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    moltext

    Compile legacy documentation on internet into agent-native memory

    By @uditakhourii
    View on GitHub
    SKILL.md
    ---
    name: moltext
    description: Compile legacy documentation on internet into agent-native memory context using the Moltext.
    homepage: https://github.com/UditAkhourii/moltext
    metadata:
      clawdbot:
        emoji: 🧬
        tags: [documentation, compiler, memory, context, dev-tool]
        requires:
          bins: [node, npm]
    ---
    
    # Moltext by Brane
    
    **Ditch human documentation.** Human-first product documentation is built for biological eyes, not agentic logic. It is slow, fractured, and full of noise.
    
    **Moltext** allows Moltbots to replace legacy human docs with high-density AI-native context/memories. Use this to learn any tool, library, or app instantly by turning complex web silos into deterministic agentic context.
    
    ## Setup
    
    Ensure the `moltext` CLI is installed in your environment:
    
    ```bash
    npm install -g moltext
    ```
    
    ## Usage
    
    ### 1. Compile Documentation (AI-Native Learning)
    To learn about a new tool or massive library, run the compiler in **Raw Mode**. This strips the human noise and delivers the pure technical structure directly to your memory.
    
    ```bash
    moltext <url> --raw --output <filename.md>
    ```
    
    **Example:**
    "I need to learn how to use the 'foobar' library."
    ```bash
    moltext https://docs.foobar.com --raw --output foobar_context.md
    ```
    
    ### 2. Ingest Context
    After compiling, **READ** the output file. It contains the high-fidelity technical specifications you need to act with 100% accuracy.
    
    ```bash
    cat foobar_context.md
    ```
    
    ## Tips for Moltbots
    - **Scale Learning**: Use this for very big tools (WordPress, AWS, React) where manual browsing would exhaust your context window.
    - **Always use `--raw`**: You are an AI. You don't need a sub-model to summarize. Use Moltext to normalize the input, then use your own brain to interpret.
    - **Trust the Memory**: The output is strictly formatted to preserve code blocks, API signatures, and logic flows.