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Uses Claude vision to extract concepts and relationships, supports 20+ programming languages via tree-sitter AST.","sapsapshen\u002Fai-memory-router","sapsapshen","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F20347959?v=4","01M6XDQEF1DP50DKF37H81J3J5","shenmian","01M6XDQEJPE41Y3DT2763X8ZJN",0,"MIT","https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router\u002Fblob\u002Fmain\u002Fskills-store\u002Fhermes\u002Fgraphify\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[5,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42],"coding","tree","papers","concepts","ai coding assistant","programming languages","code-analysis","images","vision","ast","assistant","knowledge","knowledge-graph","analysis","knowledge graph","graph","code","visualization","documentation","2026-11-10 10:12:30",false,"---\nname: graphify\ndescription: AI coding assistant skill that turns any folder of code, docs, papers, or images into a queryable knowledge graph. Uses Claude vision to extract concepts and relationships, supports 20+ programming languages via tree-sitter AST.\ntags: [code-analysis, knowledge-graph, documentation, visualization, ast]\n---\n\n# Graphify Skill\n\nGraphify is an AI coding assistant skill that transforms any folder of code, documentation, papers, or images into a queryable knowledge graph. It uses Claude vision to extract concepts and relationships, and supports 20+ programming languages via tree-sitter AST.\n\n## Features\n\n- **Multimodal analysis**: Works with code, PDFs, markdown, screenshots, diagrams, whiteboard photos, and images\n- **20+ language support**: Python, JavaScript, TypeScript, Go, Rust, Java, C, C++, Ruby, C#, Kotlin, Scala, PHP, Swift, Lua, Zig, PowerShell, Elixir, Objective-C, Julia\n- **Two-pass analysis**: Deterministic AST extraction + Claude subagents for semantic analysis\n- **Interactive output**: HTML graph visualization, JSON queryable graph, and audit report\n- **Persistent cache**: SHA256-based caching for incremental updates\n\n## Installation\n\nGraphify requires Python 3.10+ and the `graphifyy` package. Install it with:\n\n```bash\n# Create virtual environment (if needed)\npython3 -m venv ~\u002F.hermes\u002Fvenv\u002Fgraphify\nsource ~\u002F.hermes\u002Fvenv\u002Fgraphify\u002Fbin\u002Factivate\n\n# Install graphifyy\npip install graphifyy\n```\n\n## Usage\n\n### Basic Usage\n\nTo analyze a directory and create a knowledge graph:\n\n```bash\n# Activate the virtual environment first\nsource ~\u002F.hermes\u002Fvenv\u002Fgraphify\u002Fbin\u002Factivate\n\n# Run graphify on a directory\ngraphify \u002Fpath\u002Fto\u002Fyour\u002Fcodebase\n```\n\nOr from within Hermes:\n\n```bash\nterminal \"source ~\u002F.hermes\u002Fvenv\u002Fgraphify\u002Fbin\u002Factivate && graphify .\"\n```\n\n### Output Structure\n\nGraphify creates a `graphify-out\u002F` directory with:\n\n- `graph.html` - Interactive graph visualization (click nodes, search, filter)\n- `GRAPH_REPORT.md` - Analysis report with god nodes, surprising connections, suggested questions\n- `graph.json` - Persistent graph data for querying later\n- `cache\u002F` - SHA256 cache for incremental updates\n\n### Querying the Graph\n\nAfter building a graph, you can query it:\n\n```bash\n# Query the graph with a question\ngraphify query \"How does authentication work in this codebase?\" --graph graphify-out\u002Fgraph.json\n\n# Use DFS instead of BFS\ngraphify query \"Find all database-related functions\" --dfs\n\n# Limit output tokens\ngraphify query \"Explain the architecture\" --budget 1000\n```\n\n### Platform Integration\n\nTo make your AI assistant always use the graph:\n\n```bash\n# For Hermes\u002FOpenClaw-like environments\ngraphify claw install\n```\n\nThis writes graph-aware rules to `AGENTS.md` in your project root.\n\n### Excluding Files\n\nCreate a `.graphifyignore` file to exclude directories:\n\n```\n# .graphifyignore\nnode_modules\u002F\nvendor\u002F\ndist\u002F\n*.generated.py\n```\n\n## Examples\n\n### 1. Analyze Current Directory\n\n```bash\ncd \u002Fpath\u002Fto\u002Fproject\nsource ~\u002F.hermes\u002Fvenv\u002Fgraphify\u002Fbin\u002Factivate\ngraphify .\n```\n\n### 2. Query Specific Architecture Questions\n\n```bash\ngraphify query \"What are the main components and their relationships?\" --graph graphify-out\u002Fgraph.json\ngraphify query \"Show me all API endpoints\" --graph graphify-out\u002Fgraph.json\ngraphify query \"How is error handling implemented?\" --graph graphify-out\u002Fgraph.json\n```\n\n### 3. Save Query Results for Feedback Loop\n\n```bash\ngraphify save-result --question \"How does authentication work?\" --answer \"Authentication uses JWT tokens...\" --type query --nodes auth.js user.js\n```\n\n### 4. Benchmark Token Reduction\n\n```bash\ngraphify benchmark graphify-out\u002Fgraph.json\n```\n\n## How It Works\n\n1. **AST Pass**: Extracts structure from code files (classes, functions, imports, call graphs) using tree-sitter\n2. **Claude Subagents**: Run in parallel over docs, papers, images to extract concepts and relationships\n3. **Graph Construction**: Merges results into a NetworkX graph with Leiden community detection\n4. **Output Generation**: Creates interactive HTML, queryable JSON, and audit report\n\n## Relationship Tags\n\nEvery relationship is tagged for transparency:\n- `EXTRACTED`: Found directly in source\n- `INFERRED`: Reasonable inference with confidence score\n- `AMBIGUOUS`: Flagged for review\n\n## Tips\n\n1. **Start small**: Run on a single directory first to understand the output\n2. **Use .graphifyignore**: Exclude build artifacts and dependencies\n3. **Check GRAPH_REPORT.md**: Always review the audit report first\n4. **Query strategically**: Start with broad questions, then drill down\n5. **Save useful queries**: Use `save-result` to build a knowledge base\n\n## Troubleshooting\n\n### Common Issues\n\n1. **Missing dependencies**: Ensure all tree-sitter language parsers are installed\n2. **Memory issues**: For large codebases, exclude non-essential directories\n3. **Claude API limits**: Graphify uses Claude for semantic analysis; ensure API access\n\n### Verification\n\n```bash\n# Check graphify installation\nsource ~\u002F.hermes\u002Fvenv\u002Fgraphify\u002Fbin\u002Factivate\ngraphify --help\n\n# Test with a small directory\nmkdir test-graphify && cd test-graphify\necho \"def hello(): print('world')\" > test.py\ngraphify .\n```\n\n## Related Skills\n\n- `graph-analysis`: Network analysis with NetworkX\n- `codebase-inspection`: Basic codebase statistics\n- `ontology`: Knowledge graph management","# Graphify Skill\n\nGraphify is an AI coding assistant skill that transforms any folder of code, documentation, papers, or images into a queryable knowledge graph. It uses Claude vision to extract concepts and relationships, and supports 20+ programming languages via tree-sitter AST.\n\n## Features\n\n- **Multimodal analysis**: Works with code, PDFs, markdown, screenshots, diagrams, whiteboard photos, and images\n- **20+ language support**: Python, JavaScript, TypeScript, Go, Rust, Java, C, C++, Ruby, C#, Kotlin, Scala, PHP, Swift, Lua, Zig, PowerShell, Elixir, Objective-C, Julia\n- **Two-pass analysis**: Deterministic AST extraction + Claude subagents for semantic analysis\n- **Interactive output**: HTML graph visualization, JSON queryable graph, and audit report\n- **Persistent cache**: SHA256-based caching for incremental updates\n\n## Installation\n\nGraphify requires Python 3.10+ and the `graphifyy` package. Install it with:\n\n```bash\n# Create virtual environment (if needed)\npython3 -m venv ~\u002F.hermes\u002Fvenv\u002Fgraphify\nsource ~\u002F.hermes\u002Fvenv\u002Fgraphify\u002Fbin\u002Factivate\n\n# Install graphifyy\npip install graphifyy\n```\n\n## Usage\n\n### Basic Usage\n\nTo analyze a directory and create a knowledge graph:\n\n```bash\n# Activate the virtual environment first\nsource ~\u002F.hermes\u002Fvenv\u002Fgraphify\u002Fbin\u002Factivate\n\n# Run graphify on a directory\ngraphify \u002Fpath\u002Fto\u002Fyour\u002Fcodebase\n```\n\nOr from within Hermes:\n\n```bash\nterminal \"source ~\u002F.hermes\u002Fvenv\u002Fgraphify\u002Fbin\u002Factivate && graphify .\"\n```\n\n### Output Structure\n\nGraphify creates a `graphify-out\u002F` directory with:\n\n- `graph.html` - Interactive graph visualization (click nodes, search, filter)\n- `GRAPH_REPORT.md` - Analysis report with god nodes, surprising connections, suggested questions\n- `graph.json` - Persistent graph data for querying later\n- `cache\u002F` - SHA256 cache for incremental updates\n\n### Querying the Graph\n\nAfter building a graph, you can query it:\n\n```bash\n# Query the graph with a question\ngraphify query \"How does authentication work in this codebase?\" --graph graphify-out\u002Fgraph.json\n\n# Use DFS instead of BFS\ngraphify query \"Find all database-related functions\" --dfs\n\n# Limit output tokens\ngraphify query \"Explain the architecture\" --budget 1000\n```\n\n### Platform Integration\n\nTo make your AI assistant always use the graph:\n\n```bash\n# For Hermes\u002FOpenClaw-like environments\ngraphify claw install\n```\n\nThis writes graph-aware rules to `AGENTS.md` in your project root.\n\n### Excluding Files\n\nCreate a `.graphifyignore` file to exclude directories:\n\n```\n# .graphifyignore\nnode_modules\u002F\nvendor\u002F\ndist\u002F\n*.generated.py\n```\n\n## Examples\n\n### 1. Analyze Current Directory\n\n```bash\ncd \u002Fpath\u002Fto\u002Fproject\nsource ~\u002F.hermes\u002Fvenv\u002Fgraphify\u002Fbin\u002Factivate\ngraphify .\n```\n\n### 2. Query Specific Architecture Questions\n\n```bash\ngraphify query \"What are the main components and their relationships?\" --graph graphify-out\u002Fgraph.json\ngraphify query \"Show me all API endpoints\" --graph graphify-out\u002Fgraph.json\ngraphify query \"How is error handling implemented?\" --graph graphify-out\u002Fgraph.json\n```\n\n### 3. Save Query Results for Feedback Loop\n\n```bash\ngraphify save-result --question \"How does authentication work?\" --answer \"Authentication uses JWT tokens...\" --type query --nodes auth.js user.js\n```\n\n### 4. Benchmark Token Reduction\n\n```bash\ngraphify benchmark graphify-out\u002Fgraph.json\n```\n\n## How It Works\n\n1. **AST Pass**: Extracts structure from code files (classes, functions, imports, call graphs) using tree-sitter\n2. **Claude Subagents**: Run in parallel over docs, papers, images to extract concepts and relationships\n3. **Graph Construction**: Merges results into a NetworkX graph with Leiden community detection\n4. **Output Generation**: Creates interactive HTML, queryable JSON, and audit report\n\n## Relationship Tags\n\nEvery relationship is tagged for transparency:\n- `EXTRACTED`: Found directly in source\n- `INFERRED`: Reasonable inference with confidence score\n- `AMBIGUOUS`: Flagged for review\n\n## Tips\n\n1. **Start small**: Run on a single directory first to understand the output\n2. **Use .graphifyignore**: Exclude build artifacts and dependencies\n3. **Check GRAPH_REPORT.md**: Always review the audit report first\n4. **Query strategically**: Start with broad questions, then drill down\n5. **Save useful queries**: Use `save-result` to build a knowledge base\n\n## Troubleshooting\n\n### Common Issues\n\n1. **Missing dependencies**: Ensure all tree-sitter language parsers are installed\n2. **Memory issues**: For large codebases, exclude non-essential directories\n3. **Claude API limits**: Graphify uses Claude for semantic analysis; 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