Local Doc Rag Skill

AutoDoc SkillBase: Local Documentation Indexing for AI Agent Skills

[](https://camilemuz.github.io/local-doc-rag-skill/)

The Knowledge Fabric Weaver 🧠

AutoDoc SkillBase transforms scattered documentation into a unified, AI-accessible knowledge fabric. Imagine treating every README, API reference, and internal wiki as a thread in a tapestry that your AI agents can weave through in milliseconds. This isn't another note-taking tool — it's a *skill extraction engine* that teaches Claude and other AI models to think in your domain's language.

**Built for 2026's AI-first workflows**, this system indexes documentation locally, converts it into structured skill files, and exposes them as contextual tools for any AI agent via OpenAI API and Claude API integration. Think of it as giving your AI a photographic memory of every technical document you've ever read.

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Why This Exists 🌍

Traditional RAG systems treat documentation as a passive library to query. AutoDoc SkillBase treats documentation as an *active skill* — something the AI can internalize and apply without constant context-switching. The difference is the same as reading a cookbook versus having a sous chef who already knows the recipe.

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Mermaid Diagram: How Knowledge Becomes Skill

flowchart LR
    A[Local Docs] --> B[AutoDoc Indexer]
    B --> C{Skill Extraction}
    C --> D[Structured JSON Skills]
    C --> E[Markdown Summaries]
    C --> F[Contextual Embeddings]
    D --> G[Claude API]
    E --> H[OpenAI API]
    F --> I[Local Vector Store]
    G --> J[AI Agent Action]
    H --> J
    I --> J
    J --> K[Context-Aware Responses]
    K --> L[User]
    L --> M[Feedback Loop]
    M --> B

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Feature List 🚀

• Local-First Indexing: No data leaves your machine. Security meets accessibility.
• Multi-Format Ingestion: Markdown, HTML, PDF, plaintext, code comments, a