interactive (local desktop)\n\nCredentials are encrypted at rest (AES-256-GCM) with the key stored in your OS keyring (or `~/.config/gws/.encryption_key` when `GOOGLE_WORKSPACE_CLI_KEYRING_BACKEND=file`).\n\n```bash\ngws auth setup # one-time: creates a Cloud project, enables APIs, logs you in\ngws auth login # subsequent scope selection and login\n```\n\n> `gws auth setup` requires the [`gcloud` CLI](https://cloud.google.com/sdk/docs/install). If you don't have `gcloud`, use the [manual setup](#manual-oauth-setup-google-cloud-console) below instead.\n\n> [!WARNING]\n> **Scope limits in testing mode:** If your OAuth app is unverified (testing mode),\n> Google limits consent to ~25 scopes. The `recommended` scope preset includes 85+\n> scopes and **will fail** for unverified apps (especially for `@gmail.com` accounts).\n> Choose individual services instead to filter the scope picker:\n> ```bash\n> gws auth login -s drive,gmail,sheets\n> ```\n\n\n### Manual OAuth setup (Google Cloud Console)\n\nUse this when `gws auth setup` cannot automate project/client creation, or when you want explicit control.\n\n1. Open Google Cloud Console in the target project:\n - OAuth consent screen: `https://console.cloud.google.com/apis/credentials/consent?project=`\n - Credentials: `https://console.cloud.google.com/apis/credentials?project=`\n2. Configure OAuth branding/audience if prompted:\n - App type: **External** (testing mode is fine)\n3. Add your account under **Test users**\n4. Create an OAuth client:\n - Type: **Desktop app**\n5. Download the client JSON and save it to:\n - `~/.config/gws/client_secret.json`\n\n> [!IMPORTANT]\n> **You must add yourself as a test user.** In the OAuth consent screen, click\n> **Test users → Add users** and enter your Google account email. Without this,\n> login will fail with a generic \"Access blocked\" error.\n\nThen run:\n\n```bash\ngws auth login\n```\n\n### Browser-assisted auth (human or agent)\n\nYou can complete OAuth either manually or with browser automation.\n\n- **Human flow**: run `gws auth login`, open the printed URL, approve scopes.\n- **Agent-assisted flow**: the agent opens the URL, selects account, handles consent prompts, and returns control once the localhost callback succeeds.\n\nIf consent shows **\"Google hasn't verified this app\"** (testing mode), click **Continue**.\nIf scope checkboxes appear, select required scopes (or **Select all**) before continuing.\n\n### Headless / CI (export flow)\n\n1. Complete interactive auth on a machine with a browser.\n2. Export credentials:\n ```bash\n gws auth export --unmasked > credentials.json\n ```\n3. On the headless machine:\n ```bash\n export GOOGLE_WORKSPACE_CLI_CREDENTIALS_FILE=/path/to/credentials.json\n gws drive files list # just works\n ```\n\n### Service Account (server-to-server)\n\nPoint to your key file; no login needed.\n\n```bash\nexport GOOGLE_WORKSPACE_CLI_CREDENTIALS_FILE=/path/to/service-account.json\ngws drive files list\n```\n\n### Pre-obtained Access Token\n\nUseful when another tool (e.g. `gcloud`) already mints tokens for your environment.\n\n```bash\nexport GOOGLE_WORKSPACE_CLI_TOKEN=$(gcloud auth print-access-token)\n```\n\n### Precedence\n\n| Priority | Source | Set via |\n| -------- | ---------------------- | --------------------------------------- |\n| 1 | Access token | `GOOGLE_WORKSPACE_CLI_TOKEN` |\n| 2 | Credentials file | `GOOGLE_WORKSPACE_CLI_CREDENTIALS_FILE` |\n| 3 | Encrypted credentials | `gws auth login` |\n| 4 | Plaintext credentials | `~/.config/gws/credentials.json` |\n\nEnvironment variables can also live in a `.env` file.\n\n## AI Agent Skills\n\nThe repo ships 100+ Agent Skills (`SKILL.md` files) — one for every supported API, plus higher-level helpers for common workflows and 50 curated recipes for Gmail, Drive, Docs, Calendar, and Sheets. See the full [Skills Index](docs/skills.md) for the complete list.\n\n```bash\n# Install all skills at once\nnpx skills add https://github.com/googleworkspace/cli\n\n# Or pick only what you need\nnpx skills add https://github.com/googleworkspace/cli/tree/main/skills/gws-drive\nnpx skills add https://github.com/googleworkspace/cli/tree/main/skills/gws-gmail\n```\n\n\nOpenClaw setup\n\n```bash\n# Symlink all skills (stays in sync with repo)\nln -s $(pwd)/skills/gws-* ~/.openclaw/skills/\n\n# Or copy specific skills\ncp -r skills/gws-drive skills/gws-gmail ~/.openclaw/skills/\n```\n\nThe `gws-shared` skill includes an `install` block so OpenClaw auto-installs the CLI via `npm` if `gws` isn't on PATH.\n\n\n\n## Gemini CLI Extension\n\n1. Authenticate the CLI first:\n\n ```bash\n gws auth setup\n ```\n\n2. Install the extension into the Gemini CLI:\n ```bash\n gemini extensions install https://github.com/googleworkspace/cli\n ```\n\nInstalling this extension gives your Gemini CLI agent direct access to all `gws` commands and Google Workspace agent skills. Because `gws` handles its own authentication securely, you simply need to authenticate your terminal once prior to using the agent, and the extension will automatically inherit your credentials.\n\n## Advanced Usage\n\n### Multipart Uploads\n\n```bash\ngws drive files create --json '{\"name\": \"report.pdf\"}' --upload ./report.pdf\n```\n\n### Pagination\n\n| Flag | Description | Default |\n| ------------------- | ---------------------------------------------- | ------- |\n| `--page-all` | Auto-paginate, one JSON line per page (NDJSON) | off |\n| `--page-limit ` | Max pages to fetch | 10 |\n| `--page-delay ` | Delay between pages | 100 ms |\n\n### Google Sheets — Shell Escaping\n\nSheets ranges use `!` which bash interprets as history expansion. Always wrap values in **single quotes**:\n\n```bash\n# Read cells A1:C10 from \"Sheet1\"\ngws sheets spreadsheets values get \\\n --params '{\"spreadsheetId\": \"SPREADSHEET_ID\", \"range\": \"Sheet1!A1:C10\"}'\n\n# Append rows\ngws sheets spreadsheets values append \\\n --params '{\"spreadsheetId\": \"ID\", \"range\": \"Sheet1!A1\", \"valueInputOption\": \"USER_ENTERED\"}' \\\n --json '{\"values\": [[\"Name\", \"Score\"], [\"Alice\", 95]]}'\n```\n\n### Helper Commands\n\nSome services ship hand-crafted helper commands alongside the auto-generated Discovery surface. Helper commands are prefixed with `+` so they are visually distinct and never collide with Discovery-generated method names.\n\nTime-aware helpers (`+agenda`, `+standup-report`, `+weekly-digest`, `+meeting-prep`) automatically use your **Google account timezone** (fetched from Calendar Settings API and cached for 24 hours). Override with `--timezone`/`--tz` on `+agenda`, or set the `--timezone` flag for explicit control.\n\nRun `gws --help` to see both Discovery methods and helper commands together.\n\n```bash\ngws gmail --help # shows +send, +reply, +reply-all, +forward, +triage, +watch …\ngws calendar --help # shows +insert, +agenda …\ngws drive --help # shows +upload …\n```\n\n**Full helper reference:**\n\n| Service | Command | Description |\n|---------|---------|-------------|\n| `gmail` | `+send` | Send a",
"manifest_file": "Cargo.toml",
"manifest_content": "# Copyright 2026 Google LLC\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in writing, software\n# distributed under the License is distributed on an \"AS IS\" BASIS,\n# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n# See the License for the specific language governing permissions and\n# limitations under the License.\n\n[workspace]\nmembers = [\"crates/google-workspace-cli\", \"crates/google-workspace\"]\nresolver = \"2\"\n\n# The profile that 'cargo dist' will build with\n[profile.dist]\ninherits = \"release\"\nlto = \"thin\"\n",
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{
"owner": "stablyai",
"name": "orca",
"full_name": "stablyai/orca",
"url": "https://github.com/stablyai/orca",
"description": "Orca is the ADE for working with a fleet of parallel agents. Run any coding agent with your own subscription. Available on desktop and mobile.",
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"ghostty",
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"license": "MIT",
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"created_at": "2026-03-17T03:28:57Z",
"pushed_at": "2026-06-25T11:16:54Z",
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\n\n### Mobile Companion\n\nMonitor and steer your agents from your phone — get notified when an agent finishes and send follow-ups from anywhere.\n\n[iOS App Store](https://apps.apple.com/us/app/orca-ide/id6766130217) · [TestFlight](https://testflight.apple.com/join/YjeGMQBA) · [Android APK](https://github.com/stablyai/orca/releases/download/mobile-android-v0.0.16/app-release.apk) · [Docs →](https://www.onorca.dev/docs/mobile)\n\n
\n
\n \n
\n
\n
\n
\n\n### Parallel Worktrees\n\nFan one prompt across five agents, each in its own isolated git worktree — compare the results and merge the winner.\n\n[Docs →](https://www.onorca.dev/docs/model/worktrees)\n\n
\n
\n \n
\n
\n
\n
\n\n### Terminal Splits\n\nGhostty-class terminals with WebGL rendering, infinite splits, and scrollback that survives restarts.\n\n[Docs →](https://www.onorca.dev/docs/terminal)\n\n
\n
\n \n
\n
\n
\n
\n\n### Design Mode\n\nClick any UI element in a real Chromium window to send its HTML, CSS, and a cropped screenshot straight into your agent's prompt.\n\n[Docs →](https://www.onorca.dev/docs/browser/design-mode)\n\n
\n
\n \n
\n
\n
\n
\n\n### GitHub & Linear, Native\n\nBrowse PRs, issues, and project boards in-app — open a worktree from any task and review without a context switch.\n\n[Docs →](https://www.onorca.dev/docs/review/linear)\n\n
\n
\n \n
\n
\n
\n
\n\n### SSH Worktrees\n\nRun agents on a beefy remote box with full file editing, git, and terminals — auto-reconnect and port forwarding included.\n\n[Docs →](https://www.onorca.dev/docs/ssh)\n\n
\n
\n \n
\n
\n
\n
\n\n### Annotate AI Diffs\n\nDrop comments on any diff line and ship them back to the agent — review, edit, and commit without leaving Orca.\n\n[Docs →](https://www.onorca.dev/docs/review/annotate-ai-diff)\n\n
\n
\n \n
\n
\n
\n
\n\n### Drag Files to Agents\n\nVS Code's editor with autosave everywhere — drag files or images straight into an agent prompt.\n\n[Docs →](https://www.onorca.dev/docs/editing/file-explorer)\n\n
\n
\n \n
\n
\n
\n
\n\n### Orca CLI\n\nAgents drive Orca too — script every workflow with `orca worktree create`, `snapshot`, `click`, and `fill`.\n\n[Docs →](https://www.onorca.dev/docs/cli/overview)\n\n
\n
\n \n
\n
\n
\n\n**Also in the box:**\n\n- **[Quick open](https://www.onorca.dev/docs/model/quick-open)** — Search across worktrees, files, agents, commands, and repo context without leaving your flow.\n- **[Account switcher & usage tracking](https://www.onorca.dev/docs/agents/usage-tracking)** — See Claude and Codex usage and rate-limit resets, and hot-swap accounts without re-logging in.\n- **[Rich repo previews](https://www.onorca.dev/docs/editing/markdown)** — Preview Markdown, images, PDFs, and repo docs in the workspace.\n- **[Computer Use](https://www.onorca.dev/docs/cli/computer-use)** — Let agents operate desktop apps and visible UI when a workflow needs real interaction.\n- **[Notifications and unread state](https://www.onorca.dev/docs/notifications)** — Know when an agent finishes or needs attention, then mark threads unread to come back later.\n- **And many, many more** — we ship daily, so this list is perpetually behind. The [changelog](https://github.com/stablyai/orca/releases) is the real feature list.\n\n---\n\n## Supported Agents\n\nWorks with **any CLI agent** — if it runs in a terminal, it runs in Orca.\n\n
\n \n\n## What is iroh?\n\nIroh gives you an API for dialing by public key.\nYou say “connect to that phone”, iroh will find & maintain the fastest connection for you, regardless of where it is.\n\n### Hole-punching\n\nThe fastest route is a direct connection, so if necessary, iroh tries to hole-punch.\nShould this fail, it can fall back to an open ecosystem of public relay servers.\nTo ensure these connections are as fast as possible, we [continuously measure iroh][iroh-perf].\n\n### Built on [QUIC]\n\nIroh uses [noq] to establish [QUIC] connections between endpoints.\nThis way you get authenticated encryption, concurrent streams with stream priorities, a datagram transport and avoid head-of-line-blocking out of the box.\n\n## Compose Protocols\n\nUse pre-existing protocols built on iroh instead of writing your own:\n- [iroh-blobs] for [BLAKE3]-based content-addressed blob transfer scaling from kilobytes to terabytes\n- [iroh-gossip] for establishing publish-subscribe overlay networks that scale, requiring only resources that your average phone can handle\n- [iroh-docs] for an eventually-consistent key-value store of [iroh-blobs] blobs\n\n## Getting Started\n\n### Rust Library\n\nIt's easiest to use iroh from rust.\nInstall it using `cargo add iroh`, then on the connecting side:\n\n```rs\nconst ALPN: &[u8] = b\"iroh-example/echo/0\";\n\nlet endpoint = Endpoint::bind().await?;\n\n// Open a connection to the accepting endpoint\nlet conn = endpoint.connect(addr, ALPN).await?;\n\n// Open a bidirectional QUIC stream\nlet (mut send, mut recv) = conn.open_bi().await?;\n\n// Send some data to be echoed\nsend.write_all(b\"Hello, world!\").await?;\nsend.finish()?;\n\n// Receive the echo\nlet response = recv.read_to_end(1000).await?;\nassert_eq!(&response, b\"Hello, world!\");\n\n// As the side receiving the last application data - say goodbye\nconn.close(0u32.into(), b\"bye!\");\n\n// Close the endpoint and all its connections\nendpoint.close().await;\n```\n\nAnd on the accepting side:\n```rs\nlet endpoint = Endpoint::bind().await?;\n\nlet router = Router::builder(endpoint)\n .accept(ALPN.to_vec(), Arc::new(Echo))\n .spawn()\n .await?;\n\n// The protocol definition:\n#[derive(Debug, Clone)]\nstruct Echo;\n\nimpl ProtocolHandler for Echo {\n async fn accept(&self, connection: Connection) -> Result<()> {\n let (mut send, mut recv) = connection.accept_bi().await?;\n\n // Echo any bytes received back directly.\n let bytes_sent = tokio::io::copy(&mut recv, &mut send).await?;\n\n send.finish()?;\n connection.closed().await;\n\n Ok(())\n }\n}\n```\n\nThe full example code with more comments can be found at [`echo.rs`][echo-rs].\n\nOr use one of the pre-existing protocols, e.g. [iroh-blobs] or [iroh-gossip].\n\n### Other Languages\n\nIf you want to use iroh from other languages, make sure to check out [iroh-ffi], the repository for FFI bindings.\n\n### Links\n\n- [Introducing Iroh (video)][iroh-yt-video]\n- [Iroh Documentation][docs]\n- [Iroh Examples]\n- [Iroh Experiments]\n\n## Repository Structure\n\nThis repository contains a workspace of crates:\n- `iroh`: The core library for hole-punching & communicating with relays.\n- `iroh-relay`: The relay client and server implementation. This is the code we run in production for the public relays (and you can, too!).\n- `iroh-base`: Common types like `EndpointId` or `RelayUrl`.\n- `iroh-dns-server`: DNS server implementation powering the DNS/Pkarr address lookup for EndpointIds, running at dns.iroh.link.\n\n## License\n\nCopyright 2025 N0, INC.\n\nThis project is licensed under either of\n\n * Apache License, Version 2.0, ([LICENSE-APACHE](LICENSE-APACHE) or\n https://www.apache.org/licenses/LICENSE-2.0)\n * MIT license ([LICENSE-MIT](LICENSE-MIT) or\n https://opensource.org/licenses/MIT)\n\nat your option.\n\n## Contribution\n\nUnless you explicitly state otherwise, any contribution intentionally submitted for inclusion in this project by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.\n\n[QUIC]: https://en.wikipedia.org/wiki/QUIC\n[BLAKE3]: https://github.com/BLAKE3-team/BLAKE3\n[noq]: https://github.com/n0-computer/noq\n[iroh-blobs]: https://github.com/n0-computer/iroh-blobs\n[iroh-gossip]: https://github.com/n0-computer/iroh-gossip\n[iroh-docs]: https://github.com/n0-computer/iroh-docs\n[iroh-doctor]: https://github.com/n0-computer/iroh-doctor\n[willow protocol]: https://willowprotocol.org\n[iroh-ffi]: https://github.com/n0-computer/iroh-ffi\n[iroh-yt-video]: https://www.youtube.com/watch?v=RwAt36Xe3UI_\n[Iroh Examples]: https://github.com/n0-computer/iroh-examples\n[Iroh Experiments]: https://github.com/n0-computer/iroh-experiments\n[echo-rs]: /iroh/examples/echo.rs\n[iroh-perf]: https://perf.iroh.computer\n[docs]: https://docs.iroh.computer\n",
"manifest_file": "Cargo.toml",
"manifest_content": "[workspace]\nmembers = [\n \"iroh-base\",\n \"iroh-dns\",\n \"iroh-dns-server\",\n \"iroh\",\n \"iroh/bench\",\n \"iroh-relay\",\n]\nresolver = \"2\"\n\n[profile.release]\ndebug = true\n\n[profile.dev-ci]\ninherits = 'dev'\nopt-level = 1\n\n[profile.optimized-release]\ninherits = 'release'\ndebug = false\nlto = true\ndebug-assertions = false\nopt-level = 3\npanic = 'abort'\nincremental = false\n\n[workspace.lints.rust]\nmissing_debug_implementations = \"warn\"\n\n# We use this --cfg for documenting the cargo features on which an API\n# is available. To preview this locally use: RUSTDOCFLAGS=\"--cfg\n# iroh_docsrs\" cargo +nightly doc --all-features. We use our own\n# iroh_docsrs instead of the common docsrs to avoid also enabling this\n# feature in any dependencies, because some indirect dependencies\n# require a feature enabled when using `--cfg docsrs` which we can not\n# do. To enable for a crate set `#![cfg_attr(iroh_docsrs,\n# feature(doc_cfg))]` in the crate.\n# We also have our own `iroh_loom` cfg to enable tokio-rs/loom testing.\nunexpected_cfgs = { level = \"warn\", check-cfg = [\"cfg(iroh_docsrs)\", \"cfg(iroh_loom)\", \"cfg(skip_patchbay)\"] }\n\n[workspace.lints.clippy]\nunused-async = \"warn\"\n",
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{
"owner": "NanmiCoder",
"name": "MediaCrawler",
"full_name": "NanmiCoder/MediaCrawler",
"url": "https://github.com/NanmiCoder/MediaCrawler",
"description": "小红书笔记 | 评论爬虫、抖音视频 | 评论爬虫、快手视频 | 评论爬虫、B 站视频 ｜ 评论爬虫、微博帖子 ｜ 评论爬虫、百度贴吧帖子 ｜ 百度贴吧评论回复爬虫 | 知乎问答文章｜评论爬虫",
"language": "Python",
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"metadata": {
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"license": "NOASSERTION",
"open_issues": 174,
"created_at": "2023-06-09T12:14:34Z",
"pushed_at": "2026-06-18T09:22:51Z",
"homepage": "https://nanmicoder.github.io/MediaCrawler/",
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"readme_content": "# 🔥 MediaCrawler - 自媒体平台爬虫 🕷️\n\n
\n\n---\n\nhttps://github.com/user-attachments/assets/043ec09f-4bdd-41d5-aee0-8fda6b83e267\n\n**agent multiplexer that lives in your terminal.**\n\nworkspaces, tabs, panes. mouse-native: click, drag, split. every agent at a glance: blocked, working, done. detach and reattach, agents keep running. no gui app, no electron, no mac-only native wrapper. you see the agent's own terminal, not someone's interpretation of it.\n\n---\n\n## install\n\n```bash\ncurl -fsSL https://herdr.dev/install.sh | sh\n```\n\non windows preview beta:\n\n```powershell\npowershell -ExecutionPolicy Bypass -c \"irm https://herdr.dev/install.ps1 | iex\"\n```\n\nor install with homebrew:\n\n```bash\nbrew install herdr\n```\n\nor install with mise:\n\n```bash\nmise use -g herdr\n```\n\nif mise reports `herdr not found in mise tool registry`, update mise and retry. older mise versions predate the herdr registry entry; `mise use -g github:ogulcancelik/herdr` works as a temporary fallback.\n\nor download the stable Linux/macOS binary from [releases](https://github.com/ogulcancelik/herdr/releases). Native Windows binaries are preview-only beta builds.\n\n## quick start\n\nStart Herdr in the directory where the work lives:\n\n```bash\nherdr\n```\n\nHerdr starts or attaches to one background session server. When a session has no workspaces, Herdr opens one automatically. Run an agent in the root pane. Press `ctrl+b`, then `shift+n` to create another workspace, `ctrl+b`, then `v` or `minus` to split panes, `ctrl+b`, then `c` to create a tab, and `ctrl+b`, then `w` to switch workspaces.\n\nPress `ctrl+b q` to detach the client. The server and pane processes keep running. Open another terminal and run `herdr` again to reattach.\n\n## core concepts\n\n**Server and client.** By default, `herdr` attaches to a background server. Detaching closes only the client. `herdr server stop` stops the default server and kills its panes. Named sessions are separate server namespaces: use `herdr session attach work`, `herdr session stop work`, and `herdr session list` when you want fully separate runtime state.\n\n**Workspaces, tabs, panes.** A workspace is the project-level container. Tabs group panes inside a workspace. Panes are real terminal processes, not rewritten agent views.\n\n**Copy.** Herdr copies pane text, not the sidebar. Drag-select inside a pane, double-click a word or token, or press `prefix+[` for keyboard copy mode. In copy mode, move with `h/j/k/l`, `w/b/e`, and `{`/`}`, start selection with `v` or Space, copy with `y` or Enter, and leave with `q` or Esc. In PuTTY and some SSH terminals, hold `Shift` while dragging to use the terminal's own selection, and `Shift` + right click to paste.\n\n**Update and restore.** `herdr update` installs a new binary, but a running server keeps using the old process until it is stopped or handed off. Stop the old server to use the new version. Stopping exits pane processes. Run `herdr server stop`, then run `herdr` again for the default session. For a named session, run `herdr session stop `, then run `herdr session attach ` again. `herdr update --handoff` is experimental and tries to move live panes, including foreground processes such as dev servers, from the old server to the new one. With current official integrations installed, supported agent panes can restart from their native agent sessions after a server restart or update.\n\n**Keybindings.** Herdr uses explicit keybinding strings. `prefix+n` means press the configured prefix, then `n`. `ctrl+alt+n`, `cmd+k`, `alt+1`, and function-key chords are direct terminal-mode shortcuts and do not need the prefix. Plain direct printable keys such as `n` steal normal typing, so use `prefix+n` unless you intentionally want a modifier-gated direct binding.\n\n**Agent awareness.** The sidebar shows blocked, working, done, and idle states. Detection works with process names and terminal output by default. Official integrations can add native session identity for restore, semantic state reports, or both.\n\n## update\n\nHerdr notifies you when a new version is available. Run manually:\n\n```bash\nherdr update\n```\n\n`herdr update` is for installs managed by Herdr's own installer. Homebrew, mise, and Nix installs update through `brew upgrade herdr`, `mise upgrade herdr`, or your Nix workflow, then use the same stop-and-run-again flow if a session is still running the old server. Linux and macOS direct installs can opt into development preview builds with `herdr channel set preview` and return to stable with `herdr channel set stable`. Windows beta installs are preview-only for now. See [install docs](https://herdr.dev/docs/install/) and [session state docs](https://herdr.dev/docs/session-state/) for the full update, restart, restore, and handoff matrix.\n\nLinux and macOS direct installs use the stable update channel by default. Windows beta installs default to preview. To test preview builds from `master` before the next stable release:\n\n```bash\nherdr channel set preview\n```\n\nTo return Linux and macOS direct installs to stable:\n\n```bash\nherdr channel set stable\n```\n\nFor direct installs, changing channels also checks that channel and installs its latest binary. If that update fails, run `herdr update` to retry from the configured channel.\n\nPreview is only for direct installs managed by Herdr's updater. Homebrew, mise, and Nix stay on stable and update through their package managers.\n\n## how it compares\n\n| | tmux | gui managers | herdr |\n|--------------------------|------|--------------|-------|\n| persistent sessions | ✓ | — | ✓ |\n| detach / reattach | ✓ | — | ✓ |\n| panes, tabs, workspaces | ✓ | ✓ | ✓ |\n| agent awareness | — | ✓ | ✓ |\n| lives in your terminal | ✓ | — | ✓ |\n| real terminal views | ✓ | — | ✓ |\n| mouse-native | — | ✓ | ✓ |\n| lightweight binary | ✓ | — | ✓ |\n| agents can orchestrate | ? | ? | ✓ |\n\ntmux gives you persistence and panes, but it was built before agents existed. gui managers show agent state, but they make you leave your terminal and use their wrapped view. herdr is persistence and awareness in one tool that stays out of your way.\n\n## remote and attach\n\nHerdr works over normal SSH. Run it on the remote host, detach, and reattach later:\n\n```\nssh you@yourserver\nherdr\n```\n\nYou can also attach from your local terminal without opening a shell first:\n\n```bash\nherdr --remote workbox\nherdr --remote ssh://you@yourserver:2222\n```\n\nRemote attach adds fallback SSH keepalives by default while preserving your own SSH config. Set `[remote].manage_ssh_config = false` to use plain `ssh`.\n\nDirect attach connects your current terminal to one server-owned terminal:\n\n```bash\nherdr agent attach \nherdr terminal attach \n```\n\nSee [persistence and remote docs](https://herdr.dev/docs/persistence-remote/) for remote keybinding, named-session, and handoff details.\n\n## agent awareness\n\nthe sidebar shows which agents are blocked, working, or done. workspaces roll up to their most urgent state so you can scan the full list at a glance.\n\nstates:\n\n- 🔴 **blocked** — agent needs input or approval\n- 🟡 **working** — agent is actively running\n- 🔵 **done** — work finished, you have not looked at it yet\n- 🟢 **idle** — done and seen\n\ndetection works by reading foreground process and terminal output. zero config, no hooks required. official claude code, codex, github copilot cli, devin, droid, kimi code cli, qodercli, and cursor agent cli integrations provide session restore identity; pi, omp, kimi code cli, opencode, kilo code cli, hermes, and custom socket integrations can report their own state.\n\n## lives in your terminal\n\nnot a gui window, not a web dashboard, not electron. herdr runs inside whatever terminal you already use. single rust binary, no dependencies. works inside tmux as the outer terminal environment.\n\n## what you get\n\n- **workspaces** — organized around git repos or folder names, each with its own tabs and panes\n- **tabs** — first-class in the socket api and cli\n- **copy-friendly** — drag-select pane text, double-click tokens, or use keyboard copy mode with `prefix+[`, `h/j/k/l`, `{`/`}`, `v`, and `y`\n- **notifications** — sounds and toasts for background events; tab-aware suppression\n- **18 built-in themes** — catppuccin, terminal, tokyo night, gruvbox, one, solarized, kanagawa, rosé pine, vesper, and light variants for the main palettes\n- **session persistence** — pane processes survive client detach; sessions restore panes after full restart, with opt-in recent screen history\n\n## agents can use herdr too\n\nThe local Unix socket lets agents create workspaces, split or zoom panes, spawn helpers, read output, and wait for state changes. Start with the [socket API docs](https://herdr.dev/docs/socket-api/) and [`SKILL.md`](./SKILL.md).\n\n## supported agents\n\nautomatic detection works out of the box. process name matching plus terminal output heuristics.\n\n| agent | idle / done | working | blocked |\n|-------|-------------|---------|---------|\n| [pi](https://pi.dev) | ✓ | ✓ | partial |\n| [claude code](https://docs.anthropic.com/en/docs/claude-code) | ✓ | ✓ | ✓ |\n| [codex](https://github.com/openai/codex) | ✓ | ✓ | ✓ |\n| [droid](https://factory.ai) | ✓ | ✓ | ✓ |\n| [amp](https://ampcode.com) | ✓ | ✓ | ✓ |\n| [opencode](https://github.com/anomalyco/opencode) | ✓ | ✓ | ✓ |\n| [grok cli](https://x.ai/grok) | ✓ | ✓ | ✓ |\n| [hermes agent](https://github.com/NousResearch/hermes-agent) | ✓ | ✓ | ✓ |\n| [kilo code cli](https://kilo.ai/) | ✓ | ✓ | ✓ |\n| [devin cli](https://docs.devin.ai/cli) | ✓ | ✓ | ✓ |\n| cursor agent | ✓ | ✓ | ✓ |\n| antigravity cli | ✓ | ✓ | ✓ |\n| kimi code cli | ✓ | ✓ | ✓ |\n| [github copilot cli](https://github.com/features/copilot) | ✓ | ✓ | ✓ |\n| [qodercli](https://qoder.com/cli) | ✓ | ✓ | ✓ |\n| [kiro cli](https://kiro.dev/docs/cli/) | ✓ | ✓ | — |\n\ndetected but not fully tested: gemini cli, cline.\n\nfor agents outside the built-in list, herdr still works as a terminal multiplexer with workspaces, panes, and tiling. custom integrations can report agent labels over the socket api. see the [socket api docs](https://herdr.dev/docs/socket-api/).\n\n### direct integrations\n\nofficial integrations have two roles. claude code, codex, github copilot cli, devin, droid, qodercli, and cursor agent cli report session identity for native restore, while their state still comes from screen detection. pi, omp, kimi code cli, opencode, kilo code cli, and hermes report both semantic state and session identity. install with:\n\n```bash\nherdr integration install pi\nherdr integration install omp\nherdr integration install claude\nherdr integration install codex\nherdr integration install copilot\nherdr integration install devin\nherdr integration install droid\nherdr integration install kimi\nherdr integration install opencode\nherdr integration install kilo\nherdr integration install hermes\nherdr integration install qodercli\nherdr integration install cursor\n```\n\nsee the [integrations docs](https://herdr.dev/docs/integrations/) for setup details.\n\n## keybindings\n\nPress `ctrl+b` to enter prefix mode. Default actions are prefix-first and tmux-like:\n\n| key | action |\n|-----|--------|\n| `prefix+c` | new tab |\n| `prefix+n` / `prefix+p` | next / previous tab |\n| `prefix+1..9` | switch tab |\n| `prefix+w` | workspace navigation |\n| `prefix+g` | session navigator |\n| `prefix+shift+n` |",
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"readme_content": "# Handy\n\n[](https://discord.com/invite/WVBeWsNXK4)\n\n**A free, open source, and extensible speech-to-text application that works completely offline.**\n\nHandy is a cross-platform desktop application that provides simple, privacy-focused speech transcription. Press a shortcut, speak, and have your words appear in any text field. This happens on your own computer without sending any information to the cloud.\n\n## Why Handy?\n\nHandy was created to fill the gap for a truly open source, extensible speech-to-text tool. As stated on [handy.computer](https://handy.computer):\n\n- **Free**: Accessibility tooling belongs in everyone's hands, not behind a paywall\n- **Open Source**: Together we can build further. Extend Handy for yourself and contribute to something bigger\n- **Private**: Your voice stays on your computer. Get transcriptions without sending audio to the cloud\n- **Simple**: One tool, one job. Transcribe what you say and put it into a text box\n\nHandy isn't trying to be the best speech-to-text app—it's trying to be the most forkable one.\n\n## How It Works\n\n1. **Press** a configurable keyboard shortcut to start/stop recording (or use push-to-talk mode)\n2. **Speak** your words while the shortcut is active\n3. **Release** and Handy processes your speech using Whisper\n4. **Get** your transcribed text pasted directly into whatever app you're using\n\nThe process is entirely local:\n\n- Silence is filtered using VAD (Voice Activity Detection) with Silero\n- Transcription uses your choice of models:\n - **Whisper models** (Small/Medium/Turbo/Large) with GPU acceleration when available\n - **Parakeet V3** - CPU-optimized model with excellent performance and automatic language detection\n- Works on Windows, macOS, and Linux\n\n## Quick Start\n\n### Installation\n\n1. Download the latest release from the [releases page](https://github.com/cjpais/Handy/releases) or the [website](https://handy.computer)\n - **macOS**: Also available via [Homebrew cask](https://formulae.brew.sh/cask/handy): `brew install --cask handy`\n - **Windows**: Also available via [winget](https://github.com/microsoft/winget-pkgs): `winget install cjpais.Handy` \\\n **Note:** The Homebrew cask and winget package are not maintained by the Handy developers.\n2. Install the application\n3. Launch Handy and grant necessary system permissions (microphone, accessibility)\n4. Configure your preferred keyboard shortcuts in Settings\n5. Start transcribing!\n\n### Development Setup\n\nFor detailed build instructions including platform-specific requirements, see [BUILD.md](BUILD.md).\n\n## Integrations\n\n\n\nControl Handy from [Raycast](https://www.raycast.com) — start/stop recording, browse transcript history, manage dictionary, switch models and languages.\n\n[Source](https://github.com/mattiacolombomc/raycast-handy) · by [@mattiacolombomc](https://github.com/mattiacolombomc)\n\n## Architecture\n\nHandy is built as a Tauri application combining:\n\n- **Frontend**: React + TypeScript with Tailwind CSS for the settings UI\n- **Backend**: Rust for system integration, audio processing, and ML inference\n- **Core Libraries**:\n - `whisper-rs`: Local speech recognition with Whisper models\n - `transcribe-rs`: CPU-optimized speech recognition with Parakeet models\n - `cpal`: Cross-platform audio I/O\n - `vad-rs`: Voice Activity Detection\n - `rdev`: Global keyboard shortcuts and system events\n - `rubato`: Audio resampling\n\n### Debug Mode\n\nHandy includes an advanced debug mode for development and troubleshooting. Access it by pressing:\n\n- **macOS**: `Cmd+Shift+D`\n- **Windows/Linux**: `Ctrl+Shift+D`\n\n### CLI Parameters\n\nHandy supports command-line flags for controlling a running instance and customizing startup behavior. These work on all platforms (macOS, Windows, Linux).\n\n**Remote control flags** (sent to an already-running instance via the single-instance plugin):\n\n```bash\nhandy --toggle-transcription # Toggle recording on/off\nhandy --toggle-post-process # Toggle recording with post-processing on/off\nhandy --cancel # Cancel the current operation\n```\n\n**Startup flags:**\n\n```bash\nhandy --start-hidden # Start without showing the main window\nhandy --no-tray # Start without the system tray icon\nhandy --debug # Enable debug mode with verbose logging\nhandy --help # Show all available flags\n```\n\nFlags can be combined for autostart scenarios:\n\n```bash\nhandy --start-hidden --no-tray\n```\n\n> **macOS tip:** When Handy is installed as an app bundle, invoke the binary directly:\n>\n> ```bash\n> /Applications/Handy.app/Contents/MacOS/Handy --toggle-transcription\n> ```\n\n## Known Issues & Current Limitations\n\nThis project is actively being developed and has some [known issues](https://github.com/cjpais/Handy/issues). We believe in transparency about the current state:\n\n### Major Issues (Help Wanted)\n\n**Whisper Model Crashes:**\n\n- Whisper models crash on certain system configurations (Windows and Linux)\n- Does not affect all systems - issue is configuration-dependent\n - If you experience crashes and are a developer, please help to fix and provide debug logs!\n\n**Wayland Support (Linux):**\n\n- Limited support for Wayland display server\n- Requires [`wtype`](https://github.com/atx/wtype) or [`dotool`](https://sr.ht/~geb/dotool/) for text input to work correctly (see [Linux Notes](#linux-notes) below for installation)\n\n### Linux Notes\n\n**Text Input Tools:**\n\nFor reliable text input on Linux, install the appropriate tool for your display server:\n\n| Display Server | Recommended Tool | Install Command |\n| -------------- | ---------------- | -------------------------------------------------- |\n| X11 | `xdotool` | `sudo apt install xdotool` |\n| Wayland | `wtype` | `sudo apt install wtype` |\n| Both | `dotool` | `sudo apt install dotool` (requires `input` group) |\n\n- **X11**: Install `xdotool` for both direct typing and clipboard paste shortcuts\n- **Wayland**: Install `wtype` (preferred) or `dotool` for text input to work correctly\n- **dotool setup**: Requires adding your user to the `input` group: `sudo usermod -aG input $USER` (then log out and back in)\n\nWithout these tools, Handy falls back to enigo which may have limited compatibility, especially on Wayland.\n\n**Other Notes:**\n\n- **Runtime library dependency (`libgtk-layer-shell.so.0`)**:\n - Handy links `gtk-layer-shell` on Linux. If startup fails with `error while loading shared libraries: libgtk-layer-shell.so.0`, install the runtime package for your distro:\n\n | Distro | Package to install | Example command |\n | ------------- | --------------------- | -------------------------------------- |\n | Ubuntu/Debian | `libgtk-layer-shell0` | `sudo apt install libgtk-layer-shell0` |\n | Fedora/RHEL | `gtk-layer-shell` | `sudo dnf install gtk-layer-shell` |\n | Arch Linux | `gtk-layer-shell` | `sudo pacman -S gtk-layer-shell` |\n\n - For building from source on Ubuntu/Debian, you may also need `libgtk-layer-shell-dev`.\n\n- The recording overlay is disabled by default on Linux (`Overlay Position: None`) because certain compositors treat it as the active window. When the overlay is visible it can steal focus, which prevents Handy from pasting back into the application that triggered transcription. If you enable the overlay anyway, be aware that clipboard-based pasting might fail or end up in the wrong window.\n- If you are having trouble with the app, running with the environment variable `WEBKIT_DISABLE_DMABUF_RENDERER=1` may help\n- If Handy fails to start reliably on Linux, see [Troubleshooting → Linux Startup Crashes or Instability](#linux-startup-crashes-or-instability).\n- **Global keyboard shortcuts (Wayland):** On Wayland, system-level shortcuts must be configured through your desktop environment or window manager. Use the [CLI flags](#cli-parameters) as the command for your custom shortcut.\n\n **GNOME:**\n 1. Open **Settings > Keyboard > Keyboard Shortcuts > Custom Shortcuts**\n 2. Click the **+** button to add a new shortcut\n 3. Set the **Name** to `Toggle Handy Transcription`\n 4. Set the **Command** to `handy --toggle-transcription`\n 5. Click **Set Shortcut** and press your desired key combination (e.g., `Super+O`)\n\n **KDE Plasma:**\n 1. Open **System Settings > Shortcuts > Custom Shortcuts**\n 2. Click **Edit > New > Global Shortcut > Command/URL**\n 3. Name it `Toggle Handy Transcription`\n 4. In the **Trigger** tab, set your desired key combination\n 5. In the **Action** tab, set the command to `handy --toggle-transcription`\n\n **Sway / i3:**\n\n Add to your config file (`~/.config/sway/config` or `~/.config/i3/config`):\n\n ```ini\n bindsym $mod+o exec handy --toggle-transcription\n ```\n\n **Hyprland:**\n\n Add to your config file (`~/.config/hypr/hyprland.conf`):\n\n ```ini\n bind = $mainMod, O, exec, handy --toggle-transcription\n ```\n\n- You can also manage global shortcuts outside of Handy via Unix signals, which lets Wayland window managers or other hotkey daemons keep ownership of keybindings:\n\n | Signal | Action | Example |\n | --------- | ----------------------------------------- | ---------------------- |\n | `SIGUSR2` | Toggle transcription | `pkill -USR2 -n handy` |\n | `SIGUSR1` | Toggle transcription with post-processing | `pkill -USR1 -n handy` |\n\n Example Sway config:\n\n ```ini\n bindsym $mod+o exec pkill -USR2 -n handy\n bindsym $mod+p exec pkill -USR1 -n handy\n ```\n\n `pkill` here simply delivers the signal—it does not terminate the process.\n\n**Overlay & Pasting Issues (Linux):**\n\n- The recording overlay window can interfere with pasting transcribed text into target applications on Linux (X11)\n- **Solution:** Open **Settings > Advanced** and set **\"Overlay Position\"** to **\"None\"** to disable the overlay\n- Enable **\"Audio Feedback\"** (also in Advanced) if you still want audible confirmation of recording state\n- Users who upgrade from older versions or import settings from other platforms may need to manually apply this change\n\n### Platform Support\n\n- **macOS (both Intel and Apple Silicon)**\n- **x64 Windows**\n- **x64 Linux**\n\n### System Requirements/Recommendations\n\nThe following are recommendations for running Handy on your own machine. If you don't meet the system requirements, the performance of the application may be degraded. We are working on improving the performance across all kinds of computers and hardware.\n\n**For Whisper Models:**\n\n- **macOS**: M series Mac, Intel Mac\n- **Windows**: Intel, AMD, or NVIDIA GPU\n- **Linux**: Intel, AMD, or NVIDIA GPU\n - Ubuntu 22.04, 24.04\n\n**For Parakeet V3 Model:**\n\n- **CPU-only operation** - runs on a wide variety of hardware\n- **Minimum**: Intel Skylake (6th gen) or equivalent AMD processors\n- **Performance**: ~5x real-time speed on mid-range hardware (tested on i5)\n- **Automatic language detection** - no manual language selection required\n\n## Roadmap & Active Development\n\nWe're actively working on several features and improvements. Contributions and feedback are welcome!\n\n### In Progress\n\n**Debug Logging:**\n\n- Adding debug logging to a file to help diagnose issues\n\n**macOS Keyboard Improvements:**\n\n- Support for Globe key as transcription trigger\n- A rewrite of global shortcut handling for MacOS, and potentially other OS's too.\n\n**Opt-in Analytics:**\n\n- Collect anonymous usage data to help improve Handy\n- Privacy-first approach with clear opt-in\n\n**Sett",
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"readme_content": "# Hiring Agent\n\n
Resume-to-Score pipeline that extracts structured data from PDFs, enriches with GitHub signals, and outputs a fair, explainable evaluation.
\n\n---\n\n## Contents\n\n- [Overview](#overview)\n- [Architecture](#architecture)\n- [Installation and Setup](#installation-and-setup)\n - [Prerequisites](#prerequisites)\n - [Quick setup with pip](#quick-setup-with-pip)\n - [Ollama models](#ollama-models)\n- [Configuration](#configuration)\n- [How it works](#how-it-works)\n- [CLI usage](#cli-usage)\n- [Directory layout](#directory-layout)\n- [Provider details](#provider-details)\n- [Contributing](#contributing)\n- [License](#license)\n\n---\n\n## Overview\n\nHiring Agent parses a resume PDF to Markdown, extracts sectioned JSON using a local or hosted LLM, augments the data with GitHub profile and repository signals, then produces an objective evaluation with category scores, evidence, bonus points, and deductions. You can run fully local with Ollama or use Google Gemini.\n\n---\n\n## Architecture\n\n
\n
\n
\n\n**Flow**\n\n1. `pymupdf_rag.py` converts PDF pages to Markdown-like text.\n2. `pdf.py` calls the LLM per section using Jinja templates under `prompts/templates`.\n3. `github.py` fetches profile and repos, classifies projects, and asks the LLM to select the top 7.\n4. `evaluator.py` runs a strict-scored evaluation with fairness constraints.\n5. `score.py` orchestrates everything end to end and writes CSV when development mode is on.\n\n
\n
\n\n**Key modules**\n\n- `models.py`\n Pydantic schemas and LLM provider interfaces.\n\n- `llm_utils.py`\n Provider initialization and response cleanup.\n\n- `transform.py`\n Normalization from loose LLM JSON to JSON Resume style.\n\n- `prompts/`\n All Jinja templates for extraction and scoring.\n\n
\n\n# 💡 WeKnora — Turn Documents into Living Knowledge with RAG, Agents and Auto-Wiki\n\n## 📌 Overview\n\n[**WeKnora**](https://weknora.weixin.qq.com) is an open-source, LLM-powered knowledge framework built for enterprise-grade document understanding, semantic retrieval, and autonomous reasoning.\n\nIt is organized around three core capabilities: **RAG-based Quick Q&A** for everyday lookups, a **ReAct Agent** that autonomously orchestrates retrieval, MCP tools and web search to handle complex multi-step tasks, and a brand-new **Wiki Mode** in which agents distill raw documents into a self-maintaining, interlinked markdown knowledge base with an interactive knowledge graph. Combined with multi-source ingestion (Feishu / Notion / Yuque, and growing), 20+ LLM provider integrations, full Langfuse observability, **enterprise-ready multi-tenant RBAC** (4-tier role matrix + per-resource ownership + per-tenant audit log), and a fully self-hostable modular architecture, WeKnora turns scattered documents into a queryable, reasoning-capable, continuously evolving knowledge asset.\n\nThe framework supports auto-syncing knowledge from Feishu, Notion, and Yuque (more data sources coming soon), handles 10+ document formats including PDF, Word, images, and Excel, and can serve Q&A directly through IM channels like WeCom, Feishu, Slack, and Telegram. It is compatible with major LLM providers including OpenAI, DeepSeek, Qwen (Alibaba Cloud), Zhipu, Hunyuan, Gemini, MiniMax, NVIDIA, and Ollama. Its fully modular design allows swapping LLMs, vector databases, and storage backends, with support for local and private cloud deployment ensuring complete data sovereignty. WeKnora also integrates with **Langfuse** for comprehensive observability into agent reasoning, token usage, and pipeline tracing.\n\n\n## ✨ Latest Updates\n\n- **v0.6.2** — Per-upload process configuration with upload-confirm dialog; document reparse with `process_config`; `weknora` CLI v0.9 (bundled Agent Skills, `session stop`, auth/profile harmonization); KB marquee multi-select; HNSW index for 1024-dim pgvector embeddings; chat resources store refactor; Langfuse-only tracing (Jaeger removed). See [`CHANGELOG.md`](./CHANGELOG.md).\n- **v0.6.1** — Document parsing trace timeline (Langfuse-style span tree with stage-by-stage progress + stop-parse); OpenSearch vector store driver; declarative built-in models via YAML; system admin & consolidated platform settings + audit log; new-user onboarding guide; settings UI redesign; `weknora` CLI v0.7 / v0.8 (agent-first wire contract, NDJSON, `--dry-run`); OpenDataLoader + PaddleOCR-VL parsers; MCP server multi-transport (stdio / SSE / HTTP); per-model thinking-mode config; Tencent LKEAP rerank + native Gemini embeddings + MiniMax-M3. See [`CHANGELOG.md`](./CHANGELOG.md).\n- **v0.6.0** — Tenant RBAC (4-tier role matrix `Owner` / `Admin` / `Contributor` / `Viewer` + per-KB ownership + per-tenant audit log), tenant member management & multi-workspace UX, self-service workspaces; `weknora` CLI v0.4 GA with `mcp serve`; KB retrieval fan-out across vector stores; AES-256-GCM credential encryption + docreader gRPC TLS + Token; Zhipu embedder + Huawei OBS; server-side user preferences; Go 1.26.0. See [`docs/RBAC说明.md`](./docs/RBAC说明.md) and [`CHANGELOG.md`](./CHANGELOG.md).\n- **v0.5.2** — Wiki ingest scales to 40k-document KBs (task queue + DLQ); MCP human-in-the-loop tool approval; Anthropic / Apache Doris / Tencent VectorDB / KS3 / SearXNG backends; adaptive 3-tier chunking with live preview; global ⌘K command palette; Yuque connector + WeChat Mini Program; `weknora` CLI preview.\n- **v0.5.1** — Knowledge-base batch management; tenant-wide IM channels overview; session search + user-scoped pinning; unified Model / Web Search / MCP settings cards; per-agent LLM timeout; desktop tenant switching.\n- **v0.5.0** — Wiki Mode GA — agents auto-generate structured, interlinked Markdown wiki pages with a knowledge graph; wiki browser + visual graph in the UI.\n- **v0.4.0** — WeKnora Cloud (hosted LLM + parsing); Chrome Extension; ClawHub Skill; WeChat IM; attachment processing; Azure OpenAI / Alibaba OSS; Notion connector; Baidu + Ollama web search; VectorStore management.\n- **v0.3.6** — ASR (audio); Feishu data-source auto-sync; OIDC; IM quote-reply context + thread-based sessions; document summarization; Tavily search; parallel tool calling; agent @mention scope restriction.\n- **v0.3.5** — Telegram / DingTalk / Mattermost IM; IM slash commands + QA queue; suggested questions; VLM auto-describe MCP tool images; Novita AI; channel tracking.\n- **v0.3.4** — WeCom / Feishu / Slack IM; multimodal image support; NVIDIA model API; Weaviate; AWS S3; AES-256-GCM API-key encryption; built-in MCP service; hybrid-search optimization; `final_answer` tool.\n- **v0.3.3** — Parent-child chunking; KB pinning; fallback response; passage cleaning for rerank; storage auto-creation; Milvus.\n- **v0.3.2** — Knowledge Search entry; per-source parser & storage engine config; image rendering in local storage; document preview; Volcengine TOS; Mermaid rendering; batch session management; memory graph preview.\n- **v0.3.0** — Shared Space; Agent Skills + sandboxed execution; custom agents; Data Analyst agent; thinking mode; Bing / Google web search; API Key auth; Helm chart; Korean i18n; Qdrant.\n- **v0.2.0** — Agent Mode (ReACT); multi-type knowledge bases (FAQ + document); conversation strategy config; DuckDuckGo web search; MCP tool integration; new UI with agent mode switching; MQ async task management.\n\n\n## 📱 Interface Showcase\n\n
\n
\n
💬 Intelligent Q&A Conversation
\n
\n
\n
📖 Wiki Browser
\n
🕸️ Wiki Knowledge Graph
\n
\n
\n
🤖 Agent Mode · Tool Call Process
\n
⚙️ Conversation Settings
\n
\n
\n
🔭 Observability · Langfuse Tracing
\n
\n
\n\n## 🏗️ Architecture\n\n\n\nFully modular pipeline from document parsing, vectorization, and retrieval to LLM inference — every component is swappable and extensible. Supports local / private cloud deployment with full data sovereignty and a zero-barrier Web UI for quick onboarding.\n\n## 🧩 Feature Overview\n\n**Intelligent Conversation**\n\n| Capability | Details |\n|------------|---------|\n| Intelligent Reasoning | ReACT progressive multi-step reasoning, autonomously orchestrating knowledge retrieval, MCP tools, and web search; custom agent support |\n| Quick Q&A | RAG-based Q&A over knowledge bases for fast and accurate answers |\n| Wiki Mode | Agent-driven auto-generation of structured, interlinked markdown Wiki pages from raw documents |\n| Tool Calling | Built-in tools, MCP tools, web search |\n| Conversation Strategy | Online Prompt editing, retrieval threshold tuning, multi-turn context awareness |\n| Suggested Questions | Auto-generated question suggestions based on knowledge base content |\n\n**Knowledge Management**\n\n| Capability | Details |\n|------------|---------|\n| Knowledge Base Types | FAQ / Document / Wiki with folder import, URL import, tag management, and online entry |\n| Per-Upload Process Config | Override parser, chunking, multimodal (VLM / ASR), graph extraction, and question generation per upload batch via upload-confirm dialog or `process_config` API; reparse with new settings |\n| Data Source Import | Auto-sync from Feishu / Notion / Yuque (more data sources coming soon); incremental and full sync |\n| Document Formats | PDF / Word / Txt / Markdown / HTML / Images / CSV / Excel / PPT / JSON |\n| Retrieval Strategies | BM25 sparse / Dense retrieval / GraphRAG / parent-child chunking / HNSW-accelerated pgvector (1024-dim) / multi-dimensional indexing |\n| Batch Selection | Marquee drag-select multiple documents in the KB list for batch operations |\n| E2E Testing | Full-pipeline visualization with recall hit rate, BLEU / ROUGE metric evaluation |\n\n**Integrations & Extensions**\n\n| Capability | Details |\n|------------|---------|\n| LLMs | OpenAI / Azure OpenAI / Anthropic (Claude) / DeepSeek / Qwen (Alibaba Cloud) / Zhipu / Hunyuan / Doubao (Volcengine) / Gemini / MiniMax / NVIDIA / Novita AI / SiliconFlow / OpenRouter / Ollama |\n| Embeddings | Ollama / BGE / GTE / Zhipu / OpenAI-compatible APIs |\n| Vector DBs | PostgreSQL (pgvector) / Elasticsearch / OpenSearch / Milvus / Weaviate / Qdrant / Apache Doris / Tencent VectorDB |\n| Object Storage | Local / MinIO / AWS S3 / Volcengine TOS / Alibaba Cloud OSS / Kingsoft Cloud KS3 / Huawei Cloud OBS |\n| IM Channels | WeCom / Feishu / Slack / Telegram / DingTalk / Mattermost / WeChat |\n| Web Search | DuckDuckGo / Bing / Google / Tavily / Baidu / Ollama / SearXNG |\n\n**Platform**\n\n| Capability | Details |\n|------------|---------|\n| Deployment | Local / Docker / Kubernetes (Helm) with private and offline support |\n| UI | Web UI / RESTful API / CLI (`weknora`) / Chrome Extension / WeChat Mini Program |\n| Access Control | Tenant RBAC with 4-tier role matrix (Owner / Admin / Contributor / Viewer), per-KB resource ownership, per-tenant audit log, invite-only workspaces, self-service tenant creation, cross-tenant superuser |\n| Security | AES-256-GCM at-rest encryption for API keys and MCP / data-source credentials with graceful key rotation; gRPC TLS + Token between app and docreader; ",
"manifest_file": "go.mod",
"manifest_content": "module github.com/Tencent/WeKnora\n\ngo 1.26.0\n\nrequire (\n\tcodeberg.org/readeck/go-readability/v2 v2.1.2\n\tgithub.com/DATA-DOG/go-sqlmock v1.5.2\n\tgithub.com/JohannesKaufmann/html-to-markdown/v2 v2.5.1\n\tgithub.com/PuerkitoBio/goquery v1.12.0\n\tgithub.com/aliyun/alibabacloud-oss-go-sdk-v2 v1.5.1\n\tgithub.com/asg017/sqlite-vec-go-bindings v0.1.6\n\tgithub.com/aws/aws-sdk-go-v2 v1.41.7\n\tgithub.com/aws/aws-sdk-go-v2/config v1.32.17\n\tgithub.com/aws/aws-sdk-go-v2/credentials v1.19.16\n\tgithub.com/aws/aws-sdk-go-v2/service/s3 v1.101.0\n\tgithub.com/chromedp/chromedp v0.15.1\n\tgithub.com/duckdb/duckdb-go/v2 v2.10502.0\n\tgithub.com/elastic/go-elasticsearch/v7 v7.17.10\n\tgithub.com/elastic/go-elasticsearch/v8 v8.19.6\n\tgithub.com/gin-contrib/cors v1.7.7\n\tgithub.com/gin-gonic/gin v1.12.0\n\tgithub.com/go-openapi/strfmt v0.26.2\n\tgithub.com/go-sql-driver/mysql v1.10.0\n\tgithub.com/go-viper/mapstructure/v2 v2.5.0\n\tgithub.com/golang-jwt/jwt/v5 v5.3.1\n\tgithub.com/golang-migrate/migrate/v4 v4.19.1\n\tgithub.com/google/jsonschema-go v0.4.3\n\tgithub.com/google/uuid v1.6.0\n\tgithub.com/gorilla/websocket v1.5.3\n\tgithub.com/hibiken/asynq v0.26.0\n\tgithub.com/jackc/pgx/v5 v5.9.2\n\tgithub.com/joho/godotenv v1.5.1\n\tgithub.com/ks3sdklib/aws-sdk-go v1.11.0\n\tgithub.com/larksuite/oapi-sdk-go/v3 v3.6.1\n\tgithub.com/longbridgeapp/opencc v0.3.13\n\tgithub.com/mark3labs/mcp-go v0.52.0\n\tgithub.com/milvus-io/milvus/client/v2 v2.6.4\n\tgithub.com/minio/minio-go/v7 v7.1.0\n\tgithub.com/mmcdole/gofeed v1.3.0\n\tgithub.com/neo4j/neo4j-go-driver/v6 v6.0.0\n\tgithub.com/ollama/ollama v0.23.2\n\tgithub.com/open-dingtalk/dingtalk-stream-sdk-go v0.9.1\n\tgithub.com/opensearch-project/opensearch-go/v4 v4.6.0\n\tgithub.com/panjf2000/ants/v2 v2.12.0\n\tgithub.com/parquet-go/parquet-go v0.29.0\n\tgithub.com/pganalyze/pg_query_go/v6 v6.2.2\n\tgithub.com/pgvector/pgvector-go v0.3.0\n\tgithub.com/qdrant/go-client v1.18.1\n\tgithub.com/redis/go-redis/v9 v9.14.1\n\tgithub.com/robfig/cron/v3 v3.0.1\n\tgithub.com/sashabaranov/go-openai v1.41.2\n\tgithub.com/sirupsen/logrus v1.9.4\n\tgithub.com/slack-go/slack v0.23.1\n\tgithub.com/spf13/viper v1.21.0\n\tgithub.com/stretchr/testify v1.11.1\n\tgithub.com/swaggo/files v1.0.1\n\tgithub.com/swaggo/gin-swagger v1.6.1\n\tgithub.com/swaggo/swag v1.16.6\n\tgithub.com/tencent/vectordatabase-sdk-go v1.8.4\n\tgithub.com/tencentcloud/tencentcloud-sdk-go/tencentcloud/common v1.3.103\n\tgithub.com/tencentcloud/tencentcloud-sdk-go/tencentcloud/lkeap v1.3.103\n\tgithub.com/tencentyun/cos-go-sdk-v5 v0.7.73\n\tgithub.com/tiktoken-go/tokenizer v0.7.0\n\tgithub.com/volcengine/ve-tos-golang-sdk/v2 v2.9.4\n\tgithub.com/wailsapp/wails/v2 v2.12.0\n\tgithub.com/weaviate/weaviate v1.37.3\n\tgithub.com/weaviate/weaviate-go-client/v5 v5.7.3\n\tgithub.com/xuri/excelize/v2 v2.10.1\n\tgithub.com/yanyiwu/gojieba v1.4.7\n\tgo.uber.org/dig v1.19.0\n\tgolang.org/x/crypto v0.51.0\n\tgolang.org/x/mod v0.36.0\n\tgolang.org/x/net v0.54.0\n\tgolang.org/x/sync v0.20.0\n\tgolang.org/x/time v0.15.0\n\tgoogle.golang.org/api v0.278.0\n\tgoogle.golang.org/grpc v1.81.0\n\tgoogle.golang.org/protobuf v1.36.11\n\tgopkg.in/natefinch/lumberjack.v2 v2.2.1\n\tgopkg.in/yaml.v3 v3.0.1\n\tgorm.io/driver/postgres v1.6.0\n\tgorm.io/driver/sqlite v1.6.0\n\tgorm.io/gorm v1.31.1\n)\n\nrequire (\n\tcloud.google.com/go/auth v0.20.0 // indirect\n\tcloud.google.com/go/auth/oauth2adapt v0.2.8 // indirect\n\tcloud.google.com/go/compute/metadata v0.9.0 // indirect\n\tfilippo.io/edwards25519 v1.2.0 // indirect\n\tgit.sr.ht/~jackmordaunt/go-toast/v2 v2.0.3 // indirect\n\tgithub.com/JohannesKaufmann/dom v0.2.0 // indirect\n\tgithub.com/KyleBanks/depth v1.2.1 // indirect\n\tgithub.com/andybalholm/brotli v1.2.0 // indirect\n\tgithub.com/andybalholm/cascadia v1.3.3 // indirect\n\tgithub.com/apache/arrow-go/v18 v18.5.1 // indirect\n\tgithub.com/aws/aws-sdk-go-v2/aws/protocol/eventstream v1.7.10 // indirect\n\tgithub.com/aws/aws-sdk-go-v2/feature/ec2/imds v1.18.23 // indirect\n\tgithub.com/aws/aws-sdk-go-v2/internal/configsources v1.4.23 // indirect\n\tgithub.com/aws/aws-sdk-go-v2/internal/endpoints/v2 v2.7.23 // indirect\n\tgithub.com/aws/aws-sdk-go-v2/internal/v4a v1.4.24 // indirect\n\tgithub.com/aws/aws-sdk-go-v2/service/internal/accept-encoding v1.13.9 // indirect\n\tgithub.com/aws/aws-sdk-go-v2/service/internal/checksum v1.9.15 // indirect\n\tgithub.com/aws/aws-sdk-go-v2/service/internal/presigned-url v1.13.23 // indirect\n\tgithub.com/aws/aws-sdk-go-v2/service/internal/s3shared v1.19.23 // indirect\n\tgithub.com/aws/aws-sdk-go-v2/service/signin v1.0.11 // indirect\n\tgithub.com/aws/aws-sdk-go-v2/service/sso v1.30.17 // indirect\n\tgithub.com/aws/aws-sdk-go-v2/service/ssooidc v1.35.21 // indirect\n\tgithub.com/aws/aws-sdk-go-v2/service/sts v1.42.1 // indirect\n\tgithub.com/aws/smithy-go v1.25.1 // indirect\n\tgithub.com/bahlo/generic-list-go v0.2.0 // indirect\n\tgithub.com/beorn7/perks v1.0.1 // indirect\n\tgithub.com/bep/debounce v1.2.1 // indirect\n\tgithub.com/blang/semver/v4 v4.0.0 // indirect\n\tgithub.com/buger/jsonparser v1.1.2 // indirect\n\tgithub.com/bytedance/gopkg v0.1.3 // indirect\n\tgithub.com/bytedance/sonic v1.15.0 // indirect\n\tgithub.com/byteda",
"strategic_keywords": [
"agent",
"agents",
"mcp",
"rag",
"skill",
"llm",
"eval",
"vector",
"embedding"
],
"relationship_label": "Skill 来源",
"data_confidence": "high",
"evidence_sources": [
"github_trending",
"github_repo_api",
"readme",
"go.mod"
],
"score_breakdown": {
"heat": 19,
"relevance": 20,
"novelty": 15,
"productize": 14,
"adoption": 10,
"relation": 10,
"risk_signal": 8,
"total": 96
},
"strategic_score": 96
},
{
"owner": "modem-dev",
"name": "hunk",
"full_name": "modem-dev/hunk",
"url": "https://github.com/modem-dev/hunk",
"description": "Review-first terminal diff viewer for agentic coders",
"language": "TypeScript",
"total_stars": 5648,
"forks": 145,
"stars_this_period": 718,
"source_slice": "typescript",
"source_slices": [
"typescript"
],
"metadata": {
"topics": [
"cli",
"code-review",
"diff",
"git",
"tui"
],
"license": "MIT",
"open_issues": 63,
"created_at": "2026-03-17T19:16:15Z",
"pushed_at": "2026-06-24T16:51:08Z",
"homepage": "https://hunk.dev",
"default_branch": "main",
"forks": 145,
"watchers": 9,
"archived": false,
"size_kb": 4502
},
"readme_content": "# hunk\n\nHunk is a review-first terminal diff viewer for agent-authored changesets, built on [OpenTUI](https://github.com/anomalyco/opentui) and [Pierre diffs](https://www.npmjs.com/package/@pierre/diffs).\n\n[](https://github.com/modem-dev/hunk/actions/workflows/ci.yml?branch=main)\n[](https://github.com/modem-dev/hunk/releases)\n[](LICENSE)\n\n- multi-file review stream with sidebar navigation\n- inline AI and agent annotations beside the code\n- split, stack, and responsive auto layouts\n- watch mode for auto-reloading file and Git-backed reviews\n- keyboard, mouse, pager, and Git difftool support\n\n
\n
\n
\n \n \n Split view with sidebar and inline AI notes\n
\n
\n \n \n Stacked view and mouse-selectable menus\n
\n
\n
\n\n## Install\n\n```bash\nnpm i -g hunkdiff\n```\n\nOr with Homebrew:\n\n```bash\nbrew install modem-dev/tap/hunk\n```\n\nRequirements:\n\n- Node.js 18+\n- macOS, Linux, or Windows\n- Git recommended for most workflows\n\n> Nix users can use the `default` package exported in `flake.nix` instead. See [nix/README.md](./nix/README.md) for details.\n\n## Quick start\n\n```bash\nhunk # show help\nhunk --version # print the installed version\n```\n\n### Working with Git\n\nHunk mirrors Git's diff-style commands, but opens the changeset in a review UI instead of plain text.\n\n```bash\nhunk diff # review current repo changes, including untracked files\nhunk diff --watch # auto-reload as the working tree changes\nhunk show # review the latest commit\nhunk show HEAD~1 # review an earlier commit\n```\n\n### Working with Jujutsu and Sapling\n\nHunk auto-detects Jujutsu and Sapling checkouts, so `hunk diff [revset]` and `hunk show [revset]` use native revsets inside jj or Sapling workspaces. To override VCS detection, set `vcs = \"git\"` or `vcs = \"jj\"` or `vcs = \"sl\"` in [config](#config).\n\n### Working with raw files and patches\n\n```bash\nhunk diff before.ts after.ts # compare two files directly\nhunk diff before.ts after.ts --watch # auto-reload when either file changes\ngit diff --no-color | hunk patch - # review a patch from stdin\n```\n\n### Working with agents\n\n1. Open Hunk in another terminal with `hunk diff` or `hunk show`.\n2. Tell your agent to add the skill file returned by `hunk skill path`.\n3. Ask your agent to use the skill against the live Hunk session.\n\nA good generic prompt is:\n\n```text\nLoad the Hunk skill and use it for this review. Run `hunk skill path` to get the skill path.\n```\n\nFor the full live-session and `--agent-context` workflow guide, see [docs/agent-workflows.md](docs/agent-workflows.md).\n\n## Feature comparison\n\n| Capability | [hunk](https://github.com/modem-dev/hunk) | [lumen](https://github.com/jnsahaj/lumen) | [difftastic](https://github.com/Wilfred/difftastic) | [delta](https://github.com/dandavison/delta) | [diff-so-fancy](https://github.com/so-fancy/diff-so-fancy) | [diff](https://www.gnu.org/software/diffutils/) |\n| ---------------------------------- | ----------------------------------------- | ----------------------------------------- | --------------------------------------------------- | -------------------------------------------- | ---------------------------------------------------------- | ----------------------------------------------- |\n| Review-first interactive UI | ✅ | ✅ | ❌ | ❌ | ❌ | ❌ |\n| Multi-file review stream + sidebar | ✅ | ✅ | ❌ | ❌ | ❌ | ❌ |\n| Inline agent / AI annotations | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ |\n| Responsive auto split/stack layout | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ |\n| Mouse support inside the viewer | ✅ | ✅ | ❌ | ❌ | ❌ | ❌ |\n| Runtime view toggles | ✅ | ✅ | ❌ | ❌ | ❌ | ❌ |\n| Syntax highlighting | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ |\n| Structural diffing | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ |\n| Pager-compatible mode | ✅ | ❌ | ✅ | ✅ | ✅ | ✅ |\n\nHunk is optimized for reviewing a full changeset interactively.\n\n## Advanced\n\n### Config\n\nYou can persist preferences to a config file:\n\n- `~/.config/hunk/config.toml`\n- `.hunk/config.toml`\n\nExample:\n\n```toml\ntheme = \"github-dark-default\" # any built-in theme id, auto, or custom\nmode = \"auto\" # auto, split, stack\nvcs = \"git\" # git, jj, sl\nwatch = false\nexclude_untracked = false\nline_numbers = true\nwrap_lines = false\nagent_notes = false\ntransparent_background = false\n```\n\n`theme = \"auto\"` and `--theme auto` query the terminal background at startup, choose `github-light-default` for light backgrounds and `github-dark-default` for dark backgrounds, and fall back to `github-dark-default` if the terminal does not answer.\nOlder theme ids such as `graphite` and `paper` remain accepted as compatibility aliases.\n`exclude_untracked` affects Git/Sapling working-tree `hunk diff` sessions only.\n`transparent_background` can also be written as `transparentBackground`.\n\nCustom themes can inherit from any built-in theme and override only the colors you care about:\n\n```toml\ntheme = \"custom\"\n\n[custom_theme]\nbase = \"catppuccin-mocha\"\nlabel = \"My Theme\"\naccent = \"#7fd1ff\"\npanel = \"#10161d\"\nnoteBorder = \"#c49bff\"\n\n[custom_theme.syntax]\nkeyword = \"#8ed4ff\"\nstring = \"#c7b4ff\"\ncomment = \"#6e85a7\"\noperator = \"#7fd1ff\"\nvariable = \"#eef4ff\"\n```\n\nAll custom theme colors must use `#rrggbb` hex values. Press `t` in the app, or choose `View -> Themes…`, to open the theme selector.\n\n### Git integration\n\nSet Hunk as your Git pager so `git diff` and `git show` open in Hunk automatically:\n\n> [!NOTE]\n> Untracked files are auto-included only for Hunk's own `hunk diff` working-tree loader. If you open `git diff` through `hunk pager`, Git still decides the patch contents, so untracked files will not appear there.\n\n```bash\ngit config --global core.pager \"hunk pager\"\n```\n\nOr in your Git config:\n\n```ini\n[core]\n pager = hunk pager\n```\n\nIf you want to keep Git's default pager and add opt-in aliases instead:\n\n```bash\ngit config --global alias.hdiff \"-c core.pager=\\\"hunk pager\\\" diff\"\ngit config --global alias.hshow \"-c core.pager=\\\"hunk pager\\\" show\"\n```\n\n### Jujutsu pager integration\n\nTo use Hunk as jj's pager, run `jj config edit --user` and update:\n\n```toml\n[ui]\npager = [\"hunk\", \"pager\"]\ndiff-formatter = \":git\"\n```\n\n### Sapling pager integration\n\nTo use Hunk as Sapling's pager, run `sl config -u` and update:\n\n```ini\n[pager]\npager = hunk pager\n```\n\n### OpenTUI component\n\nHunk also publishes `HunkDiffView` and lower-level primitives from `hunkdiff/opentui` for embedding the same diff renderer in your own OpenTUI app.\n\nSee [docs/opentui-component.md](docs/opentui-component.md) for install, API, and runnable examples.\n\n## Examples\n\nReady-to-run demo diffs live in [`examples/`](examples/README.md).\n\nEach example includes the exact command to run from the repository root.\n\n## Contributing\n\n💬 _Chat with users/contributors on the [Modem Discord server](https://discord.gg/WZFjaP6Gt8)_\n\nFor source setup, tests, packaging checks, and repo architecture, see [CONTRIBUTING.md](CONTRIBUTING.md).\n\n## Sponsor\n\nSponsored by [Modem](https://modem.dev?utm_source=github&utm_medium=oss&utm_campaign=oss_hunk&utm_content=readme_footer).\n\n\n \n \n \n \n \n\n\n## License\n\n[MIT](LICENSE)\n",
"manifest_file": "package.json",
"manifest_content": "{\n \"name\": \"hunkdiff\",\n \"version\": \"0.16.0\",\n \"description\": \"Desktop-inspired terminal diff viewer for understanding agent-authored changesets.\",\n \"keywords\": [\n \"ai\",\n \"code-review\",\n \"diff\",\n \"git\",\n \"terminal\",\n \"tui\"\n ],\n \"homepage\": \"https://github.com/modem-dev/hunk#readme\",\n \"bugs\": {\n \"url\": \"https://github.com/modem-dev/hunk/issues\"\n },\n \"license\": \"MIT\",\n \"repository\": {\n \"type\": \"git\",\n \"url\": \"git+https://github.com/modem-dev/hunk.git\"\n },\n \"bin\": {\n \"hunk\": \"./bin/hunk.cjs\",\n \"hunkdiff\": \"./bin/hunk.cjs\"\n },\n \"workspaces\": [\n \".\",\n \"packages/*\"\n ],\n \"files\": [\n \"bin\",\n \"dist/npm\",\n \"skills\",\n \"README.md\",\n \"LICENSE\"\n ],\n \"type\": \"module\",\n \"exports\": {\n \"./opentui\": {\n \"types\": \"./dist/npm/opentui/index.d.ts\",\n \"import\": \"./dist/npm/opentui/index.js\"\n },\n \"./package.json\": \"./package.json\"\n },\n \"publishConfig\": {\n \"access\": \"public\"\n },\n \"scripts\": {\n \"start\": \"bun run src/main.tsx\",\n \"dev\": \"bun --watch src/main.tsx\",\n \"build:npm\": \"bun run ./scripts/build-npm.ts\",\n \"build:bin\": \"bun run ./scripts/build-bin.ts\",\n \"build:prebuilt:npm\": \"bun run build:npm && bun run build:bin && bun run ./scripts/stage-prebuilt-npm.ts\",\n \"build:prebuilt:artifact\": \"bun run build:bin && bun run ./scripts/build-prebuilt-artifact.ts\",\n \"stage:prebuilt:release\": \"bun run build:npm && bun run ./scripts/stage-prebuilt-npm.ts --artifact-root ./dist/release/artifacts\",\n \"install:bin\": \"bun run ./scripts/install-bin.ts\",\n \"typecheck\": \"tsc --noEmit\",\n \"format\": \"oxfmt --write .\",\n \"format:check\": \"oxfmt --check .\",\n \"lint\": \"oxlint . --deny-warnings\",\n \"lint:fix\": \"oxlint . --fix\",\n \"changeset\": \"bunx @changesets/cli@2.31.0\",\n \"changeset:status\": \"bunx @changesets/cli@2.31.0 status\",\n \"release:version\": \"bunx @changesets/cli@2.31.0 version\",\n \"prepare\": \"simple-git-hooks\",\n \"test\": \"\\\"${npm_execpath:-bun}\\\" test ./src ./packages ./scripts ./test/cli ./test/session\",\n \"test:theme-contrast\": \"bun test src/ui/themes.test.ts --test-name-pattern contrast\",\n \"test:integration\": \"\\\"${npm_execpath:-bun}\\\" test ./test/pty\",\n \"test:tty-smoke\": \"HUNK_RUN_TTY_SMOKE=1 \\\"${npm_execpath:-bun}\\\" test ./test/smoke\",\n \"check:pack\": \"bun run ./scripts/check-pack.ts\",\n \"check:prebuilt-pack\": \"bun run ./scripts/check-prebuilt-pack.ts\",\n \"smoke:prebuilt-install\": \"bun run ./scripts/smoke-prebuilt-install.ts\",\n \"publish:prebuilt:npm\": \"bun run ./scripts/publish-prebuilt-npm.ts\",\n \"update:homebrew-formula\": \"bun run ./scripts/update-homebrew-formula.ts\",\n \"prepack\": \"bun run build:npm\",\n \"bench\": \"bun run benchmarks/run.ts\",\n \"bench:release\": \"bun run ./scripts/run-release-benchmark.ts\",\n \"bench:release:compare\": \"bun run ./scripts/compare-release-benchmarks.ts\",\n \"bench:bootstrap-load\": \"bun run benchmarks/bootstrap-load.ts\",\n \"bench:working-tree-load\": \"bun run benchmarks/working-tree-load.ts\",\n \"bench:changeset-parse\": \"bun run benchmarks/changeset-parse.ts\",\n \"bench:render-layout\": \"bun run benchmarks/render-layout.ts\",\n \"bench:highlight-prefetch\": \"bun run benchmarks/highlight-prefetch.ts\",\n \"bench:large-stream\": \"bun run benchmarks/large-stream.ts\",\n \"bench:interaction-latency\": \"bun run benchmarks/interaction-latency.ts\",\n \"bench:non-ascii-stream\": \"bun run benchmarks/non-ascii-stream.ts\",\n \"bench:huge-stream\": \"bun run benchmarks/huge-stream.ts\",\n \"bench:large-stream-profile\": \"bun run benchmarks/large-stream-profile.ts\",\n \"bench:memory\": \"bun run benchmarks/memory.ts\",\n \"bench:navigation-memory\": \"bun run benchmarks/navigation-memory.ts\",\n \"bench:resize-memory\": \"bun run benchmarks/resize-memory.ts\",\n \"bench:daemon-memory\": \"bun run scripts/daemon-memory-check.ts\",\n \"bench:competitors\": \"bun run benchmarks/competitors.ts\",\n \"nix:update-lock\": \"nix run .#update-bun-lock\"\n },\n \"dependencies\": {\n \"@pierre/diffs\": \"1.2.2\",\n \"bun\": \"^1.3.10\",\n \"commander\": \"^14.0.3\",\n \"diff\": \"^8.0.3\",\n \"shell-quote\": \"1.8.4\",\n \"string-width\": \"^8.2.1\",\n \"zod\": \"^4.3.6\"\n },\n \"devDependencies\": {\n \"@hunk/session-broker\": \"workspace:*\",\n \"@hunk/session-broker-bun\": \"workspace:*\",\n \"@hunk/session-broker-core\": \"workspace:*\",\n \"@hunk/session-broker-node\": \"workspace:*\",\n \"@opentui/core\": \"^0.1.89\",\n \"@opentui/react\": \"^0.1.89\",\n \"@types/bun\": \"1.3.13\",\n \"@types/react\": \"^19.2.14\",\n \"@types/shell-quote\": \"1.7.5\",\n \"@types/ws\": \"^8.18.1\",\n \"lint-staged\": \"^16.4.0\",\n \"oxfmt\": \"^0.41.0\",\n \"oxlint\": \"^1.56.0\",\n \"react\": \"^19.2.4\",\n \"simple-git-hooks\": \"^2.13.1\",\n \"tuistory\": \"^0.0.16\",\n \"typescript\": \"^5.9.3\"\n },\n \"peerDependencies\": {\n \"@opentui/core\": \"^0.1.89\",\n \"@opentui/react\": \"^0.1.89\",\n \"react\": \"^19.2.4\"\n },\n \"simple-git-hooks\": {\n \"pre-commit\": \"bunx lint-staged\"\n },\n \"engines\": {\n \"node\": \">=18\"\n },\n \"packageManager\": \"bun@1",
"strategic_keywords": [
"agent",
"agents",
"skill",
"workspace",
"workflow"
],
"relationship_label": "Memory 组件",
"data_confidence": "high",
"evidence_sources": [
"github_trending",
"github_repo_api",
"readme",
"package.json"
],
"score_breakdown": {
"heat": 19,
"relevance": 20,
"novelty": 15,
"productize": 14,
"adoption": 10,
"relation": 10,
"risk_signal": 8,
"total": 96
},
"strategic_score": 96
},
{
"owner": "1jehuang",
"name": "jcode",
"full_name": "1jehuang/jcode",
"url": "https://github.com/1jehuang/jcode",
"description": "Coding Agent Harness",
"language": "Rust",
"total_stars": 7747,
"forks": 860,
"stars_this_period": 638,
"source_slice": "rust",
"source_slices": [
"rust"
],
"metadata": {
"topics": [
"ai",
"claude",
"cli",
"coding-agent",
"llm",
"mcp",
"openai",
"rust",
"terminal",
"tui"
],
"license": "MIT",
"open_issues": 101,
"created_at": "2026-01-05T09:43:36Z",
"pushed_at": "2026-06-25T06:38:11Z",
"homepage": "",
"default_branch": "master",
"forks": 860,
"watchers": 39,
"archived": false,
"size_kb": 433452
},
"readme_content": "
\n\n# jcode\n\n[](https://github.com/1jehuang/jcode/releases)\n[](LICENSE)\n[](https://github.com/1jehuang/jcode/releases)\n[](https://github.com/1jehuang/jcode/commits/master)\n[](https://github.com/1jehuang/jcode/stargazers)\n[](https://discord.gg/nBe9vGyK9a)\n\nThe next generation coding agent harness to raise the skill ceiling. \nBuilt for multi-session workflows, infinite customizability, and performance. \n\n \n\n\n \n\n\n \n\n[Features](#features) · [Install](#installation) · [Quick Start](#quick-start) · [Further Reading](#further-reading) · [Contributing](CONTRIBUTING.md)\n\n
\n\n---\n\n
\n\n## Installation\n\n
\n\n```bash\n# macOS & Linux\ncurl -fsSL https://raw.githubusercontent.com/1jehuang/jcode/master/scripts/install.sh | bash\n```\n\nNeed Windows, Homebrew, source builds, provider setup, or tell your agent to set it up for you?\n[Jump to detailed installation](#detailed-installation).\n\n---\n\n\n
\n\n## Performance & Resource Efficiency\n\n
\n\njcode is built to be as performant and resource efficient as possible. Every metric is optimized to the bone, which is important for scaling multi-session workflows. Here we sample a few metrics to show the difference: RAM usage and boot up.\n\n### RAM comparison\n\n
\n\n
\n
\n
\n 1 active session\n
\n \n
\n
Tool
\n
PSS
\n
Comparison
\n
\n \n \n
\n
jcode (local embedding off)
\n
27.8 MB
\n
baseline
\n
\n
\n
jcode
\n
167.1 MB
\n
6.0× more RAM
\n
\n
\n
pi
\n
144.4 MB
\n
5.2× more RAM
\n
\n
\n
Codex CLI
\n
140.0 MB
\n
5.0× more RAM
\n
\n
\n
OpenCode
\n
371.5 MB
\n
13.4× more RAM
\n
\n
\n
GitHub Copilot CLI
\n
333.3 MB
\n
12.0× more RAM
\n
\n
\n
Cursor Agent
\n
214.9 MB
\n
7.7× more RAM
\n
\n
\n
Claude Code
\n
386.6 MB
\n
13.9× more RAM
\n
\n
\n
Antigravity CLI
\n
243.7 MB
\n
8.8× more RAM
\n
\n \n
\n
\n
\n
\n 10 active sessions\n
\n \n
\n
Tool
\n
PSS
\n
Comparison
\n
\n \n \n
\n
jcode (local embedding off)
\n
117.0 MB
\n
baseline
\n
\n
\n
jcode
\n
260.8 MB
\n
2.2× more RAM
\n
\n
\n
pi
\n
833.0 MB
\n
7.1× more RAM
\n
\n
\n
Codex CLI
\n
334.8 MB
\n
2.9× more RAM
\n
\n
\n
OpenCode
\n
3237.2 MB
\n
27.7× more RAM
\n
\n
\n
GitHub Copilot CLI
\n
1756.5 MB
\n
15.0× more RAM
\n
\n
\n
Cursor Agent
\n
1632.4 MB
\n
14.0× more RAM
\n
\n
\n
Claude Code
\n
2300.6 MB
\n
19.7× more RAM
\n
\n
\n
Antigravity CLI
\n
1021.2 MB
\n
8.7× more RAM
\n
\n \n
\n
\n
\n
\n\n
\n\n### Time to first frame\n\n
\n\n| Tool | Time to first frame | Range | Comparison |\n|---|---:|---:|---:|\n| **jcode** | **14.0 ms** | 10.1–19.3 ms | baseline |\n| **Antigravity CLI** | **383.5 ms** | 363.1–415.4 ms | **27.4× slower** |\n| **pi** | **590.7 ms** | 369.6–934.8 ms | **42.2× slower** |\n| **Codex CLI** | **882.8 ms** | 742.3–1640.9 ms | **63.1× slower** |\n| **OpenCode** | **1035.9 ms** | 922.5–1104.4 ms | **74.0× slower** |\n| **GitHub Copilot CLI** | **1518.6 ms** | 1357.4–1826.8 ms | **108.5× slower** |\n| **Cursor Agent** | **1949.7 ms** | 1711.0–2104.8 ms | **139.3× slower** |\n| **Claude Code** | **3436.9 ms** | 2032.7–8927.2 ms | **245.5× slower** |\n\n
\n\nMeasured on this Linux machine across 10 interactive PTY launches.\n\n### Time to first input\n(time until typed probe text appears on the rendered screen; Antigravity uses its internal input-ready log marker because the sign-in screen suppresses probe echo.)\n
\n\n| Tool | Time to first input | Range | Comparison |\n|---|---:|---:|---:|\n| **jcode** | **48.7 ms** | 30.3–62.7 ms | baseline |\n| **Antigravity CLI** | **383.7 ms** | 363.4–415.7 ms | **7.9× slower** |\n| **pi** | **596.4 ms** | 373.9–955.2 ms | **12.2× slower** |\n| **Codex CLI** | **905.8 ms** | 760.1–1675.7 ms | **18.6× slower** |\n| **OpenCode** | **1047.9 ms** | 931.1–1116.9 ms | **21.5× slower** |\n| **GitHub Copilot CLI** | **1583.4 ms** | 1422.8–1880.0 ms | **32.5× slower** |\n| **Cursor Agent** | **1978.7 ms** | 1727.3–2130.0 ms | **40.6× slower** |\n| **Claude Code** | **3512.8 ms** | 2137.4–9002.0 ms | **72.2× slower** |\n\n
\n\nMeasured on this Linux machine across 10 interactive PTY launches. Antigravity CLI was unauthenticated for this run; its sign-in screen rendered normally and emitted an internal `CLI ready for user input` marker, but did not echo the typed probe.\n\n### Additional clients / memory scaling\n\n
\n\n| Tool | Extra PSS per added session | Comparison |\n|---|---:|---:|\n| **jcode (local embedding off)** | **~9.9 MB** | baseline |\n| **jcode** | **~10.4 MB** | **1.1× more RAM** |\n| **pi** | **~76.5 MB** | **7.7× more RAM** |\n| **Codex CLI** | **~21.6 MB** | **2.2× more RAM** |\n| **OpenCode** | **~318.4 MB** | **32.2× more RAM** |\n| **GitHub Copilot CLI** | **~158.1 MB** | **16.0× more RAM** |\n| **Cursor Agent** | **~157.5 MB** | **15.9× more RAM** |\n| **Claude Code** | **~212.7 MB** | **21.5× more RAM** |\n| **Antigravity CLI** | **~86.4 MB** | **8.7× more RAM** |\n\n
\nversions tested for this corrected memory rerun:\n\n- `jcode v0.9.1888-dev (be386f2)`\n- `pi 0.62.0`\n- `codex-cli 0.120.0`\n- `opencode 1.0.203`\n- `GitHub Copilot CLI 1.0.24` for the 1-session rerun, `GitHub Copilot CLI 1.0.27` for the 10-session rerun\n- `Cursor Agent 2026.04.08-a41fba1`\n- `Claude Code 2.1.86 (Claude Code)`\n- `Antigravity CLI 1.0.0`\n\n
\n\n\n---\n\n## Memory (Agent memory)\n\nJcode embeds each turn/response as a semantic vector. Every turn does queries a graph of memories to efficiently find related memory entries via a cosine similarity check. The embedding hits are fed into the conversation, or optionally uses a memory sideagent which verifies the memories are relevant, and potentially does more work for information retreival before injecting into the conversation. This results in a human like memory system which allows the agent to automatically recall relevant information to the conversation without actively calling memory tools or being a token burner. \not \nTo have memories which are retrieved, they must also be extracted and stored. Every so often (semantic drift, K turns since last extraction, session end, etc), memories are extracted via a memory sideagent, and put into the memory graph. \n\nThe harness also provides explicit memory tools to allow the agent to actively search or store the memory without relying on a passive background process. The harness also provides session search for traditional RAG on previous sessions. \n\nMemories are automatically consolidated every so often via the ambient mode. This reorganizes, checks for staleness and conflicts, etc\n\n
\n\n> [!Caution]\n> **Misuse Disclaimer:** \n> The developers of RustDesk do not condone or support any unethical or illegal use of this software. Misuse, such as unauthorized access, control or invasion of privacy, is strictly against our guidelines. The authors are not responsible for any misuse of the application.\n\n\nChat with us: [Discord](https://discord.gg/nDceKgxnkV) | [Twitter](https://twitter.com/rustdesk) | [Reddit](https://www.reddit.com/r/rustdesk) | [YouTube](https://www.youtube.com/@rustdesk)\n\n[](https://rustdesk.com/pricing.html)\n\nYet another remote desktop solution, written in Rust. Works out of the box with no configuration required. You have full control of your data, with no concerns about security. You can use our rendezvous/relay server, [set up your own](https://rustdesk.com/server), or [write your own rendezvous/relay server](https://github.com/rustdesk/rustdesk-server-demo).\n\n\n\nRustDesk welcomes contribution from everyone. See [CONTRIBUTING.md](docs/CONTRIBUTING.md) for help getting started.\n\n[**FAQ**](https://github.com/rustdesk/rustdesk/wiki/FAQ)\n\n[**BINARY DOWNLOAD**](https://github.com/rustdesk/rustdesk/releases)\n\n[**NIGHTLY BUILD**](https://github.com/rustdesk/rustdesk/releases/tag/nightly)\n\n[](https://f-droid.org/en/packages/com.carriez.flutter_hbb)\n[](https://flathub.org/apps/com.rustdesk.RustDesk)\n\n## Dependencies\n\nDesktop versions use Flutter or Sciter (deprecated) for GUI, this tutorial is for Sciter only, since it is easier and more friendly to start. Check out our [CI](https://github.com/rustdesk/rustdesk/blob/master/.github/workflows/flutter-build.yml) for building Flutter version.\n\nPlease download Sciter dynamic library yourself.\n\n[Windows](https://raw.githubusercontent.com/c-smile/sciter-sdk/master/bin.win/x64/sciter.dll) |\n[Linux](https://raw.githubusercontent.com/c-smile/sciter-sdk/master/bin.lnx/x64/libsciter-gtk.so) |\n[macOS](https://raw.githubusercontent.com/c-smile/sciter-sdk/master/bin.osx/libsciter.dylib)\n\n## Raw Steps to build\n\n- Prepare your Rust development env and C++ build env\n\n- Install [vcpkg](https://github.com/microsoft/vcpkg), and set `VCPKG_ROOT` env variable correctly\n\n - Windows: vcpkg install libvpx:x64-windows-static libyuv:x64-windows-static opus:x64-windows-static aom:x64-windows-static\n - Linux/macOS: vcpkg install libvpx libyuv opus aom\n\n- run `cargo run`\n\n## [Build](https://rustdesk.com/docs/en/dev/build/)\n\n## How to Build on Linux\n\n### Ubuntu 18 (Debian 10)\n\n```sh\nsudo apt install -y zip g++ gcc git curl wget nasm yasm libgtk-3-dev clang libxcb-randr0-dev libxdo-dev \\\n libxfixes-dev libxcb-shape0-dev libxcb-xfixes0-dev libasound2-dev libpulse-dev cmake make \\\n libclang-dev ninja-build libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev libpam0g-dev\n```\n\n### openSUSE Tumbleweed\n\n```sh\nsudo zypper install gcc-c++ git curl wget nasm yasm gcc gtk3-devel clang libxcb-devel libXfixes-devel cmake alsa-lib-devel gstreamer-devel gstreamer-plugins-base-devel xdotool-devel pam-devel\n```\n\n### Fedora 28 (CentOS 8)\n\n```sh\nsudo yum -y install gcc-c++ git curl wget nasm yasm gcc gtk3-devel clang libxcb-devel libxdo-devel libXfixes-devel pulseaudio-libs-devel cmake alsa-lib-devel gstreamer1-devel gstreamer1-plugins-base-devel pam-devel\n```\n\n### Arch (Manjaro)\n\n```sh\nsudo pacman -Syu --needed unzip git cmake gcc curl wget yasm nasm zip make pkg-config clang gtk3 xdotool libxcb libxfixes alsa-lib pipewire\n```\n\n### Install vcpkg\n\n```sh\ngit clone https://github.com/microsoft/vcpkg\ncd vcpkg\ngit checkout 2023.04.15\ncd ..\nvcpkg/bootstrap-vcpkg.sh\nexport VCPKG_ROOT=$HOME/vcpkg\nvcpkg/vcpkg install libvpx libyuv opus aom\n```\n\n### Fix libvpx (For Fedora)\n\n```sh\ncd vcpkg/buildtrees/libvpx/src\ncd *\n./configure\nsed -i 's/CFLAGS+=-I/CFLAGS+=-fPIC -I/g' Makefile\nsed -i 's/CXXFLAGS+=-I/CXXFLAGS+=-fPIC -I/g' Makefile\nmake\ncp libvpx.a $HOME/vcpkg/installed/x64-linux/lib/\ncd\n```\n\n### Build\n\n```sh\ncurl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh\nsource $HOME/.cargo/env\ngit clone --recurse-submodules https://github.com/rustdesk/rustdesk\ncd rustdesk\nmkdir -p target/debug\nwget https://raw.githubusercontent.com/c-smile/sciter-sdk/master/bin.lnx/x64/libsciter-gtk.so\nmv libsciter-gtk.so target/debug\nVCPKG_ROOT=$HOME/vcpkg cargo run\n```\n\n## How to build with Docker\n\nBegin by cloning the repository and building the Docker container:\n\n```sh\ngit clone https://github.com/rustdesk/rustdesk\ncd rustdesk\ngit submodule update --init --recursive\ndocker build -t \"rustdesk-builder\" .\n```\n\nThen, each time you need to build the application, run the following command:\n\n```sh\ndocker run --rm -it -v $PWD:/home/user/rustdesk -v rustdesk-git-cache:/home/user/.cargo/git -v rustdesk-registry-cache:/home/user/.cargo/registry -e PUID=\"$(id -u)\" -e PGID=\"$(id -g)\" rustdesk-builder\n```\n\nNote that the first build may take longer before dependencies are cached, subsequent builds will be faster. Additionally, if you need to specify different arguments to the build command, you may do so at the end of the command in the `` position. For instance, if you wanted to build an optimized release version, you would run the command above followed by `--release`. The resulting executable will be available in the target folder on your system, and can be run with:\n\n```sh\ntarget/debug/rustdesk\n```\n\nOr, if you're running a release executable:\n\n```sh\ntarget/release/rustdesk\n```\n\nPlease ensure that you run these commands from the root of the RustDesk repository, or the application may not find the required resources. Also note that other cargo subcommands such as `install` or `run` are not currently supported via this method as they would install or run the program inside the container instead of the host.\n\n## File Structure\n\n- **[libs/hbb_common](https://github.com/rustdesk/rustdesk/tree/master/libs/hbb_common)**: video codec, config, tcp/udp wrapper, protobuf, fs functions for file transfer, and some other utility functions\n- **[libs/scrap](https://github.com/rustdesk/rustdesk/tree/master/libs/scrap)**: screen capture\n- **[libs/enigo](https://github.com/rustdesk/rustdesk/tree/master/libs/enigo)**: platform specific keyboard/mouse control\n- **[libs/clipboard](https://github.com/rustdesk/rustdesk/tree/master/libs/clipboard)**: file copy and paste implementation for Windows, Linux, macOS.\n- **[src/ui](https://github.com/rustdesk/rustdesk/tree/master/src/ui)**: obsolete Sciter UI (deprecated)\n- **[src/server](https://github.com/rustdesk/rustdesk/tree/master/src/server)**: audio/clipboard/input/video services, and network connections\n- **[src/client.rs](https://github.com/rustdesk/rustdesk/tree/master/src/client.rs)**: start a peer connection\n- **[src/rendezvous_mediator.rs](https://github.com/rustdesk/rustdesk/tree/master/src/rendezvous_mediator.rs)**: Communicate with [rustdesk-server](https://github.com/rustdesk/rustdesk-server), wait for remote direct (TCP hole punching) or relayed connection\n- **[src/platform](https://github.com/rustdesk/rustdesk/tree/master/src/platform)**: platform specific code\n- **[flutter](https://github.com/rustdesk/rustdesk/tree/master/flutter)**: Flutter code for desktop and mobile\n- **[flutter/web/js](https://github.com/rustdesk/rustdesk/tree/master/flutter/web/v1/js)**: JavaScript for Flutter web client\n\n## Screenshots\n\n\n\n\n\n\n\n\n\n",
"manifest_file": "Cargo.toml",
"manifest_content": "[package]\nname = \"rustdesk\"\nversion = \"1.4.8\"\nauthors = [\"rustdesk \"]\nedition = \"2021\"\nbuild= \"build.rs\"\ndescription = \"RustDesk Remote Desktop\"\ndefault-run = \"rustdesk\"\nrust-version = \"1.75\"\n\n[lib]\nname = \"librustdesk\"\ncrate-type = [\"cdylib\", \"staticlib\", \"rlib\"]\n\n[[bin]]\nname = \"naming\"\npath = \"src/naming.rs\"\n\n[[bin]]\nname = \"service\"\npath = \"src/service.rs\"\n\n[features]\ninline = []\ncli = []\nuse_samplerate = [\"samplerate\"]\nuse_rubato = [\"rubato\"]\nuse_dasp = [\"dasp\"]\nflutter = [\"flutter_rust_bridge\"]\ndefault = [\"use_dasp\"]\nhwcodec = [\"scrap/hwcodec\"]\nvram = [\"scrap/vram\"]\nmediacodec = [\"scrap/mediacodec\"]\nplugin_framework = []\nlinux-pkg-config = [\"magnum-opus/linux-pkg-config\", \"scrap/linux-pkg-config\"]\nunix-file-copy-paste = [\n \"dep:x11-clipboard\",\n \"dep:x11rb\",\n \"dep:percent-encoding\",\n \"dep:once_cell\",\n \"clipboard/unix-file-copy-paste\",\n]\nscreencapturekit = [\"cpal/screencapturekit\"]\n\n# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html\n\n[dependencies]\nasync-trait = \"0.1\"\nscrap = { path = \"libs/scrap\", features = [\"wayland\"] }\nhbb_common = { path = \"libs/hbb_common\" }\nserde_derive = \"1.0\"\nserde = \"1.0\"\nserde_json = \"1.0\"\nserde_repr = \"0.1\"\ncfg-if = \"1.0\"\nlazy_static = \"1.4\"\nsha2 = \"0.10\"\nrepng = \"0.2\"\nparity-tokio-ipc = { git = \"https://github.com/rustdesk-org/parity-tokio-ipc\" }\nmagnum-opus = { git = \"https://github.com/rustdesk-org/magnum-opus\" }\ndasp = { version = \"0.11\", features = [\"signal\", \"interpolate-linear\", \"interpolate\"], optional = true }\nrubato = { version = \"0.12\", optional = true }\nsamplerate = { version = \"0.2\", optional = true }\nuuid = { version = \"1.3\", features = [\"v4\"] }\nclap = \"4.2\"\nrpassword = \"7.2\"\nnum_cpus = \"1.15\"\nbytes = { version = \"1.4\", features = [\"serde\"] }\ndefault-net = \"0.14\"\nwol-rs = \"1.0\"\nflutter_rust_bridge = { version = \"=1.80\", features = [\"uuid\"], optional = true}\nerrno = \"0.3\"\nrdev = { git = \"https://github.com/rustdesk-org/rdev\" }\nurl = { version = \"2.3\", features = [\"serde\"] }\ncrossbeam-queue = \"0.3\"\nhex = \"0.4\"\nchrono = \"0.4\"\ncidr-utils = \"0.5\"\nfon = \"0.6\"\nzip = \"0.6\"\nshutdown_hooks = \"0.1\"\ntotp-rs = { version = \"5.4\", default-features = false, features = [\"gen_secret\", \"otpauth\"] }\nstunclient = \"0.4\"\nkcp-sys= { git = \"https://github.com/rustdesk-org/kcp-sys\"}\nreqwest = { version = \"0.12\", features = [\"blocking\", \"socks\", \"json\", \"native-tls\", \"rustls-tls\", \"rustls-tls-native-roots\", \"gzip\"], default-features=false }\n\n[target.'cfg(not(target_os = \"linux\"))'.dependencies]\n# https://github.com/rustdesk/rustdesk/discussions/10197, not use cpal on linux\ncpal = { git = \"https://github.com/rustdesk-org/cpal\", branch = \"osx-screencapturekit\" }\nringbuf = \"0.3\"\n\n[target.'cfg(not(any(target_os = \"android\", target_os = \"ios\")))'.dependencies]\nmac_address = \"1.1\"\nsciter-rs = { git = \"https://github.com/rustdesk-org/rust-sciter\", branch = \"dyn\" }\nsys-locale = \"0.3\"\nenigo = { path = \"libs/enigo\", features = [ \"with_serde\" ] }\nclipboard = { path = \"libs/clipboard\" }\nctrlc = \"3.2\"\n# arboard = { version = \"3.4\", features = [\"wayland-data-control\"] }\narboard = { git = \"https://github.com/rustdesk-org/arboard\", features = [\"wayland-data-control\"] }\nclipboard-master = { git = \"https://github.com/rustdesk-org/clipboard-master\" }\nportable-pty = { git = \"https://github.com/rustdesk-org/wezterm\", branch = \"rustdesk/pty_based_0.8.1\", package = \"portable-pty\" }\n\nsystem_shutdown = \"4.0\"\nqrcode-generator = \"4.1\"\n\n[target.'cfg(target_os = \"windows\")'.dependencies]\nwinapi = { version = \"0.3\", features = [\n \"winuser\",\n \"wincrypt\",\n \"shellscalingapi\",\n \"pdh\",\n \"synchapi\",\n \"memoryapi\",\n \"shellapi\",\n \"devguid\",\n \"setupapi\",\n \"cguid\",\n \"cfgmgr32\",\n \"ioapiset\",\n \"winspool\",\n] }\nwindows = { version = \"0.61\", features = [\n \"Win32\",\n \"Win32_Foundation\",\n \"Win32_Security\",\n \"Win32_Security_Authorization\",\n \"Win32_Storage_FileSystem\",\n \"Win32_System\",\n \"Win32_System_Diagnostics\",\n \"Win32_System_Diagnostics_ToolHelp\",\n \"Win32_System_Environment\",\n \"Win32_System_IO\",\n \"Win32_System_Memory\",\n \"Win32_System_Pipes\",\n \"Win32_System_Threading\",\n \"Win32_UI_Shell\",\n] }\nwinreg = \"0.11\"\nwindows-service = \"0.6\"\nvirtual_display = { path = \"libs/virtual_display\" }\nremote_printer = { path = \"libs/remote_printer\" }\nimpersonate_system = { git = \"https://github.com/rustdesk-org/impersonate-system\" }\nshared_memory = \"0.12\"\ntauri-winrt-notification = \"0.1\"\nrunas = \"1.2\"\n\n[target.'cfg(target_os = \"macos\")'.dependencies]\nobjc = \"0.2\"\ncocoa = \"0.24\"\ndispatch = \"0.2\"\ncore-foundation = \"0.9\"\ncore-graphics = \"0.22\"\ninclude_dir = \"0.7\"\nfruitbasket = \"0.10\"\nobjc_id = \"0.1\"\n# If we use piet \"0.7\" here, we must also update core-graphics to \"0.24\".\npiet = \"0.6\"\npiet-coregraphics = \"0.6\"\nforeign-types = \"0.3\"\n\n[target.'cfg(any(target_os = \"macos\", target_os = \"linux\", target_os = \"windows\"))'.dependencies]\ntray-icon = { git = \"https://github.com/tauri-apps/tray-icon\", version ",
"strategic_keywords": [
"workflow"
],
"relationship_label": "Skill 来源",
"data_confidence": "high",
"evidence_sources": [
"github_trending",
"github_repo_api",
"readme",
"Cargo.toml"
],
"score_breakdown": {
"heat": 19,
"relevance": 8,
"novelty": 8,
"productize": 14,
"adoption": 10,
"relation": 7,
"risk_signal": 8,
"total": 74
},
"strategic_score": 74
},
{
"owner": "Lightricks",
"name": "LTX-2",
"full_name": "Lightricks/LTX-2",
"url": "https://github.com/Lightricks/LTX-2",
"description": "Official Python inference and LoRA trainer package for the LTX-2 audio–video generative model.",
"language": "Python",
"total_stars": 7936,
"forks": 1257,
"stars_this_period": 581,
"source_slice": "python",
"source_slices": [
"python"
],
"metadata": {
"topics": [
"generative-ai",
"ltx",
"ltx-2"
],
"license": "NOASSERTION",
"open_issues": 96,
"created_at": "2026-01-03T13:16:29Z",
"pushed_at": "2026-06-17T14:26:42Z",
"homepage": "https://ltx.io/model/ltx-2",
"default_branch": "main",
"forks": 1257,
"watchers": 81,
"archived": false,
"size_kb": 1868
},
"readme_content": "# LTX-2\n\n[](https://ltx.io)\n[](https://huggingface.co/Lightricks/LTX-2.3)\n[](https://console.ltx.video/playground)\n[](https://arxiv.org/abs/2601.03233)\n[](https://discord.gg/ltxplatform)\n\n**LTX-2** is the first DiT-based audio-video foundation model that contains all core capabilities of modern video generation in one model: synchronized audio and video, high fidelity, multiple performance modes, production-ready outputs, API access, and open access.\n\n
\n \n
\n\n## 🚀 Quick Start\n\n```bash\n# Clone the repository\ngit clone https://github.com/Lightricks/LTX-2.git\ncd LTX-2\n\n# Set up the environment\nuv sync --frozen\nsource .venv/bin/activate\n```\n\n### Required Models\n\nDownload the following models from the [LTX-2.3 HuggingFace repository](https://huggingface.co/Lightricks/LTX-2.3):\n\n**LTX-2.3 Model Checkpoint** (choose and download one of the following)\n * [`ltx-2.3-22b-dev.safetensors`](https://huggingface.co/Lightricks/LTX-2.3/blob/main/ltx-2.3-22b-dev.safetensors) - [Download](https://huggingface.co/Lightricks/LTX-2.3/resolve/main/ltx-2.3-22b-dev.safetensors)\n * [`ltx-2.3-22b-distilled-1.1.safetensors`](https://huggingface.co/Lightricks/LTX-2.3/blob/main/ltx-2.3-22b-distilled-1.1.safetensors) - [Download](https://huggingface.co/Lightricks/LTX-2.3/resolve/main/ltx-2.3-22b-distilled-1.1.safetensors)\n\n**Spatial Upscaler** - Required for current two-stage pipeline implementations in this repository\n * [`ltx-2.3-spatial-upscaler-x2-1.1.safetensors`](https://huggingface.co/Lightricks/LTX-2.3/blob/main/ltx-2.3-spatial-upscaler-x2-1.1.safetensors) - [Download](https://huggingface.co/Lightricks/LTX-2.3/resolve/main/ltx-2.3-spatial-upscaler-x2-1.1.safetensors)\n * [`ltx-2.3-spatial-upscaler-x1.5-1.0.safetensors`](https://huggingface.co/Lightricks/LTX-2.3/blob/main/ltx-2.3-spatial-upscaler-x1.5-1.0.safetensors) - [Download](https://huggingface.co/Lightricks/LTX-2.3/resolve/main/ltx-2.3-spatial-upscaler-x1.5-1.0.safetensors)\n\n**Temporal Upscaler** - Supported by the model and will be required for future pipeline implementations\n * [`ltx-2.3-temporal-upscaler-x2-1.0.safetensors`](https://huggingface.co/Lightricks/LTX-2.3/blob/main/ltx-2.3-temporal-upscaler-x2-1.0.safetensors) - [Download](https://huggingface.co/Lightricks/LTX-2.3/resolve/main/ltx-2.3-temporal-upscaler-x2-1.0.safetensors)\n\n**Distilled LoRA** - Required for current two-stage pipeline implementations in this repository (except DistilledPipeline, ICLoraPipeline, and LipDubPipeline)\n * [`ltx-2.3-22b-distilled-lora-384-1.1.safetensors`](https://huggingface.co/Lightricks/LTX-2.3/blob/main/ltx-2.3-22b-distilled-lora-384-1.1.safetensors) - [Download](https://huggingface.co/Lightricks/LTX-2.3/resolve/main/ltx-2.3-22b-distilled-lora-384-1.1.safetensors)\n\n**Gemma Text Encoder** (download all assets from the repository)\n * [`Gemma 3`](https://huggingface.co/google/gemma-3-12b-it-qat-q4_0-unquantized/tree/main)\n\n**LoRAs**\n * [`LTX-2.3-22b-IC-LoRA-Union-Control`](https://huggingface.co/Lightricks/LTX-2.3-22b-IC-LoRA-Union-Control) - [Download](https://huggingface.co/Lightricks/LTX-2.3-22b-IC-LoRA-Union-Control/resolve/main/ltx-2.3-22b-ic-lora-union-control-ref0.5.safetensors)\n * [`LTX-2.3-22b-IC-LoRA-Motion-Track-Control`](https://huggingface.co/Lightricks/LTX-2.3-22b-IC-LoRA-Motion-Track-Control) - [Download](https://huggingface.co/Lightricks/LTX-2.3-22b-IC-LoRA-Motion-Track-Control/resolve/main/ltx-2.3-22b-ic-lora-motion-track-control-ref0.5.safetensors)\n * [`LTX-2-19b-IC-LoRA-Detailer`](https://huggingface.co/Lightricks/LTX-2-19b-IC-LoRA-Detailer) - [Download](https://huggingface.co/Lightricks/LTX-2-19b-IC-LoRA-Detailer/resolve/main/ltx-2-19b-ic-lora-detailer.safetensors)\n * [`LTX-2-19b-IC-LoRA-Pose-Control`](https://huggingface.co/Lightricks/LTX-2-19b-IC-LoRA-Pose-Control) - [Download](https://huggingface.co/Lightricks/LTX-2-19b-IC-LoRA-Pose-Control/resolve/main/ltx-2-19b-ic-lora-pose-control.safetensors)\n * [`LTX-2-19b-LoRA-Camera-Control-Dolly-In`](https://huggingface.co/Lightricks/LTX-2-19b-LoRA-Camera-Control-Dolly-In) - [Download](https://huggingface.co/Lightricks/LTX-2-19b-LoRA-Camera-Control-Dolly-In/resolve/main/ltx-2-19b-lora-camera-control-dolly-in.safetensors)\n * [`LTX-2-19b-LoRA-Camera-Control-Dolly-Left`](https://huggingface.co/Lightricks/LTX-2-19b-LoRA-Camera-Control-Dolly-Left) - [Download](https://huggingface.co/Lightricks/LTX-2-19b-LoRA-Camera-Control-Dolly-Left/resolve/main/ltx-2-19b-lora-camera-control-dolly-left.safetensors)\n * [`LTX-2-19b-LoRA-Camera-Control-Dolly-Out`](https://huggingface.co/Lightricks/LTX-2-19b-LoRA-Camera-Control-Dolly-Out) - [Download](https://huggingface.co/Lightricks/LTX-2-19b-LoRA-Camera-Control-Dolly-Out/resolve/main/ltx-2-19b-lora-camera-control-dolly-out.safetensors)\n * [`LTX-2-19b-LoRA-Camera-Control-Dolly-Right`](https://huggingface.co/Lightricks/LTX-2-19b-LoRA-Camera-Control-Dolly-Right) - [Download](https://huggingface.co/Lightricks/LTX-2-19b-LoRA-Camera-Control-Dolly-Right/resolve/main/ltx-2-19b-lora-camera-control-dolly-right.safetensors)\n * [`LTX-2-19b-LoRA-Camera-Control-Jib-Down`](https://huggingface.co/Lightricks/LTX-2-19b-LoRA-Camera-Control-Jib-Down) - [Download](https://huggingface.co/Lightricks/LTX-2-19b-LoRA-Camera-Control-Jib-Down/resolve/main/ltx-2-19b-lora-camera-control-jib-down.safetensors)\n * [`LTX-2-19b-LoRA-Camera-Control-Jib-Up`](https://huggingface.co/Lightricks/LTX-2-19b-LoRA-Camera-Control-Jib-Up) - [Download](https://huggingface.co/Lightricks/LTX-2-19b-LoRA-Camera-Control-Jib-Up/resolve/main/ltx-2-19b-lora-camera-control-jib-up.safetensors)\n * [`LTX-2-19b-LoRA-Camera-Control-Static`](https://huggingface.co/Lightricks/LTX-2-19b-LoRA-Camera-Control-Static) - [Download](https://huggingface.co/Lightricks/LTX-2-19b-LoRA-Camera-Control-Static/resolve/main/ltx-2-19b-lora-camera-control-static.safetensors)\n * [`LTX-2.3-22b-IC-LoRA-HDR`](https://huggingface.co/Lightricks/LTX-2.3-22b-IC-LoRA-HDR) - HDR IC-LoRA and pre-computed text embeddings for `HDRICLoraPipeline`\n * [`LTX-2.3-22b-IC-LoRA-LipDub`](https://huggingface.co/Lightricks/LTX-2.3-22b-IC-LoRA-LipDub) - [Download](https://huggingface.co/Lightricks/LTX-2.3-22b-IC-LoRA-LipDub/resolve/main/ltx-2.3-22b-ic-lora-lipdub-0.9.safetensors)\n\n### Available Pipelines\n\n* **[TI2VidTwoStagesPipeline](packages/ltx-pipelines/src/ltx_pipelines/ti2vid_two_stages.py)** - Production-quality text/image-to-video with 2x upsampling (recommended)\n* **[TI2VidTwoStagesHQPipeline](packages/ltx-pipelines/src/ltx_pipelines/ti2vid_two_stages_hq.py)** - Same two-stage flow as above but uses the res_2s second-order sampler (fewer steps, better quality)\n* **[TI2VidOneStagePipeline](packages/ltx-pipelines/src/ltx_pipelines/ti2vid_one_stage.py)** - Single-stage generation for quick prototyping\n* **[DistilledPipeline](packages/ltx-pipelines/src/ltx_pipelines/distilled.py)** - Fastest inference with 8 predefined sigmas\n* **[ICLoraPipeline](packages/ltx-pipelines/src/ltx_pipelines/ic_lora.py)** - Video-to-video and image-to-video transformations (uses distilled model.)\n* **[KeyframeInterpolationPipeline](packages/ltx-pipelines/src/ltx_pipelines/keyframe_interpolation.py)** - Interpolate between keyframe images\n* **[A2VidPipelineTwoStage](packages/ltx-pipelines/src/ltx_pipelines/a2vid_two_stage.py)** - Audio-to-video generation conditioned on an input audio file\n* **[RetakePipeline](packages/ltx-pipelines/src/ltx_pipelines/retake.py)** - Regenerate a specific time region of an existing video\n* **[HDRICLoraPipeline](packages/ltx-pipelines/src/ltx_pipelines/hdr_ic_lora.py)** - Video-to-video with HDR output (linear float frames via LogC3 inverse decode, suitable for EXR export and tonemapping)\n* **[LipDubPipeline](packages/ltx-pipelines/src/ltx_pipelines/lipdub.py)** - Lip dubbing, rephrasing, matching speaker identity (distilled model, single IC-LoRA, Two stages).\n\n### ⚡ Optimization Tips\n\n* **Use DistilledPipeline** - Fastest inference with only 8 predefined sigmas (8 steps stage 1, 4 steps stage 2)\n* **Enable FP8 quantization** - Enables lower memory footprint: `--quantization fp8-cast` (CLI) or `quantization=QuantizationPolicy.fp8_cast()` (Python). Fp8-cast should be used with bf16 checkpoints, it shall downcast them on the fly. For Hopper GPUs with TensorRT-LLM, use `--quantization fp8-scaled-mm` for FP8 scaled matrix multiplication. Fp8-scaled-mm should be used with fp8 checkpoints.\n* **Install attention optimizations** - On datacenter Blackwell GPUs (B200), install FlashAttention 4 manually: `uv pip install 'flash-attn-4==4.0.0b9'` (this specific revision is the one we have verified against torch 2.9.1+cu128; newer betas have known issues on consumer Blackwell). On other CUDA GPUs (including Hopper), use xFormers (`uv sync --extra xformers`).\n* **Use gradient estimation** - Reduce inference steps from 40 to 20-30 while maintaining quality (see [pipeline documentation](packages/ltx-pipelines/README.md#denoising-loop-optimization))\n* **Skip memory cleanup** - If you have sufficient VRAM, disable automatic memory cleanup between stages for faster processing\n* **Choose single-stage pipeline** - Use `TI2VidOneStagePipeline` for faster generation when high resolution isn't required\n\n## ✍️ Prompting for LTX-2\n\nWhen writing prompts, focus on detailed, chronological descriptions of actions and scenes. Include specific movements, appearances, camera angles, and environmental details - all in a single flowing paragraph. Start directly with the action, and keep descriptions literal and precise. Think like a cinematographer describing a shot list. Keep within 200 words. For best results, build your prompts using this structure:\n\n- Start with main action in a single sentence\n- Add specific details about movements and gestures\n- Describe character/object appearances precisely\n- Include background and environment details\n- Specify camera angles and movements\n- Describe lighting and colors\n- Note any changes or sudden events\n\nFor additional guidance on writing a prompt please refer to \n\n### Automatic Prompt Enhancement\n\nLTX-2 pipelines support automatic prompt enhancement via an `enhance_prompt` parameter.\n\n## 🔌 ComfyUI Integration\n\nTo use our model with ComfyUI, please follow the instructions at .\n\n## 📦 Packages\n\nThis reposit",
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\n
\n \n
\n
\n A KV Cache Management Layer for Scalable LLM Inference\n
\n\n## Updates\n- [2026/05] 🔥 Agentic workload benchmark on AMD MI300X ([blog](https://blog.lmcache.ai/en/2026/05/12/benchmarking-lmcache-for-multi-turn-agentic-workloads-on-amd-mi300x/)).\n- [2026/04] 🔥 LMCache's new multiprocess (MP) architecture release ([blog](https://blog.lmcache.ai/en/2026/04/03/lmcaches-new-architecture-boosts-moe-inference-performance-by-10x/)).\n- [2026/03] LMCache at GTC 2026 ([post](https://www.linkedin.com/posts/lmcache-lab_llm-opensource-nvidiagtc-activity-7442721875664826369-pMAu?utm_source=share&utm_medium=member_desktop&rcm=ACoAADkIIvQBTyG53kXXX70OZdE5rhpllYQqmIA)).\n- [2026/01] LMCache multi-node P2P CPU memory sharing, from experimental feature to production ([blog](https://blog.lmcache.ai/en/2026/01/21/p2p-1/)).\n\n\nMore\n\n- [2025/11] LMCache x CoreWeave accelerate efficient LLM inference for Cohere ([blog](https://blog.lmcache.ai/en/2025/10/29/breaking-the-memory-barrier-how-lmcache-and-coreweave-power-efficient-llm-inference-for-cohere/)).\n- [2025/10] LMCache joins the PyTorch Foundation and Tensormesh unveiled ([blog](https://blog.lmcache.ai/en/2025/10/31/tensormesh-unveiled-and-lmcache-joins-the-pytorch-foundation/), [PyTorch](https://pytorch.org/blog/lmcache-joins-pytorch-ecosystem/)).\n- [2025/09] NVIDIA Dynamo integrates LMCache, accelerating LLM inference ([blog](https://blog.lmcache.ai/en/2025/09/18/nvidia-dynamo-integrates-lmcache-accelerating-llm-inference/)).\n- [2025/08] 🎉 LMCache hits 5,000+ GitHub stars ([blog](https://blog.lmcache.ai/en/2025/08/28/%f0%9f%8e%89-lmcache-hits-5000-github-stars-thank-you-community/)).\n- [2025/08] LMCache supports gpt-oss (20B/120B) on day 1 ([blog](https://blog.lmcache.ai/en/2025/08/05/lmcache-supports-gpt-oss-20b-120b-on-day-1/)).\n- [2025/07] Get faster LLM inference and cheaper responses with LMCache and Redis ([Redis blog](https://redis.io/blog/get-faster-llm-inference-and-cheaper-responses-with-lmcache-and-redis/)).\n- [2025/07] LMCache extends its turbo-boost to multimodal models in vLLM V1 ([blog](https://blog.lmcache.ai/en/2025/07/03/lmcache-extends-its-turbo-boost-to-multimodal-models-in-vllm-v1/)).\n- [2025/06] LLM Production Stack goes cross-hardware: AMD, Arm and Ascend ([blog](https://blog.lmcache.ai/en/2025/06/20/llm-production-stack-goes-cross-hardware-ascend-arm-and-amd-support-incoming/)).\n\n\n\n## About\n\nLMCache is a **KV cache management layer** for LLM inference. It turns KV cache from a temporary state into reusable *AI-native knowledge* that can be *stored* persistently, *reused* across multiple serving engines, *monitored* with an observability stack, and *transformed* for better generation quality. As a result, LMCache **reduces TTFT** (time-to-first-token) and **improves throughput**, especially for long-context agentic, multi-turn conversation, and knowledge-augmented workloads (e.g., RAG).\n\nLMCache is **vendor-neutral**. It can be used as a KV cache layer for a range of mainstream open-source serving engines, inference frameworks, hardware vendors, storage systems, and infrastructure providers. The vendor neutrality allows users to freely switch between serving engines and storage vendors, while reusing the stored KV caches.\n\n
\n\n \n \n \n\n
\n\n### Key features\n\n- **Engine-independent deployment**: LMCache, as a standalone daemon process, manages KV cache independently from the inference engine process, so that KV cache will not be lost even if the inference engine crashes (i.e., no fate-sharing with engines).\n\n- **Persistent, tiered KV cache offloading and reuse**: Move KV caches out of GPU memory into a tiered storage hierarchy spanning CPU memory, local storage, and remote backends, enabling reuse across requests, sessions, and engine instances to reduce repeated prefill computation and improve TTFT.\n\n- **Production-level KV cache observability**: LMCache provides a rich set of KV cache observability metrics, including typical Kubernetes metrics (health monitoring, performance diagnostics), KV-cache-specific metrics (request-level and token-level prefix cache hits, lifecycle, request-level KV cache performance), management metrics (user-specific usage), and more.\n\n- **Pluggable storage and transport backends**: Easily integrate remote storage and KV transfer backends through a unified interface, enabling KV cache offloading and sharing across storage providers. Through this interface, LMCache supports storage backends including CPU RAM, local disk (SSD), Redis/Valkey, Mooncake, InfiniStore, S3-compatible object storage, NIXL, and GDS.\n\n- **Non-prefix KV reuse**: Extend KV reuse beyond prefix caching by reusing cached KV blocks at any position in the prompt. This leverages CacheBlend to selectively recompute tokens for quality recovery.\n\n- **PD disaggregation and KV transfer**: Support KV cache transfer from prefill workers to decode workers over NVLink, RDMA, or TCP through transport layers such as NIXL.\n\n- **Pluggable KV transformation**: A simple interface for researchers to write compression, token dropping, and custom serialization through a flexible SERDE interface.\n\nLMCache is becoming an integral layer in the LLM inference *ecosystem*, with *community*-driven integration with serving engines, inference frameworks, hardware vendors, storage systems, and infrastructure providers:\n\n
\n \n
\n\n## Getting Started\n\nTo use LMCache, simply install `lmcache` from your package manager, e.g. pip:\n```bash\npip install lmcache\n```\n\nFor more setup options and examples, see:\n- [Installation](https://docs.lmcache.ai/getting_started/installation.html)\n- [Quickstart](https://docs.lmcache.ai/getting_started/quickstart.html)\n- [LMCache Recipes](https://docs.lmcache.ai/recipes/index.html)\n- [CLI Reference](https://docs.lmcache.ai/cli/index.html)\n- [Benchmarking Guide](https://docs.lmcache.ai/getting_started/benchmarking.html)\n- [Production Deployment](https://docs.lmcache.ai/mp/deployment.html)\n\n## Contributing\nWe welcome and value contributions and collaborations. Join us in improving LMCache. Check out the [Contributing Guide](https://docs.lmcache.ai/developer_guide/contributing.html) or join our [Slack community](https://join.slack.com/t/lmcacheworkspace/shared_invite/zt-3zxjao8h0-lRfBfnLqbALOtLsWn2ITxA) to get started.\n\n## Adoption and Partnerships\nLMCache has a growing community of developers, researchers, industry adopters, and partners building the next generation of efficient LLM inference systems.\n\n
\n \n \n \n \n \n
\n\nAs an independent open-source project, LMCache is becoming the de-facto standard for KV Cache management in LLM inference. Its continued development and community work are supported in part by [Tensormesh](https://www.tensormesh.ai/).\n\n## Citation\n\nLMCache builds on research in KV cache management, including cache reuse, offloading, compression, and serving optimization. If you use LMCache in your research, please cite the LMCache paper and related work.\n\n~~~bibtex\n@article{cheng2025lmcache,\n title={LMCache: An Efficient KV Cache Layer for Enterprise-Scale LLM Inference},\n author={Cheng, Yihua and Liu, Yuhan and Yao, Jiayi and An, Yuwei and Chen, Xiaokun and Feng, Shaoting and Huang, Yuyang and Shen, Samuel and Du, Kuntai and Jiang, Junchen},\n journal={arXiv preprint arXiv:2510.09665},\n year={2025}\n}\n~~~\n\n\nRelated papers\n\n~~~bibtex\n@inproceedings{liu2024cachegen,\n title={Cachegen: Kv cache compression and streaming for fast large language model serving},\n author={Liu, Yuhan and Li, Hanchen and Cheng, Yihua and Ray, Siddhant and Huang, Yuyang and Zhang, Qizheng and Du, Kuntai and Yao, Jiayi and Lu, Shan and Ananthanarayanan, Ganesh and others},\n booktitle={Proceedings of the ACM SIGCOMM 2024 Conference},\n pages={38--56},\n year={2024}\n}\n\n@inproceedings{yao2025cacheblend,\n title={Cacheblend: Fast large language model serving for rag with cached knowledge fusion},\n author={Yao, Jiayi and Li, Hanchen and Liu, Yuhan and Ray, Siddhant and Cheng, Yihua and Zhang, Qizheng and Du, Kuntai and Lu, Shan and Jiang, Junchen},\n booktitle={Proceedings of the twentieth European conference on computer systems},\n pages={94--109},\n year={2025}\n}\n~~~\n\n\n\n## License\n\nThe LMCache codebase is licensed under Apache License 2.0. See the [LICENSE](LICENSE) file for details.\n",
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"full_name": "infiniflow/ragflow",
"url": "https://github.com/infiniflow/ragflow",
"description": "RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs",
"language": "Go",
"total_stars": 83628,
"forks": 9699,
"stars_this_period": 545,
"source_slice": "go",
"source_slices": [
"go"
],
"metadata": {
"topics": [
"agentic-ai",
"agentic-retrieval",
"agentic-search",
"ai",
"ai-agents",
"context-engine",
"context-management",
"llm-apps",
"rag",
"retrieval-augmented-generation"
],
"license": "Apache-2.0",
"open_issues": 2849,
"created_at": "2023-12-12T06:13:13Z",
"pushed_at": "2026-06-25T13:45:36Z",
"homepage": "https://ragflow.io",
"default_branch": "main",
"forks": 9699,
"watchers": 343,
"archived": false,
"size_kb": 132921
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"readme_content": "
\n\n\n📕 Table of Contents\n\n- 💡 [What is RAGFlow?](#-what-is-ragflow)\n- 🎮 [Get Started](#-get-started)\n- 📌 [Latest Updates](#-latest-updates)\n- 🌟 [Key Features](#-key-features)\n- 🔎 [System Architecture](#-system-architecture)\n- 🎬 [Self-Hosting](#-self-hosting)\n- 🔧 [Configurations](#-configurations)\n- 🔧 [Build a Docker image](#-build-a-docker-image)\n- 🔨 [Launch service from source for development](#-launch-service-from-source-for-development)\n- 📚 [Documentation](#-documentation)\n- 📜 [Roadmap](#-roadmap)\n- 🏄 [Community](#-community)\n- 🙌 [Contributing](#-contributing)\n\n\n\n## 💡 What is RAGFlow?\n\n[RAGFlow](https://ragflow.io/) is a leading open-source Retrieval-Augmented Generation ([RAG](https://ragflow.io/basics/what-is-rag)) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs. It offers a streamlined RAG workflow adaptable to enterprises of any scale. Powered by a converged [context engine](https://ragflow.io/basics/what-is-agent-context-engine) and pre-built agent templates, RAGFlow enables developers to transform complex data into high-fidelity, production-ready AI systems with exceptional efficiency and precision.\n\n## 🎮 Get Started\n\nTry our cloud service at [https://cloud.ragflow.io](https://cloud.ragflow.io).\n\n
\n\n\n
\n\n## 🔥 Latest Updates\n\n- 2026-06-15 Support multiple chat channels such as Feishu, Discord, Telegram, Line, etc.\n- 2026-04-24 Supports DeepSeek v4.\n- 2026-03-24 [RAGFlow Skill on OpenClaw](https://clawhub.ai/yingfeng/ragflow-skill) — Provides an official skill for accessing RAGFlow datasets via OpenClaw.\n- 2025-12-26 Supports 'Memory' for AI agent.\n- 2025-11-19 Supports Gemini 3 Pro.\n- 2025-11-12 Supports data synchronization from Confluence, S3, Notion, Discord, Google Drive.\n- 2025-10-23 Supports MinerU & Docling as document parsing methods.\n- 2025-10-15 Supports orchestrable ingestion pipeline.\n- 2025-08-08 Supports OpenAI's latest GPT-5 series models.\n- 2025-08-01 Supports agentic workflow and MCP.\n- 2025-05-23 Adds a Python/JavaScript code executor component to Agent.\n- 2025-03-19 Supports using a multi-modal model to make sense of images within PDF or DOCX files.\n\n## 🎉 Stay Tuned\n\n⭐️ Star our repository to stay up-to-date with exciting new features and improvements! Get instant notifications for new\nreleases! 🌟\n\n
\n\n
\n\n## 🌟 Key Features\n\n### 🍭 **\"Quality in, quality out\"**\n\n- [Deep document understanding](./deepdoc/README.md)-based knowledge extraction from unstructured data with complicated\n formats.\n- Finds \"needle in a data haystack\" of literally unlimited tokens.\n\n### 🍱 **Template-based chunking**\n\n- Intelligent and explainable.\n- Plenty of template options to choose from.\n\n### 🌱 **Grounded citations with reduced hallucinations**\n\n- Visualization of text chunking to allow human intervention.\n- Quick view of the key references and traceable citations to support grounded answers.\n\n### 🍔 **Compatibility with heterogeneous data sources**\n\n- Supports Word, slides, excel, txt, images, scanned copies, structured data, web pages, and more.\n\n### 🛀 **Automated and effortless RAG workflow**\n\n- Streamlined RAG orchestration catered to both personal and large businesses.\n- Configurable LLMs as well as embedding models.\n- Multiple recall paired with fused re-ranking.\n- Intuitive APIs for seamless integration with business.\n\n## 🔎 System Architecture\n\n
\n\n
\n\n## 🎬 Self-Hosting\n\n### 📝 Prerequisites\n\n- CPU >= 4 cores\n- RAM >= 16 GB\n- Disk >= 50 GB\n- Docker >= 24.0.0 & Docker Compose >= v2.26.1\n- Python >= 3.13\n- [gVisor](https://gvisor.dev/docs/user_guide/install/): Required only if you intend to use the code executor (sandbox) feature of RAGFlow.\n\n> [!TIP]\n> If you have not installed Docker on your local machine (Windows, Mac, or Linux), see [Install Docker Engine](https://docs.docker.com/engine/install/).\n\n### 🚀 Start up the server\n\n1. Ensure `vm.max_map_count` >= 262144:\n\n > To check the value of `vm.max_map_count`:\n >\n > ```bash\n > $ sysctl vm.max_map_count\n > ```\n >\n > Reset `vm.max_map_count` to a value at least 262144 if it is not.\n >\n > ```bash\n > # In this case, we set it to 262144:\n > $ sudo sysctl -w vm.max_map_count=262144\n > ```\n >\n > This change will be reset after a system reboot. To ensure your change remains permanent, add or update the\n > `vm.max_map_count` value in **/etc/sysctl.conf** accordingly:\n >\n > ```bash\n > vm.max_map_count=262144\n > ```\n >\n2. Clone the repo:\n\n ```bash\n $ git clone https://github.com/infiniflow/ragflow.git\n ```\n3. Start up the server using the pre-built Docker images:\n\n> [!CAUTION]\n> All Docker images are built for x86 platforms. We don't currently offer Docker images for ARM64.\n> If you are on an ARM64 platform, follow [this guide](https://ragflow.io/docs/dev/build_docker_image) to build a Docker image compatible with your system.\n\n> The command below downloads the `v0.26.1` edition of the RAGFlow Docker image. See the following table for descriptions of different RAGFlow editions. To download a RAGFlow edition different from `v0.26.1`, update the `RAGFLOW_IMAGE` variable accordingly in **docker/.env** before using `docker compose` to start the server.\n\n```bash\n $ cd ragflow/docker\n\n # git checkout v0.26.1\n # Optional: use a stable tag (see releases: https://github.com/infiniflow/ragflow/releases)\n # This step ensures the **entrypoint.sh** file in the code matches the Docker image version.\n\n # Use CPU for DeepDoc tasks:\n $ docker compose -f docker-compose.yml up -d\n\n # To use GPU to accelerate DeepDoc tasks:\n # sed -i '1i DEVICE=gpu' .env\n # docker compose -f docker-compose.yml up -d\n```\n\n> Note: Prior to `v0.22.0`, we provided both images with embedding models and slim images without embedding models. Details as follows:\n\n| RAGFlow image tag | Image size (GB) | Has embedding models? | Stable? |\n|-------------------|-----------------|-----------------------|----------------|\n| v0.21.1 | ≈9 | ✔️ | Stable release |\n| v0.21.1-slim | ≈2 | ❌ | Stable release |\n\n> Starting with `v0.22.0`, we ship only the slim edition and no longer append the **-slim** suffix to the image tag.\n\n4. Check the server status after having the server up and running:\n\n ```bash\n $ docker logs -f docker-ragflow-cpu-1\n ```\n\n _The following output confirms a successful launch of the system:_\n\n ```bash\n\n ____ ___ ______ ______ __\n / __ \\ / | / ____// ____// /____ _ __\n / /_/ // /| | / / __ / /_ / // __ \\| | /| / /\n / _, _// ___ |/ /_/ // __/ / // /_/ /| |/ |/ /\n /_/ |_|/_/ |_|\\____//_/ /_/ \\____/ |__/|__/\n\n * Running on all addresses (0.0.0.0)\n ```\n\n > If you skip this confirmation step and directly log in to RAGFlow, your browser may prompt a `network abnormal`\n > error because, at that moment, your RAGFlow may not be fully initialized.\n >\n5. In your web browser, enter the IP address of your server and log in to RAGFlow.\n\n > With the default settings, you only need to enter `http://IP_OF_YOUR_MACHINE` (**sans** port number) as the default\n > HTTP serving port `80` can be omitted when using the default configurations.\n >\n6. In [service_conf.yaml.template](./docker/service_conf.yaml.template), select the desired LLM factory in `user_default_llm` and update\n the `API_KEY` field with the corresponding API key.\n\n > See [llm_api_key_setup](https://ragflow.io/docs/dev/llm_api_key_setup) for more information.\n >\n\n _The show is on!_\n\n## 🔧 Configurations\n\nWhen it comes to system configurations, you will need to manage the following files:\n\n- [.env](./docker/.env): Keeps the fundamental setups for the system, such as `SVR_HTTP_PORT`, `MYSQL_PASSWORD`, and\n `MINIO_PASSWORD`.\n- [service_conf.yaml.template](./docker/service_conf.yaml.template): Configures the back-end services. The environment variables in this file will be automatically populated when the Docker container starts. Any environment variables set within the Docker container will be available ",
"manifest_file": "go.mod",
"manifest_content": "module ragflow\n\ngo 1.26.4\n\nrequire (\n\tgithub.com/DATA-DOG/go-sqlmock v1.5.2\n\tgithub.com/alibabacloud-go/agentrun-20250910 v1.1.0\n\tgithub.com/alibabacloud-go/darabonba-openapi/v2 v2.1.12\n\tgithub.com/alicebob/miniredis/v2 v2.38.0\n\tgithub.com/aws/aws-sdk-go-v2 v1.41.3\n\tgithub.com/aws/aws-sdk-go-v2/aws/protocol/eventstream v1.7.6\n\tgithub.com/aws/aws-sdk-go-v2/config v1.32.11\n\tgithub.com/aws/aws-sdk-go-v2/credentials v1.19.11\n\tgithub.com/aws/aws-sdk-go-v2/service/s3 v1.96.4\n\tgithub.com/aws/aws-sdk-go-v2/service/sts v1.41.8\n\tgithub.com/aws/smithy-go v1.24.2\n\tgithub.com/browserbase/stagehand-go/v3 v3.21.0\n\tgithub.com/cenkalti/backoff/v5 v5.0.3\n\tgithub.com/cespare/xxhash/v2 v2.3.0\n\tgithub.com/cloudwego/eino v0.9.9\n\tgithub.com/denisenkom/go-mssqldb v0.12.3\n\tgithub.com/elastic/go-elasticsearch/v8 v8.19.1\n\tgithub.com/eric642/e2b-go-sdk v0.1.3\n\tgithub.com/gin-gonic/gin v1.10.1\n\tgithub.com/glebarez/sqlite v1.11.0\n\tgithub.com/go-sql-driver/mysql v1.7.0\n\tgithub.com/goccy/go-json v0.10.2\n\tgithub.com/gomarkdown/markdown v0.0.0-20260614204949-e08cff860f76\n\tgithub.com/google/uuid v1.6.0\n\tgithub.com/infiniflow/infinity-go-sdk v0.0.0-00010101000000-000000000000\n\tgithub.com/iromli/go-itsdangerous v0.0.0-20220223194502-9c8bef8dac6a\n\tgithub.com/json-iterator/go v1.1.12\n\tgithub.com/kaptinlin/jsonrepair v0.4.8\n\tgithub.com/lib/pq v1.10.9\n\tgithub.com/minio/minio-go/v7 v7.0.99\n\tgithub.com/nats-io/nats.go v1.52.0\n\tgithub.com/nikolalohinski/gonja v1.5.3\n\tgithub.com/peterh/liner v1.2.2\n\tgithub.com/pkoukk/tiktoken-go v0.1.8\n\tgithub.com/prometheus/client_golang v1.23.2\n\tgithub.com/prometheus/client_model v0.6.2\n\tgithub.com/redis/go-redis/v9 v9.18.0\n\tgithub.com/signintech/gopdf v0.36.1\n\tgithub.com/siongui/gojianfan v0.0.0-20210926212422-2f175ac615de\n\tgithub.com/spf13/viper v1.18.2\n\tgithub.com/xuri/excelize/v2 v2.10.1\n\tgithub.com/yfedoseev/office_oxide/go v0.1.2\n\tgithub.com/yfedoseev/pdf_oxide/go v0.3.67\n\tgithub.com/zeebo/xxh3 v1.0.2\n\tgo.opentelemetry.io/contrib/instrumentation/net/http/otelhttp v0.69.0\n\tgo.opentelemetry.io/otel v1.44.0\n\tgo.opentelemetry.io/otel/exporters/otlp/otlptrace v1.44.0\n\tgo.opentelemetry.io/otel/exporters/otlp/otlptrace/otlptracehttp v1.44.0\n\tgo.opentelemetry.io/otel/sdk v1.44.0\n\tgo.opentelemetry.io/otel/trace v1.44.0\n\tgo.uber.org/zap v1.27.1\n\tgolang.org/x/crypto v0.51.0\n\tgolang.org/x/net v0.55.0\n\tgolang.org/x/sync v0.20.0\n\tgolang.org/x/term v0.43.0\n\tgolang.org/x/text v0.37.0\n\tgoogle.golang.org/genai v1.54.0\n\tgoogle.golang.org/grpc v1.81.1\n\tgopkg.in/natefinch/lumberjack.v2 v2.2.1\n\tgopkg.in/yaml.v3 v3.0.1\n\tgorm.io/driver/mysql v1.5.2\n\tgorm.io/gorm v1.25.7\n)\n\nrequire (\n\tcloud.google.com/go v0.116.0 // indirect\n\tcloud.google.com/go/auth v0.9.3 // indirect\n\tcloud.google.com/go/compute/metadata v0.9.0 // indirect\n\tconnectrpc.com/connect v1.19.2 // indirect\n\tgithub.com/alibabacloud-go/alibabacloud-gateway-spi v0.0.5 // indirect\n\tgithub.com/alibabacloud-go/debug v1.0.1 // indirect\n\tgithub.com/alibabacloud-go/tea v1.3.12 // indirect\n\tgithub.com/alibabacloud-go/tea-utils/v2 v2.0.7 // indirect\n\tgithub.com/aliyun/credentials-go v1.4.5 // indirect\n\tgithub.com/apache/thrift v0.23.0 // indirect\n\tgithub.com/apapsch/go-jsonmerge/v2 v2.0.0 // indirect\n\tgithub.com/aws/aws-sdk-go-v2/feature/ec2/imds v1.18.19 // indirect\n\tgithub.com/aws/aws-sdk-go-v2/internal/configsources v1.4.19 // indirect\n\tgithub.com/aws/aws-sdk-go-v2/internal/endpoints/v2 v2.7.19 // indirect\n\tgithub.com/aws/aws-sdk-go-v2/internal/ini v1.8.5 // indirect\n\tgithub.com/aws/aws-sdk-go-v2/internal/v4a v1.4.20 // indirect\n\tgithub.com/aws/aws-sdk-go-v2/service/internal/accept-encoding v1.13.6 // indirect\n\tgithub.com/aws/aws-sdk-go-v2/service/internal/checksum v1.9.11 // indirect\n\tgithub.com/aws/aws-sdk-go-v2/service/internal/presigned-url v1.13.19 // indirect\n\tgithub.com/aws/aws-sdk-go-v2/service/internal/s3shared v1.19.19 // indirect\n\tgithub.com/aws/aws-sdk-go-v2/service/signin v1.0.7 // indirect\n\tgithub.com/aws/aws-sdk-go-v2/service/sso v1.30.12 // indirect\n\tgithub.com/aws/aws-sdk-go-v2/service/ssooidc v1.35.16 // indirect\n\tgithub.com/bahlo/generic-list-go v0.2.0 // indirect\n\tgithub.com/beorn7/perks v1.0.1 // indirect\n\tgithub.com/buger/jsonparser v1.1.1 // indirect\n\tgithub.com/bytedance/gopkg v0.1.3 // indirect\n\tgithub.com/bytedance/sonic v1.15.0 // indirect\n\tgithub.com/bytedance/sonic/loader v0.5.0 // indirect\n\tgithub.com/clbanning/mxj/v2 v2.7.0 // indirect\n\tgithub.com/cloudwego/base64x v0.1.6 // indirect\n\tgithub.com/dgryski/go-rendezvous v0.0.0-20200823014737-9f7001d12a5f // indirect\n\tgithub.com/dlclark/regexp2 v1.10.0 // indirect\n\tgithub.com/dustin/go-humanize v1.0.1 // indirect\n\tgithub.com/ebitengine/purego v0.10.1 // indirect\n\tgithub.com/eino-contrib/jsonschema v1.0.3 // indirect\n\tgithub.com/elastic/elastic-transport-go/v8 v8.8.0 // indirect\n\tgithub.com/felixge/httpsnoop v1.0.4 // indirect\n\tgithub.com/fsnotify/fsnotify v1.7.0 // indirect\n\tgithub.com/gabriel-vasile/mimetype v1.4.3 // indirect\n\tgithub.com/gin-contrib/sse v0.1.0 // indirect\n\tgithub.com/glebarez/go-sqlite",
"strategic_keywords": [
"agent",
"agents",
"rag",
"llm",
"eval",
"protocol"
],
"relationship_label": "Memory 组件",
"data_confidence": "high",
"evidence_sources": [
"github_trending",
"github_repo_api",
"readme",
"go.mod"
],
"score_breakdown": {
"heat": 19,
"relevance": 20,
"novelty": 15,
"productize": 14,
"adoption": 10,
"relation": 10,
"risk_signal": 8,
"total": 96
},
"strategic_score": 96
},
{
"owner": "everywall",
"name": "ladder",
"full_name": "everywall/ladder",
"url": "https://github.com/everywall/ladder",
"description": "Selfhosted alternative to 12ft.io. and 1ft.io. Proxy to remove CORS headers and modify HTML",
"language": "Go",
"total_stars": 8526,
"forks": 490,
"stars_this_period": 487,
"source_slice": "go",
"source_slices": [
"go"
],
"metadata": {
"topics": [
"bypass",
"cors",
"cors-proxy",
"paywall",
"paywall-blocker",
"paywall-bypasser"
],
"license": "GPL-3.0",
"open_issues": 33,
"created_at": "2023-11-01T21:09:49Z",
"pushed_at": "2026-06-19T22:13:25Z",
"homepage": "",
"default_branch": "main",
"forks": 490,
"watchers": 31,
"archived": false,
"size_kb": 20908
},
"readme_content": "
\n \n
\n\n
Ladder
\n
\n\n\n*Ladder is a http web proxy.* \n\n[简体中文](README.zh-CN.md)\n\nLadder is a developer tool for testing and analyzing paywall implementations and content delivery behavior on modern websites.\n\nIt allows developers, researchers, and publishers to simulate different client environments (such as browsers and crawlers) and observe how content is served under varying conditions. This makes it useful for debugging paywall configurations, verifying access controls, http headers, and ensuring consistent behavior across different user agents.\n\nLadder is intended for legitimate testing, research, and quality assurance purposes only. It should only be used in compliance with applicable laws and the terms of service of the target website.\n\n\n\n### How it works\n\n```mermaid\nsequenceDiagram\n client->>+ladder: GET\n ladder-->>ladder: apply RequestModifications\n ladder->>+website: GET\n website->>-ladder: 200 OK\n ladder-->>ladder: apply ResultModifications\n ladder->>-client: 200 OK\n```\n\n### Features\n- [x] Remove/modify CORS headers from responses, assets, and images ...\n- [x] Remove/modify other headers (e.g. Content-Security-Policy)\n- [x] Remove/inject custom code (HTML, CSS, JavaScript) into the page\n- [x] Apply domain based ruleset/code to modify response / requested URL\n- [x] Keep site browsable\n- [x] API\n- [x] Fetch RAW HTML\n- [x] Custom User Agent\n- [x] Custom X-Forwarded-For IP\n- [x] [Docker container](https://github.com/everywall/ladder/pkgs/container/ladder) (amd64, arm64)\n- [x] Linux binary\n- [x] Mac OS binary\n- [x] Windows binary (untested)\n- [x] Basic Auth\n- [x] Access logs\n- [x] Might break tracking, adds and other 3rd party content\n- [x] Limit the proxy to a list of domains\n- [x] Expose Ruleset to other ladders\n- [ ] Robots.txt testing\n- [ ] Optional TOR proxy\n- [ ] A key to share a proxied URL\n\n### Limitations\nSome websites deliver different content (Cloaking) depending on the type of client accessing them (for example, search engine crawlers versus standard web browsers). Ladder can be configured to emulate different client types in order to retrieve publicly accessible content for testing, automation, or research purposes.\n\nHowever, many websites implement advanced mechanisms to restrict automated access, such as fingerprinting, rate limiting, or behavioral analysis. Ladder does not circumvent such protections and may not function correctly on services that actively restrict or control access.\n\nThird-party tools such as FlareSolverr exist and may be used independently to render web pages in a headless browser environment. These tools are not part of Ladder, and their use may be subject to legal and contractual restrictions. Users are solely responsible for ensuring that their usage complies with all applicable regulations.\n\n## Installation\n\n> **Warning:** If your instance will be publicly accessible, make sure to enable Basic Auth. This will prevent unauthorized users from using your proxy. If you do not enable Basic Auth, anyone can use your proxy to browse nasty/illegal stuff. And you will be made responsible for it.\n\n### Binary\n1) Download binary [here](https://github.com/everywall/ladder/releases/latest)\n2) Unpack and run the binary `./ladder -r https://raw.githubusercontent.com/everywall/ladder-rules/main/ruleset.yaml`\n3) Open Browser (Default: http://localhost:8080)\n\n### Docker\n```bash\ndocker run -p 8080:8080 -d --env RULESET=https://raw.githubusercontent.com/everywall/ladder-rules/main/ruleset.yaml --name ladder ghcr.io/everywall/ladder:latest\n```\n\n### Docker Compose\n```bash\ncurl https://raw.githubusercontent.com/everywall/ladder/main/docker-compose.yaml --output docker-compose.yaml\ndocker-compose up -d\n```\n\n### Helm\nSee [README.md](/helm-chart/README.md) in helm-chart sub-directory for more information.\n\n## Usage\n\n### Browser\n1) Open Browser (Default: http://localhost:8080)\n2) Enter URL\n3) Press Enter\n\nOr direct by appending the URL to the end of the proxy URL:\nhttp://localhost:8080/https://www.example.com\n\nOr create a bookmark with the following URL:\n```javascript\njavascript:window.location.href=\"http://localhost:8080/\"+location.href\n```\n\n### API\n```bash\ncurl -X GET \"http://localhost:8080/api/https://www.example.com\"\n```\n\n### RAW\nhttp://localhost:8080/raw/https://www.example.com\n\n\n### Running Ruleset\nhttp://localhost:8080/ruleset\n\n## Configuration\n\n### Environment Variables\n\n| Variable | Description | Value |\n| --- | --- | --- |\n| `PORT` | Port to listen on | `8080` |\n| `PREFORK` | Spawn multiple server instances | `false` |\n| `USER_AGENT` | User agent to emulate | `Mozilla/5.0 (compatible; Googlebot/2.1; +http://www.google.com/bot.html)` |\n| `X_FORWARDED_FOR` | IP forwarder address | `66.249.66.1` |\n| `USERPASS` | Enables Basic Auth, format `admin:123456` | `` |\n| `LOG_URLS` | Log fetched URL's | `true` |\n| `DISABLE_FORM` | Disables URL Form Frontpage | `false` |\n| `FORM_PATH` | Path to custom Form HTML | `` |\n| `RULESET` | Path or URL to a ruleset file, accepts local directories | `https://raw.githubusercontent.com/everywall/ladder-rules/main/ruleset.yaml` or `/path/to/my/rules.yaml` or `/path/to/my/rules/` |\n| `EXPOSE_RULESET` | Make your Ruleset available to other ladders | `true` |\n| `ALLOWED_DOMAINS` | Comma separated list of allowed domains. Empty = no limitations | `` |\n| `ALLOWED_DOMAINS_RULESET` | Allow Domains from Ruleset. false = no limitations | `false` |\n| `FLARESOLVERR_HOST` | URL for the FlareSolverr service for Cloudflare bypass (optional) | `http://localhost:8191` |\n\n`ALLOWED_DOMAINS` and `ALLOWED_DOMAINS_RULESET` are joined together. If both are empty, no limitations are applied.\n| `BASE_PATH` | Base path for the proxy, useful if you want to run the proxy on a subpath (e.g. http://localhost:8080/proxy/) | `` |\n\n### Ruleset\n\nIt is possible to apply custom rules to modify the response or the requested URL. This can be used to remove unwanted or modify elements from the page. The ruleset is a YAML file, a directory with YAML Files, or an URL to a YAML file that contains a list of rules for each domain. These rules are loaded on startup.\n\nThere is a basic ruleset available in a separate repository [ruleset.yaml](https://raw.githubusercontent.com/everywall/ladder-rules/main/ruleset.yaml). Feel free to add your own rules and create a pull request.\n\n\n```yaml\n- domain: example.com # Includes all subdomains\n domains: # Additional domains to apply the rule\n - www.example.de\n - www.beispiel.de\n headers:\n x-forwarded-for: none # override X-Forwarded-For header or delete with none\n referer: none # override Referer header or delete with none\n user-agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36\n content-security-policy: script-src 'self'; # override response header\n cookie: privacy=1\n regexRules:\n - match: ]*\\s+)?src=\"(/)([^\"]*)\"\n replace: \n- domain: www.anotherdomain.com # Domain where the rule applies\n useFlareSolverr: false # Use FlareSolverr for Cloudflare bypass (optional, default: false)\n paths: # Paths where the rule applies\n - /article\n googleCache: false # Use Google Cache to fetch the content\n regexRules: # Regex rules to apply\n - match: ]*\\s+)?src=\"(/)([^\"]*)\"\n replace:
![\"OpenMontage\"](\"assets/logo.png\"){kind=logo}
\n![\"License\"](\"https://img.shields.io/badge/license-AGPLv3-blue.svg\"){kind=icon}
\n![\"#1](\"https://img.shields.io/badge/%F0%9F%8F%86%20%231%20on%20GitHub%20Trending-Repository%20of%20the%20Day-8957E5?style=for-the-badge&labelColor=1a1a2e\"){kind=icon}
![\"YouTube\"](\"https://img.shields.io/badge/YouTube-%40OpenMontage-FF0000?style=for-the-badge&logo=youtube&logoColor=white\"){kind=icon}
![\"X\"](\"https://img.shields.io/badge/X-%40calesthioailabs-111111?style=for-the-badge&logo=x&logoColor=white\"){kind=icon}
![\"GitHub](\"https://img.shields.io/badge/Community-GitHub%20Discussions-0b1220?style=for-the-badge&logo=github&logoColor=white\"){kind=icon}
![\"Skills\"](\"https://res.cloudinary.com/total-typescript/image/upload/v1777382277/skill-repo-light_2x.png\")
\n ![\"Graph](\"docs/graph-ui-screenshot.png\")
\n 
\n
![\"MIT](\"https://img.shields.io/badge/License-MIT-blue.svg?style=for-the-badge\"){kind=icon}
\n ![\"Python](\"https://img.shields.io/badge/Python-3.10+-green.svg?style=for-the-badge&logo=python&logoColor=white\"){kind=icon}
\n ![\"GitHub](\"https://img.shields.io/github/stars/Panniantong/agent-reach?style=for-the-badge\")
![\"Featured｜HelloGitHub\"](\"https://api.hellogithub.com/v1/widgets/recommend.svg?rid=6daa16e405ce46ed97b4a57706aeb29f&claim_uid=pfiJMqhR9uvDGlT&theme=neutral\")
\n![\"Anspire](\"./docs/assets/anspire.png\")
\n ![\"轻松抓取搜索引擎上的实时金融新闻数据](\"./docs/assets/serpapi_banner_zh.png\")
\n ![\"DSA](\"docs/assets/readme_workspace_tour_20260510.gif\")
\n![\"小红书二维码\"](\"./docs/assets/xiaohongshu_tick.jpg\")
![\"GitHub](\"https://img.shields.io/github/stars/firecrawl/firecrawl.svg?style=social&label=Star&maxAge=2592000\")
\n\n\n---\n\n## Why Firecrawl?\n\n- **Industry-leading reliability**: Covers 96% of the web, including JS-heavy pages — no proxy headaches, just clean data ([see benchmarks](https://www.firecrawl.dev/blog/the-worlds-best-web-data-api-v25))\n- **Blazingly fast**: P95 latency of 3.4s across millions of pages, built for real-time agents and dynamic apps\n- **LLM-ready output**: Clean markdown, structured JSON, screenshots, and more — spend fewer tokens, build better AI apps\n- **We handle the hard stuff**: Rotating proxies, orchestration, rate limits, JS-blocked content, and more — zero configuration\n- **Agent ready**: Connect Firecrawl to any AI agent or MCP client with a single command\n- **Media parsing**: Parse and extract content from web-hosted PDFs, DOCX, and more\n- **Actions**: Click, scroll, write, wait, and press before extracting content\n- **Open source**: Developed transparently and collaboratively — [join our community](https://github.com/firecrawl/firecrawl)\n\n---\n\n## Feature Overview\n\n**Core Endpoints**\n\n| Feature | Description |\n|---------|-------------|\n| [**Search**](#search) | Search the web and get full page content from results |\n| [**Scrape**](#scrape) | Convert any URL to markdown, HTML, screenshots, or structured JSON |\n| [**Interact**](#interact) | Scrape a page, then interact with it using AI prompts or code |\n\n**More**\n\n| Feature | Description |\n|---------|-------------|\n| [**Agent**](#agent) | Automated data gathering, just describe what you need |\n| [**Crawl**](#crawl) | Scrape all URLs of a website with a single request |\n| [**Map**](#map) | Discover all URLs on a website instantly |\n| [**Batch Scrape**](#batch-scrape) | Scrape thousands of URLs asynchronously |\n\n---\n\n## Quick Start\n\nSign up at [firecrawl.dev](https://firecrawl.dev) to get your API key. Try the [playground](https://firecrawl.dev/playground) to test it out.\n\n### Search\n\nSearch the web and get full content from results.\n\n```python\nfrom firecrawl import Firecrawl\n\napp = Firecrawl(api_key=\"fc-YOUR_API_KEY\")\n\nsearch_result = app.search(\"firecrawl\", limit=5)\n```\n\n![\"Anthropic](\"assets/banner.png\")
\n![\"Cognee](\"https://raw.githubusercontent.com/topoteretes/cognee/refs/heads/dev/assets/cognee-logo-transparent.png\"){kind=logo}
\n \n\n ![\"Sponsor\"](\"https://img.shields.io/badge/Sponsor-❤️-ff69b4.svg\"){kind=icon}
\n\n![\"Why](\"https://raw.githubusercontent.com/topoteretes/cognee/refs/heads/main/assets/cognee_benefits.png\")
\n![\"Cognee](\"assets/cognee_products.png\")
\n![\"Verified](\"https://img.shields.io/badge/Verified-DPG-3333AB?logo=data:image/svg%2bxml;base64,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\"){kind=icon}
![\"Penpot](\"https://img.shields.io/discourse/posts?server=https%3A%2F%2Fcommunity.penpot.app\")
![\"Managed](\"https://img.shields.io/badge/managed%20with-TAIGA.io-709f14.svg\"){kind=icon}
\n \n \n ![\"Gitpod](\"https://img.shields.io/badge/Gitpod-ready--to--code-blue?logo=gitpod\"){kind=icon}
![\"Voicebox\"](\".github/assets/icon-dark.webp\"){kind=icon}
\n![\"Downloads\"](\"https://img.shields.io/github/downloads/jamiepine/voicebox/total?style=flat&color=blue\")
![\"Release\"](\"https://img.shields.io/github/v/release/jamiepine/voicebox?style=flat\")
![\"Stars\"](\"https://img.shields.io/github/stars/jamiepine/voicebox?style=flat\")
![\"License\"](\"https://img.shields.io/github/license/jamiepine/voicebox?style=flat\")
![\"Ask](\"https://img.shields.io/static/v1?label=Ask&message=DeepWiki&color=5B6EF7\")
![\"Voicebox](\"landing/public/assets/app-screenshot-1.webp\")
\n \n![\"Voicebox](\"landing/public/assets/app-screenshot-2.webp\")
\n![\"Voicebox](\"landing/public/assets/app-screenshot-3.webp\")
\n![\"OpenCut](\"https://assets.opencut.app/branding/symbol.svg\")
\n ![](\"https://opencollective.com/iptv-org/backers.svg?width=890\")
\r\n\r\n### Contributors\r\n\r\n![](\"https://opencollective.com/iptv-org/contributors.svg?width=890\")
\r\n\r\n## Legal\r\n\r\nNo video files are stored in this repository. The repository simply contains user-submitted links to publicly available video stream URLs, which to the best of our knowledge have been intentionally made publicly by the copyright holders. If any links in these playlists infringe on your rights as a copyright holder, they may be removed by opening an [issue](https://github.com/iptv-org/iptv/issues/new?template=6_copyright-claim.yml). However, note that we have **no control** over the destination of the link, and just removing the link from the playlist will not remove its contents from the web. Note that linking does not directly infringe copyright because no copy is made on the site providing the link, and thus this is **not** a valid reason to send a DMCA notice to GitHub. To remove this content from the web, you should contact the web host that's actually hosting the content (**not** GitHub, nor the maintainers of this repository).\r\n\r\n## License\r\n\r\n[](LICENSE)\r\n\r\n",
"manifest_file": "package.json",
"manifest_content": "{\r\n \"name\": \"iptv\",\r\n \"scripts\": {\r\n \"act:check\": \"gh act pull_request -W .github/workflows/check.yml\",\r\n \"act:format\": \"gh act workflow_dispatch -W .github/workflows/format.yml\",\r\n \"act:update\": \"gh act workflow_dispatch -W .github/workflows/update.yml\",\r\n \"api:load\": \"tsx scripts/commands/api/load.ts\",\r\n \"playlist:format\": \"tsx scripts/commands/playlist/format.ts\",\r\n \"playlist:update\": \"tsx scripts/commands/playlist/update.ts\",\r\n \"playlist:generate\": \"tsx scripts/commands/playlist/generate.ts\",\r\n \"playlist:validate\": \"tsx scripts/commands/playlist/validate.ts\",\r\n \"playlist:lint\": \"npx m3u-linter -c m3u-linter.json\",\r\n \"playlist:test\": \"tsx scripts/commands/playlist/test.ts\",\r\n \"playlist:edit\": \"tsx scripts/commands/playlist/edit.ts\",\r\n \"playlist:export\": \"tsx scripts/commands/playlist/export.ts\",\r\n \"readme:update\": \"tsx scripts/commands/readme/update.ts\",\r\n \"report:create\": \"tsx scripts/commands/report/create.ts\",\r\n \"lint\": \"npx eslint \\\"scripts/**/*.{ts,js}\\\" \\\"tests/**/*.{ts,js}\\\"\",\r\n \"test\": \"jest --runInBand\",\r\n \"postinstall\": \"npm run api:load\"\r\n },\r\n \"jest\": {\r\n \"transform\": {\r\n \"^.+\\\\.ts$\": \"@swc/jest\"\r\n },\r\n \"testRegex\": \"tests/(.*?/)?.*test.ts$\",\r\n \"setupFilesAfterEnv\": [\r\n \"jest-expect-message\"\r\n ]\r\n },\r\n \"author\": \"Arhey\",\r\n \"private\": true,\r\n \"license\": \"MIT\",\r\n \"dependencies\": {\r\n \"@alex_neo/jest-expect-message\": \"^1.0.5\",\r\n \"@eslint/eslintrc\": \"^3.3.1\",\r\n \"@eslint/js\": \"^9.32.0\",\r\n \"@freearhey/core\": \"^0.14.3\",\r\n \"@freearhey/storage-js\": \"^0.1.0\",\r\n \"@inquirer/prompts\": \"^7.8.0\",\r\n \"@iptv-org/sdk\": \"^1.5.0\",\r\n \"@octokit/core\": \"^7.0.3\",\r\n \"@octokit/plugin-paginate-graphql\": \"^6.0.0\",\r\n \"@octokit/plugin-paginate-rest\": \"^13.1.1\",\r\n \"@octokit/plugin-rest-endpoint-methods\": \"^16.0.0\",\r\n \"@octokit/types\": \"^14.1.0\",\r\n \"@stylistic/eslint-plugin\": \"^5.2.2\",\r\n \"@swc/jest\": \"^0.2.39\",\r\n \"@types/async\": \"^3.2.25\",\r\n \"@types/cli-progress\": \"^3.11.6\",\r\n \"@types/fs-extra\": \"^11.0.4\",\r\n \"@types/jest\": \"^30.0.0\",\r\n \"@types/lodash.uniqueid\": \"^4.0.9\",\r\n \"@types/node-cleanup\": \"^2.1.5\",\r\n \"@typescript-eslint/eslint-plugin\": \"^8.38.0\",\r\n \"@typescript-eslint/parser\": \"^8.38.0\",\r\n \"async\": \"^3.2.6\",\r\n \"axios\": \"^1.15.2\",\r\n \"chalk\": \"^5.4.1\",\r\n \"cli-progress\": \"^3.12.0\",\r\n \"commander\": \"^14.0.0\",\r\n \"console-table-printer\": \"^2.14.6\",\r\n \"cross-env\": \"^10.0.0\",\r\n \"es-toolkit\": \"^1.45.1\",\r\n \"eslint\": \"^9.32.0\",\r\n \"glob\": \"^11.0.3\",\r\n \"globals\": \"^16.3.0\",\r\n \"hls-parser\": \"^0.16.0\",\r\n \"iptv-playlist-parser\": \"^0.15.1\",\r\n \"jest\": \"^30.0.5\",\r\n \"jest-expect-message\": \"^1.1.3\",\r\n \"lodash.uniqueid\": \"^4.0.1\",\r\n \"m3u-linter\": \"^0.4.3\",\r\n \"mediainfo.js\": \"^0.3.6\",\r\n \"mpd-parser\": \"^1.3.1\",\r\n \"node-cleanup\": \"^2.1.2\",\r\n \"normalize-url\": \"^8.1.0\",\r\n \"socks-proxy-agent\": \"^8.0.5\",\r\n \"tsx\": \"^4.20.3\"\r\n },\r\n \"overrides\": {\r\n \"esbuild\": \"0.23.1\",\r\n \"@xmldom/xmldom\": \">=0.8.13 <1.0.0\"\r\n }\r\n}\r\n",
"strategic_keywords": [
"workflow",
"protocol"
],
"relationship_label": "Skill 来源",
"data_confidence": "high",
"evidence_sources": [
"github_trending",
"github_repo_api",
"readme",
"package.json"
],
"score_breakdown": {
"heat": 20,
"relevance": 14,
"novelty": 15,
"productize": 14,
"adoption": 10,
"relation": 8,
"risk_signal": 6,
"total": 87
},
"strategic_score": 87
},
{
"owner": "bytedance",
"name": "deer-flow",
"full_name": "bytedance/deer-flow",
"url": "https://github.com/bytedance/deer-flow",
"description": "An open-source long-horizon SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skill, subagents and message gateway, it handles different levels of tasks that could take minutes to hours.",
"language": "Python",
"total_stars": 74625,
"forks": 10064,
"stars_this_period": 3068,
"source_slice": "all",
"source_slices": [
"all",
"python"
],
"metadata": {
"topics": [
"agent",
"agentic",
"agentic-framework",
"agentic-workflow",
"ai",
"ai-agents",
"deep-research",
"harness",
"langchain",
"langgraph",
"langmanus",
"llm",
"multi-agent",
"nodejs",
"podcast",
"python",
"superagent",
"typescript"
],
"license": "MIT",
"open_issues": 950,
"created_at": "2025-05-07T02:50:19Z",
"pushed_at": "2026-06-25T15:32:30Z",
"homepage": "https://deerflow.tech",
"default_branch": "main",
"forks": 10064,
"watchers": 319,
"archived": false,
"size_kb": 40098
},
"readme_content": "# 🦌 DeerFlow - 2.0\n\nEnglish | [中文](./README_zh.md) | [日本語](./README_ja.md) | [Français](./README_fr.md) | [Русский](./README_ru.md)\n\n[](./backend/pyproject.toml)\n[](./Makefile)\n[](./LICENSE)\n\n![\"Web](\"https://img.shields.io/badge/Web_App-worldmonitor.app-blue?style=for-the-badge&logo=googlechrome&logoColor=white\"){kind=icon}
![\"Tech](\"https://img.shields.io/badge/Tech_Variant-tech.worldmonitor.app-0891b2?style=for-the-badge&logo=googlechrome&logoColor=white\"){kind=icon}
![\"Finance](\"https://img.shields.io/badge/Finance_Variant-finance.worldmonitor.app-059669?style=for-the-badge&logo=googlechrome&logoColor=white\"){kind=icon}
![\"Commodity](\"https://img.shields.io/badge/Commodity_Variant-commodity.worldmonitor.app-b45309?style=for-the-badge&logo=googlechrome&logoColor=white\"){kind=icon}
![\"Happy](\"https://img.shields.io/badge/Happy_Variant-happy.worldmonitor.app-f59e0b?style=for-the-badge&logo=googlechrome&logoColor=white\"){kind=icon}
![\"Energy](\"https://img.shields.io/badge/Energy_Variant-energy.worldmonitor.app-eab308?style=for-the-badge&logo=googlechrome&logoColor=white\"){kind=icon}
![\"Download](\"https://img.shields.io/badge/Download-Windows_(.exe)-0078D4?style=for-the-badge&logo=windows&logoColor=white\"){kind=icon}
![\"Download](\"https://img.shields.io/badge/Download-macOS_Apple_Silicon-000000?style=for-the-badge&logo=apple&logoColor=white\"){kind=icon}
![\"Download](\"https://img.shields.io/badge/Download-macOS_Intel-555555?style=for-the-badge&logo=apple&logoColor=white\"){kind=icon}
![\"Download](\"https://img.shields.io/badge/Download-Linux_(.AppImage)-FCC624?style=for-the-badge&logo=linux&logoColor=black\"){kind=icon}
![\"Turso](\"assets/turso.png\")
\n ![](\"https://img.shields.io/github/actions/workflow/status/tursodatabase/turso/rust.yml?style=flat-square\")
![](\"https://img.shields.io/github/release/tursodatabase/turso?style=flat-square&color=9CF\")
![\"Crate\"](\"https://img.shields.io/crates/v/turso\")
![\"NPM\"](\"https://img.shields.io/npm/v/@tursodatabase/database\")
![\"PyPI\"](\"https://img.shields.io/pypi/v/pyturso\")
![\"Maven](\"https://img.shields.io/maven-central/v/tech.turso/turso\")
![](\"http://img.shields.io/badge/license-MIT-orange.svg?style=flat-square\"){kind=icon}
\n ![](\"https://img.shields.io/github/issues-pr-closed/tursodatabase/turso.svg?style=flat-square&color=FF9966\")
\n ![](\"https://img.shields.io/github/commit-activity/m/tursodatabase/turso.svg?style=flat-square\")
\n ![](\"https://img.shields.io/github/last-commit/tursodatabase/turso.svg?style=flat-square&color=FF9900\")
\n![\"Chat](\"https://img.shields.io/discord/1258658826257961020?label=Discord&logo=Discord&style=social&label=Core%20Developers\")
![\"Chat](\"https://img.shields.io/discord/933071162680958986?label=Discord&logo=Discord&style=social&label=Users\")
![\"Stirling](\"https://raw.githubusercontent.com/Stirling-Tools/Stirling-PDF/main/docs/stirling.png\")
\n![\"Docker](\"https://img.shields.io/docker/pulls/frooodle/s-pdf\")
![\"Discord\"](\"https://img.shields.io/discord/1068636748814483718?label=Discord\")
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![\"Stars\"](\"https://img.shields.io/github/stars/JCodesMore/ai-website-cloner-template?style=flat\")
![\"Discord\"](\"https://img.shields.io/discord/1400896964597383279?label=discord\")
\n\nA reusable template for reverse-engineering any website into a clean, modern Next.js codebase using AI coding agents. \n\n**Recommended: [Claude Code](https://docs.anthropic.com/en/docs/claude-code) with Opus 4.7 for best results** — but works with a variety of AI coding agents.\n\nPoint it at a URL, run `/clone-website`, and your AI agent will inspect the site, extract design tokens and assets, write component specs, and dispatch parallel builders to reconstruct every section.\n\n## Demo\n\n[](https://youtu.be/O669pVZ_qr0)\n\n> Click the image above to watch the full demo on YouTube.\n\n## Quick Start\n\n> **Important:** Start by making your own copy with GitHub's **Use this template** button. Do not clone this template repository directly for your website project, and do not open pull requests here with your generated website.\n\n1. **Create your own repository from this template**\n\n On the GitHub page for this project, click **Use this template**, then click **Create a new repository**.\n\n Give your new repository a name, choose whether it should be public or private, then click **Create repository**. If GitHub shows an **Include all branches** option, you can leave it off.\n\n This gives you your own separate project to work in, so your website changes stay in your account instead of coming back to the main template.\n\n2. **Open your new repository on your computer**\n\n After GitHub creates your copy, open that new repository. Click **Code** and open or clone your new repository with your preferred coding tool.\n\n If you use the terminal, the command will look like this:\n\n ```bash\n git clone https://github.com/YOUR-USERNAME/YOUR-NEW-REPOSITORY.git\n cd YOUR-NEW-REPOSITORY\n ```\n\n3. **Install dependencies**\n ```bash\n npm install\n ```\n4. **Start your AI agent** — Claude Code recommended:\n ```bash\n claude --chrome\n ```\n5. **Run the skill**:\n ```\n /clone-website ![\"Plane](\"https://media.docs.plane.so/logo/plane_github_readme.png\"){kind=logo}
\n\n![\"Codex](\"https://github.com/openai/codex/blob/main/.github/codex-cli-splash.png\")
\n![\"twitter\"](\"https://img.shields.io/badge/follow-Tw93-red?style=flat-square&logo=Twitter\"){kind=icon}
![\"telegram\"](\"https://img.shields.io/badge/chat-telegram-blueviolet?style=flat-square&logo=Telegram\"){kind=icon}
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![\"GitHub](\"https://img.shields.io/github/issues-closed/tw93/Pake.svg?style=flat-square\")
![\"License\"](\"https://img.shields.io/github/license/firecrawl/firecrawl\")
\n ![\"Downloads\"](\"https://static.pepy.tech/badge/firecrawl-py\"){kind=icon}
\n ![\"GitHub](\"https://img.shields.io/github/contributors/firecrawl/firecrawl.svg\")
\n ![\"Visit](\"https://img.shields.io/badge/Visit-firecrawl.dev-orange\"){kind=icon}
\n ![\"Follow](\"https://img.shields.io/badge/Follow%20on%20X-000000?style=for-the-badge&logo=x&logoColor=white\"){kind=icon}
\n ![\"Follow](\"https://img.shields.io/badge/Follow%20on%20LinkedIn-0077B5?style=for-the-badge&logo=linkedin&logoColor=white\"){kind=icon}
\n ![\"Join](\"https://img.shields.io/badge/Join%20our%20Discord-5865F2?style=for-the-badge&logo=discord&logoColor=white\"){kind=icon}
\n ![\"Clips](\"https://cdn.builder.io/api/v1/image/assets%2FYJIGb4i01jvw0SRdL5Bt%2F189ebd9b2f2b4f0ead3b33138d4e4c10?format=webp&width=800\")
\n\n**Agent-Native Loom + Jam**\n\nRecord your screen with auto-transcripts and captured browser debug logs, share a link, and let an agent read the transcript, see timestamped frames, and fix the bug.\n\n![\"Plans](\"https://cdn.builder.io/api/v1/image/assets%2FYJIGb4i01jvw0SRdL5Bt%2Fb6f4213ac7cc42eeb10c12e8ccda8936?format=webp&width=800\")
\n\n**Visual plan mode for coding agents**\n\nInstall `/visual-plan` and `/visual-recap` so your coding agent can plan before it builds and recap changes after they land. High-level code reviews with diagrams, wireframes, annotations, and review links.\n\n![\"Design](\"https://cdn.builder.io/api/v1/image/assets%2F348da13fcd8b414c87de9066196f7266%2F961bedb713a94463b834c1f2f4643bcf?format=webp&width=800\")
\n\n**Agent-Native design prototyping**\n\nGenerate interactive HTML prototypes, compare variants, refine controls, and export the result.\n\n![\"Content](\"https://cdn.builder.io/api/v1/image/assets%2FYJIGb4i01jvw0SRdL5Bt%2F89bcfc6106304bfbaf8ec8a7ccd721eb?format=webp&width=800\")
\n\n**Open-source Obsidian for MDX**\n\nEdit local Markdown/MDX files, generate rich interactive custom blocks, and draft, rewrite, or publish with an agent.\n\n![\"Slides](\"https://cdn.builder.io/api/v1/image/assets%2FYJIGb4i01jvw0SRdL5Bt%2F2c09b451d40c4a74a89a38d69170c2d8?format=webp&width=800\")
\n\n**Agent-Native Google Slides, Pitch**\n\nGenerate and edit React-based presentations via prompt or point-and-click.\n\n![\"Analytics](\"https://cdn.builder.io/api/v1/image/assets%2FYJIGb4i01jvw0SRdL5Bt%2F4933a80cc3134d7e874631f688be828a?format=webp&width=800\")
\n\n**Agent-Native Amplitude, Mixpanel**\n\nConnect analytics data sources, prompt for real charts, and build reusable dashboards.\n\n![\"npm](\"https://img.shields.io/npm/v/@googleworkspace/cli\")
![\"license\"](\"https://img.shields.io/github/license/googleworkspace/cli\")
![\"CI](\"https://img.shields.io/github/actions/workflow/status/googleworkspace/cli/ci.yml?branch=main&label=CI\")
![\"install](\"https://img.shields.io/npm/unpacked-size/@googleworkspace/cli\")
![\"Orca\"](\"resources/build/icon.png\"){kind=icon}
Orca\n![\"Total](\"docs/assets/readme-downloads.svg\")
\n ![\"Join](\"https://img.shields.io/badge/Discord-5865F2?logo=discord&logoColor=white\"){kind=icon}
![\"Follow](\"https://img.shields.io/badge/X-000000?logo=x&logoColor=white\"){kind=icon}
![\"Supported](\"https://img.shields.io/badge/macOS%20%7C%20Windows%20%7C%20Linux-4493F8?style=flat-square\"){kind=icon}
![\"Orca](\"docs/assets/readme-hero.jpg\")
\n![\"Orca](\"docs/assets/feature-wall/mobile-companion-app-showcase.gif\")
![\"Parallel](\"docs/assets/feature-wall/parallel-worktrees.gif\")
![\"Terminal](\"docs/assets/feature-wall/terminal-splits.gif\")
![\"Embedded](\"docs/assets/feature-wall/design-mode.gif\")
![\"GitHub](\"docs/assets/feature-wall/github-linear.gif\")
![\"Remote](\"docs/assets/feature-wall/ssh-worktrees.gif\")
![\"Annotate](\"docs/assets/feature-wall/annotate-diff.gif\")
![\"Drag](\"docs/assets/feature-wall/file-drag.gif\")
![\"Script](\"docs/assets/feature-wall/orca-cli.gif\")
![\"Claude](\"docs/assets/claude-logo.svg\"){kind=logo}
Claude Code \n ![\"OpenClaude](\"resources/openclaude-logo.png\"){kind=logo}
OpenClaude \n ![\"Pi](\"https://pi.dev/favicon.svg\")
Pi \n ![\"oh-my-pi](\"https://omp.sh/favicon.svg\")
oh-my-pi \n ![\"iroh\"](\"./.img/iroh_wordmark.svg\")
\n\n![\"WebUI](\"docs/static/images/img_8.png\")
\n\n\n\n\n\n## 💾 数据保存\n\nMediaCrawler 支持多种数据存储方式，包括 CSV、JSON、JSONL、Excel、SQLite 和 MySQL 数据库。\n\n📖 **详细使用说明请查看：[数据存储指南](docs/data_storage_guide.md)**\n\n\n[🚀 MediaCrawlerPro 重磅发布 🚀！更多的功能，更好的架构设计！开源不易，欢迎订阅支持！](https://github.com/MediaCrawlerPro)\n\n\n## 💬 交流群组\n- **微信交流群**：[点击加入](https://nanmicoder.github.io/MediaCrawler/%E5%BE%AE%E4%BF%A1%E4%BA%A4%E6%B5%81%E7%BE%A4.html)\n- **B站账号**：[关注我](https://space.bilibili.com/434377496)，分享AI与爬虫技术知识\n\n\n## 💰 赞助商展示\n\n\n![](\"docs/static/images/tikhub_banner_zh.png\")
\n![\"Atlas](\"docs/static/images/atlas_cloud_logo_black.png#gh-light-mode-only\"){kind=logo}
\n![\"Atlas](\"docs/static/images/atlas_cloud_logo_white.png#gh-dark-mode-only\"){kind=logo}
\n\n![\"微信赞赏\"](\"docs/static/images/wechat_pay.jpeg\")
![\"支付宝\"](\"docs/static/images/zfb_pay.png\")
![\"Buy](\"docs/static/images/bmc_button.png\")
\n![\"Install](\"https://www.raycast.com/mattiacolombomc/handy/install_button@2x.png?v=1.1\")
\n\nControl Handy from [Raycast](https://www.raycast.com) — start/stop recording, browse transcript history, manage dictionary, switch models and languages.\n\n[Source](https://github.com/mattiacolombomc/raycast-handy) · by [@mattiacolombomc](https://github.com/mattiacolombomc)\n\n## Architecture\n\nHandy is built as a Tauri application combining:\n\n- **Frontend**: React + TypeScript with Tailwind CSS for the settings UI\n- **Backend**: Rust for system integration, audio processing, and ML inference\n- **Core Libraries**:\n - `whisper-rs`: Local speech recognition with Whisper models\n - `transcribe-rs`: CPU-optimized speech recognition with Parakeet models\n - `cpal`: Cross-platform audio I/O\n - `vad-rs`: Voice Activity Detection\n - `rdev`: Global keyboard shortcuts and system events\n - `rubato`: Audio resampling\n\n### Debug Mode\n\nHandy includes an advanced debug mode for development and troubleshooting. Access it by pressing:\n\n- **macOS**: `Cmd+Shift+D`\n- **Windows/Linux**: `Ctrl+Shift+D`\n\n### CLI Parameters\n\nHandy supports command-line flags for controlling a running instance and customizing startup behavior. These work on all platforms (macOS, Windows, Linux).\n\n**Remote control flags** (sent to an already-running instance via the single-instance plugin):\n\n```bash\nhandy --toggle-transcription # Toggle recording on/off\nhandy --toggle-post-process # Toggle recording with post-processing on/off\nhandy --cancel # Cancel the current operation\n```\n\n**Startup flags:**\n\n```bash\nhandy --start-hidden # Start without showing the main window\nhandy --no-tray # Start without the system tray icon\nhandy --debug # Enable debug mode with verbose logging\nhandy --help # Show all available flags\n```\n\nFlags can be combined for autostart scenarios:\n\n```bash\nhandy --start-hidden --no-tray\n```\n\n> **macOS tip:** When Handy is installed as an app bundle, invoke the binary directly:\n>\n> ```bash\n> /Applications/Handy.app/Contents/MacOS/Handy --toggle-transcription\n> ```\n\n## Known Issues & Current Limitations\n\nThis project is actively being developed and has some [known issues](https://github.com/cjpais/Handy/issues). We believe in transparency about the current state:\n\n### Major Issues (Help Wanted)\n\n**Whisper Model Crashes:**\n\n- Whisper models crash on certain system configurations (Windows and Linux)\n- Does not affect all systems - issue is configuration-dependent\n - If you experience crashes and are a developer, please help to fix and provide debug logs!\n\n**Wayland Support (Linux):**\n\n- Limited support for Wayland display server\n- Requires [`wtype`](https://github.com/atx/wtype) or [`dotool`](https://sr.ht/~geb/dotool/) for text input to work correctly (see [Linux Notes](#linux-notes) below for installation)\n\n### Linux Notes\n\n**Text Input Tools:**\n\nFor reliable text input on Linux, install the appropriate tool for your display server:\n\n| Display Server | Recommended Tool | Install Command |\n| -------------- | ---------------- | -------------------------------------------------- |\n| X11 | `xdotool` | `sudo apt install xdotool` |\n| Wayland | `wtype` | `sudo apt install wtype` |\n| Both | `dotool` | `sudo apt install dotool` (requires `input` group) |\n\n- **X11**: Install `xdotool` for both direct typing and clipboard paste shortcuts\n- **Wayland**: Install `wtype` (preferred) or `dotool` for text input to work correctly\n- **dotool setup**: Requires adding your user to the `input` group: `sudo usermod -aG input $USER` (then log out and back in)\n\nWithout these tools, Handy falls back to enigo which may have limited compatibility, especially on Wayland.\n\n**Other Notes:**\n\n- **Runtime library dependency (`libgtk-layer-shell.so.0`)**:\n - Handy links `gtk-layer-shell` on Linux. If startup fails with `error while loading shared libraries: libgtk-layer-shell.so.0`, install the runtime package for your distro:\n\n | Distro | Package to install | Example command |\n | ------------- | --------------------- | -------------------------------------- |\n | Ubuntu/Debian | `libgtk-layer-shell0` | `sudo apt install libgtk-layer-shell0` |\n | Fedora/RHEL | `gtk-layer-shell` | `sudo dnf install gtk-layer-shell` |\n | Arch Linux | `gtk-layer-shell` | `sudo pacman -S gtk-layer-shell` |\n\n - For building from source on Ubuntu/Debian, you may also need `libgtk-layer-shell-dev`.\n\n- The recording overlay is disabled by default on Linux (`Overlay Position: None`) because certain compositors treat it as the active window. When the overlay is visible it can steal focus, which prevents Handy from pasting back into the application that triggered transcription. If you enable the overlay anyway, be aware that clipboard-based pasting might fail or end up in the wrong window.\n- If you are having trouble with the app, running with the environment variable `WEBKIT_DISABLE_DMABUF_RENDERER=1` may help\n- If Handy fails to start reliably on Linux, see [Troubleshooting → Linux Startup Crashes or Instability](#linux-startup-crashes-or-instability).\n- **Global keyboard shortcuts (Wayland):** On Wayland, system-level shortcuts must be configured through your desktop environment or window manager. Use the [CLI flags](#cli-parameters) as the command for your custom shortcut.\n\n **GNOME:**\n 1. Open **Settings > Keyboard > Keyboard Shortcuts > Custom Shortcuts**\n 2. Click the **+** button to add a new shortcut\n 3. Set the **Name** to `Toggle Handy Transcription`\n 4. Set the **Command** to `handy --toggle-transcription`\n 5. Click **Set Shortcut** and press your desired key combination (e.g., `Super+O`)\n\n **KDE Plasma:**\n 1. Open **System Settings > Shortcuts > Custom Shortcuts**\n 2. Click **Edit > New > Global Shortcut > Command/URL**\n 3. Name it `Toggle Handy Transcription`\n 4. In the **Trigger** tab, set your desired key combination\n 5. In the **Action** tab, set the command to `handy --toggle-transcription`\n\n **Sway / i3:**\n\n Add to your config file (`~/.config/sway/config` or `~/.config/i3/config`):\n\n ```ini\n bindsym $mod+o exec handy --toggle-transcription\n ```\n\n **Hyprland:**\n\n Add to your config file (`~/.config/hypr/hyprland.conf`):\n\n ```ini\n bind = $mainMod, O, exec, handy --toggle-transcription\n ```\n\n- You can also manage global shortcuts outside of Handy via Unix signals, which lets Wayland window managers or other hotkey daemons keep ownership of keybindings:\n\n | Signal | Action | Example |\n | --------- | ----------------------------------------- | ---------------------- |\n | `SIGUSR2` | Toggle transcription | `pkill -USR2 -n handy` |\n | `SIGUSR1` | Toggle transcription with post-processing | `pkill -USR1 -n handy` |\n\n Example Sway config:\n\n ```ini\n bindsym $mod+o exec pkill -USR2 -n handy\n bindsym $mod+p exec pkill -USR1 -n handy\n ```\n\n `pkill` here simply delivers the signal—it does not terminate the process.\n\n**Overlay & Pasting Issues (Linux):**\n\n- The recording overlay window can interfere with pasting transcribed text into target applications on Linux (X11)\n- **Solution:** Open **Settings > Advanced** and set **\"Overlay Position\"** to **\"None\"** to disable the overlay\n- Enable **\"Audio Feedback\"** (also in Advanced) if you still want audible confirmation of recording state\n- Users who upgrade from older versions or import settings from other platforms may need to manually apply this change\n\n### Platform Support\n\n- **macOS (both Intel and Apple Silicon)**\n- **x64 Windows**\n- **x64 Linux**\n\n### System Requirements/Recommendations\n\nThe following are recommendations for running Handy on your own machine. If you don't meet the system requirements, the performance of the application may be degraded. We are working on improving the performance across all kinds of computers and hardware.\n\n**For Whisper Models:**\n\n- **macOS**: M series Mac, Intel Mac\n- **Windows**: Intel, AMD, or NVIDIA GPU\n- **Linux**: Intel, AMD, or NVIDIA GPU\n - Ubuntu 22.04, 24.04\n\n**For Parakeet V3 Model:**\n\n- **CPU-only operation** - runs on a wide variety of hardware\n- **Minimum**: Intel Skylake (6th gen) or equivalent AMD processors\n- **Performance**: ~5x real-time speed on mid-range hardware (tested on i5)\n- **Automatic language detection** - no manual language selection required\n\n## Roadmap & Active Development\n\nWe're actively working on several features and improvements. Contributions and feedback are welcome!\n\n### In Progress\n\n**Debug Logging:**\n\n- Adding debug logging to a file to help diagnose issues\n\n**macOS Keyboard Improvements:**\n\n- Support for Globe key as transcription trigger\n- A rewrite of global shortcut handling for MacOS, and potentially other OS's too.\n\n**Opt-in Analytics:**\n\n- Collect anonymous usage data to help improve Handy\n- Privacy-first approach with clear opt-in\n\n**Sett",
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"relationship_label": "Memory 组件",
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"owner": "interviewstreet",
"name": "hiring-agent",
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"url": "https://github.com/interviewstreet/hiring-agent",
"description": "AI agent to evaluate and score resumes.",
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"metadata": {
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"license": "MIT",
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"created_at": "2025-07-29T01:50:34Z",
"pushed_at": "2026-06-22T17:40:27Z",
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"readme_content": "# Hiring Agent\n\n![\"Page](\"https://img.alicdn.com/imgextra/i4/O1CN01qKig1P1FnhpFKNdi6_!!6000000000532-2-tps-1280-256.png\")
\n![](\"https://www.spiderfoot.net/wp-content/themes/spiderfoot/img/spiderfoot-wide.png\")
![](\"https://www.spiderfoot.net/wp-content/uploads/2022/04/opensource-screenshot-v4.png\")
\n\n### FEATURES\n\n- Web based UI or CLI\n- Over 200 modules (see below)\n- Python 3.7+\n- YAML-configurable [correlation engine](/correlations/README.md) with [37 pre-defined rules](/correlations)\n- CSV/JSON/GEXF export\n- API key export/import\n- SQLite back-end for custom querying\n- Highly configurable\n- Fully documented\n- Visualisations\n- TOR integration for dark web searching\n- Dockerfile for Docker-based deployments\n- Can call other tools like DNSTwist, Whatweb, Nmap and CMSeeK\n- [Actively developed since 2012!](https://medium.com/@micallst/lessons-learned-from-my-10-year-open-source-project-4a4c8c2b4f64)\n\n### WANT MORE?\n\nNeed more from SpiderFoot? Check out [SpiderFoot HX](https://www.spiderfoot.net/hx) for:\n- 100% Cloud-based and managed for you\n- Attack Surface Monitoring with change notifications by email, REST and Slack\n- Multiple targets per scan\n- Multi-user collaboration\n- Authenticated and 2FA\n- Investigations\n- Customer support\n- Third party tools pre-installed & configured\n- Drive it with a fully RESTful API\n- TOR integration built-in\n- Screenshotting\n- Bring your own Python SpiderFoot modules\n- Feed scan data to Splunk, ElasticSearch and REST endpoints\n\nSee the full set of differences between SpiderFoot HX and the open source version [here](https://www.spiderfoot.net/open-source-vs-hx/).\n\n### USES\n\nSpiderFoot can be used offensively (e.g. in a red team exercise or penetration test) for reconnaissance of your target or defensively to gather information about what you or your organisation might have exposed over the Internet.\n\nYou can target the following entities in a SpiderFoot scan:\n\n - IP address\n - Domain/sub-domain name\n - Hostname\n - Network subnet (CIDR)\n - ASN\n - E-mail address\n - Phone number\n - Username\n - Person's name\n - Bitcoin address\n \nSpiderFoot's 200+ modules feed each other in a publisher/subscriber model to ensure maximum data extraction to do things like:\n\n- [Host/sub-domain/TLD enumeration/extraction](https://asciinema.org/a/295912)\n- [Email address, phone number and human name extraction](https://asciinema.org/a/295947)\n- [Bitcoin and Ethereum address extraction](https://asciinema.org/a/295957)\n- [Check for susceptibility to sub-domain hijacking](https://asciinema.org/a/344377)\n- DNS zone transfers\n- [Threat intelligence and Blacklist queries](https://asciinema.org/a/295949)\n- API integration with [SHODAN](https://asciinema.org/a/127601), [HaveIBeenPwned](https://asciinema.org/a/128731), [GreyNoise](https://asciinema.org/a/295943), AlienVault, SecurityTrails, etc.\n- [Social media account enumeration](https://asciinema.org/a/295923)\n- [S3/Azure/Digitalocean bucket enumeration/scraping](https://asciinema.org/a/295941)\n- IP geo-location\n- Web scraping, web content analysis\n- [Image, document and binary file meta data analysis](https://asciinema.org/a/296274)\n- Dark web searches\n- [Port scanning and banner grabbing](https://asciinema.org/a/295939)\n- [Data breach searches](https://asciinema.org/a/296145)\n- So much more...\n\n### INSTALLING & RUNNING\n\nTo install and run SpiderFoot, you need at least Python 3.7 and a number of Python libraries which you can install with `pip`. We recommend you install a packaged release since master will often have bleeding edge features and modules that aren't fully tested.\n\n#### Stable build (packaged release):\n\n```\n wget https://github.com/smicallef/spiderfoot/archive/v4.0.tar.gz\n tar zxvf v4.0.tar.gz\n cd spiderfoot-4.0\n pip3 install -r requirements.txt\n python3 ./sf.py -l 127.0.0.1:5001\n```\n\n#### Development build (cloning git master branch):\n\n```\n git clone https://github.com/smicallef/spiderfoot.git\n cd spiderfoot\n pip3 install -r requirements.txt\n python3 ./sf.py -l 127.0.0.1:5001\n```\n\nCheck out the [documentation](https://www.spiderfoot.net/documentation) and our [asciinema videos](https://asciinema.org/~spiderfoot) for more tutorials.\n\n### COMMUNITY\n\nWhether you're a contributor, user or just curious about SpiderFoot and OSINT in general, we'd love to have you join our community! SpiderFoot now has a [Discord server](https://discord.gg/vyvztrG) for seeking help from the community, requesting features or just general OSINT chit-chat.\n\n### WRITING CORRELATION RULES\n\nWe have a comprehensive write-up and reference of the correlation rule-set introduced in SpiderFoot 4.0 [here](/correlations/README.md).\n\nAlso take a look at the [template.yaml](/correlations/template.yaml) file for a walk through. The existing [37 rules](/correlations) are also quite readable and good as starting points for additional rules.\n\n### MODULES / INTEGRATIONS\n\nSpiderFoot has over 200 modules, most of which *don't require API keys*, and many of those that do require API keys *have a free tier*.\n\n| Name | Description | Type |\n|:---------| :-----------|:-------|\n[AbstractAPI](https://app.abstractapi.com/)|Look up domain, phone and IP address information from AbstractAPI.|Tiered API\n[abuse.ch](https://www.abuse.ch)|Check if a host/domain, IP address or netblock is malicious according to Abuse.ch.|Free API\n[AbuseIPDB](https://www.abuseipdb.com)|Check if an IP address is malicious according to AbuseIPDB.com blacklist.|Tiered API\n[Abusix Mail Intelligence](https://abusix.org/)|Check if a netblock or IP address is in the Abusix Mail Intelligence blacklist.|Tiered API\nAccount Finder|Look for possible associated accounts on over 500 social and other websites such as Instagram, Reddit, etc.|Internal\n[AdBlock Check](https://adblockplus.org/)|Check if linked pages would be blocked by AdBlock Plus.|Tiered API\n[AdGuard DNS](https://adguard.com/)|Check if a host would be blocked by AdGuard DNS.|Free API\n[Ahmia](https://ahmia.fi/)|Search Tor 'Ahmia' search engine for mentions of the target.|Free API\n[AlienVault IP Reputation](https://cybersecurity.att.com/)|Check if an IP or netblock is malicious according to the AlienVault IP Reputation database.|Free API\n[AlienVault OTX](https://otx.alienvault.com/)|Obtain information from AlienVault Open Threat Exchange (OTX)|Tiered API\n[Amazon S3 Bucket Finder](https://aws.amazon.com/s3/)|Search for potential Amazon S3 buckets associated with the target and attempt to list their contents.|Free API\n[Apple iTunes](https://itunes.apple.com/)|Search Apple iTunes for mobile apps.|Free API\n[Archive.org](https://archive.org/)|Identifies historic versions of interesting files/pages from the Wayback Machine.|Free API\n[ARIN](https://www.arin.net/)|Queries ARIN registry for contact information.|Free API\n[Azure Blob Finder](https://azure.microsoft.com/en-in/services/storage/blobs/)|Search for potential Azure blobs associated with the target and attempt to list their contents.|Free API\nBase64 Decoder|Identify Base64-encoded strings in URLs, often revealing interesting hidden information.|Internal\n[BGPView](https://bgpview.io/)|Obtain network information from BGPView API.|Free API\nBinary String Extractor|Attempt to identify strings in binary content.|Internal\n[BinaryEdge](https://www.binaryedge.io/)|Obtain information from BinaryEdge.io Internet scanning systems, including breaches, vulnerabilities, torrents and passive DNS.|Tiered API\n[Bing (Shared IPs)](https://www.bing.com/)|Search Bing for hosts sharing the same IP.|Tiered API\n[Bing](https://www.bing.com/)|Obtain information from bing to identify sub-domains and links.|Tiered API\nBitcoin Finder|Identify bitcoin addresses in scraped webpages.|Internal\n[Bitcoin Who's Who](https://bitcoinwhoswho.com/)|Check for Bitcoin addresses against the Bitcoin Who's Who database of suspect/malicious addresses.|Tiered API\n[BitcoinAbuse](https://www.bitcoinabuse.com/)|Check Bitcoin addresses against the bitcoinabuse.com database of suspect/malicious addresses.|Free API\n[Blockchain](https://www.blockchain.com/)|Queries blockchain.info to find the balance of identified bitcoin wallet addresses.|Free API\n[blocklist.de](http://www.blocklist.de/en/index.html)|Check if a netblock or IP is malicious according to blocklist.de.|Free API\n[BotScout](https://botscout.com/)|Searches BotScout.com's database of spam-bot IP addresses and e-mail addresses.|Tiered API\n[botvrij.eu](https://botvrij.eu/)|Check if a domain is malicious according to botvrij.eu.|Free API\n[BuiltWith](https://builtwith.com/)|Query BuiltWith.com's Domain API for information about your target's web technology stack, e-mail addresses and more.|Tiered API\n[C99](https://api.c99.nl/)|Queries the C99 API which offers various data (geo location, proxy detection, phone lookup, etc).|Commercial API\n[CallerName](http://callername.com/)|Lookup US phone number location and reputation information.|Free API\n[Censys](https://censys.io/)|Obtain host information from Censys.io.|Tiered API\n[Certificate Transparency](https://crt.sh/)|Gather hostnames from historical certificates in crt.sh.|Free API\n[CertSpotter](https://sslmate.com/certspotter/)|Gather information about SSL certificates from SSLMate CertSpotter API.|Tiered API\n[CINS Army List](https://cinsscore.com/)|Check if a netblock or IP address is malicious according to Collective Intelligence Network Security (CINS) Army list.|Free API\n[CIRCL.LU](https://www.circl.lu/)|Obtain information from CIRCL.LU's Passive DNS and Passive SSL databases.|Free API\n[CleanBrowsing.org](https://cleanbrowsing.org/)|Check if a host would be blocked by CleanBrowsing.org DNS content filters.|Free API\n[CleanTalk Spam List](https://cleantalk.org)|Check if a netblock or IP address is on CleanTalk.org's spam IP list.|Free API\n[Clearbit](https://clearbit.com/)|Check for names, addresses, domains and more based on lookups of e-mail addresses on clearbit.com.|Tiered API\n[CloudFlare DNS](https://www.cloudflare.com/)|Check if a host would be blocked by CloudFlare DNS.|Free API\n[CoinBlocker Lists](https://zerodot1.gitlab.io/CoinBlockerListsWeb/)|Check if a domain appears on CoinBlocker lists.|Free API\n[CommonCrawl](http://commoncrawl.org/)|Searches for URLs found through CommonCrawl.org.|Free API\n[Comodo Secure DNS](https://www.comodo.com/secure-dns/)|Check if a host would be blocked by Comodo Secure DNS.|Tiered API\nCompany Name Extractor|Identify company names in any obtained data.|Internal\nCookie Extractor|Extract Cookies from HTTP headers.|Internal\nCountry Name Extractor|Identify country names in any obtained data.|Internal\nCredit Card Number Extractor|Ide",
"manifest_file": "requirements.txt",
"manifest_content": "adblockparser>=0.7,<1\ndnspython>=2.3.0,<3\nExifRead>=2.3.2,<3\nCherryPy>=18.8.0,<19\ncherrypy-cors>=1.6,<2\nMako>=1.2.4,<2\nbeautifulsoup4>=4.11.2,<5\nlxml>=4.9.2,<5\nnetaddr>=0.8.0,<1\npysocks>=1.7.1,<2\nrequests>=2.28.2,<3\nipwhois>=1.1.0,<1.2.0\nipaddr>=2.2.0,<3\nphonenumbers>=8.13.6,<9\npygexf>=0.2.2,<0.3\nPyPDF2>=1.28.6,<2\npython-whois>=0.7.3,<0.8\nsecure>=0.3.0,<0.4.0\npyOpenSSL>=21.0.0,<22\npython-docx>=0.8.11,<0.9\npython-pptx>=0.6.21,<0.7\nnetworkx>=2.6.3,<2.7\ncryptography>=3.4.8,<4\npublicsuffixlist>=0.9.3,<0.10\nopenpyxl>=3.1.1,<4\npyyaml>=6.0.0,<7\n",
"strategic_keywords": [
"rag",
"workflow",
"automation"
],
"relationship_label": "Workspace 组件",
"data_confidence": "high",
"evidence_sources": [
"github_trending",
"github_repo_api",
"readme",
"requirements.txt"
],
"score_breakdown": {
"heat": 20,
"relevance": 20,
"novelty": 8,
"productize": 14,
"adoption": 10,
"relation": 9,
"risk_signal": 6,
"total": 87
},
"strategic_score": 87
},
{
"owner": "vercel-labs",
"name": "agent-browser",
"full_name": "vercel-labs/agent-browser",
"url": "https://github.com/vercel-labs/agent-browser",
"description": "Browser automation CLI for AI agents",
"language": "Rust",
"total_stars": 37135,
"forks": 2366,
"stars_this_period": 775,
"source_slice": "rust",
"source_slices": [
"rust"
],
"metadata": {
"topics": [],
"license": "Apache-2.0",
"open_issues": 540,
"created_at": "2026-01-11T05:38:15Z",
"pushed_at": "2026-06-25T00:48:22Z",
"homepage": "https://agent-browser.dev",
"default_branch": "main",
"forks": 2366,
"watchers": 98,
"archived": false,
"size_kb": 17801
},
"readme_content": "# agent-browser\n\nBrowser automation CLI for AI agents. Fast native Rust CLI.\n\n[](https://skills.sh/vercel-labs/agent-browser)\n\n## Installation\n\n### Global Installation (recommended)\n\nInstalls the native Rust binary:\n\n```bash\nnpm install -g agent-browser\nagent-browser install # Download Chrome from Chrome for Testing (first time only)\n```\n\n### Project Installation (local dependency)\n\nFor projects that want to pin the version in `package.json`:\n\n```bash\nnpm install agent-browser\nagent-browser install\n```\n\nThen use via `package.json` scripts or by invoking `agent-browser` directly.\n\n### Homebrew (macOS)\n\n```bash\nbrew install agent-browser\nagent-browser install # Download Chrome from Chrome for Testing (first time only)\n```\n\n### Cargo (Rust)\n\n```bash\ncargo install agent-browser\nagent-browser install # Download Chrome from Chrome for Testing (first time only)\n```\n\n### From Source\n\nRequires Node.js 24+, pnpm 11+, and Rust.\n\n```bash\ngit clone https://github.com/vercel-labs/agent-browser\ncd agent-browser\npnpm install\npnpm build\npnpm build:native # Requires Rust (https://rustup.rs)\npnpm link --global # Makes agent-browser available globally\nagent-browser install\n```\n\n### Linux Dependencies\n\nOn Linux, install system dependencies:\n\n```bash\nagent-browser install --with-deps\n```\n\nThis exits nonzero if the package manager cannot install every required browser library.\n\n### Updating\n\nUpgrade to the latest version:\n\n```bash\nagent-browser upgrade\n```\n\nDetects your installation method (npm, Homebrew, or Cargo) and runs the appropriate update command automatically.\n\n### Requirements\n\n- **Chrome** - Run `agent-browser install` to download Chrome from [Chrome for Testing](https://developer.chrome.com/blog/chrome-for-testing/) (Google's official automation channel). Existing Chrome, Brave, Playwright, and Puppeteer installations are detected automatically. No Playwright or Node.js required for the daemon.\n- **Node.js 24+ and pnpm 11+** - Only needed when building from source.\n- **Rust** - Only needed when building from source (see From Source above).\n\n## Quick Start\n\n```bash\nagent-browser open example.com\nagent-browser snapshot # Get accessibility tree with refs\nagent-browser click @e2 # Click by ref from snapshot\nagent-browser fill @e3 \"test@example.com\" # Fill by ref\nagent-browser get text @e1 # Get text by ref\nagent-browser screenshot page.png\nagent-browser close\n```\n\nClicks fail early when another element covers the target's click point, for example a consent banner or modal. Dismiss or interact with the reported covering element, then take a fresh snapshot before retrying the original ref.\n\nHeadless Chromium screenshots hide native scrollbars for consistent image output. Pass `--hide-scrollbars false` when launching to keep native scrollbars visible.\n\n### Traditional Selectors (also supported)\n\n```bash\nagent-browser click \"#submit\"\nagent-browser fill \"#email\" \"test@example.com\"\nagent-browser find role button click --name \"Submit\"\n```\n\n## Commands\n\n### Core Commands\n\n```bash\nagent-browser open # Launch browser (no navigation); stays on about:blank\nagent-browser open ![\"Intelligent](\"./docs/images/qa.png\")
![\"Wiki](\"./docs/images/wiki-browser.png\")
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