Generate llms.txt indexes from Markdown documentation by category.
npx skills add https://github.com/EdgeHunt/EdgeHunt --skill ck-llms-edgehunt
Please help me install this Agent Skill. Skill: ck:llms Source: https://github.com/EdgeHunt/EdgeHunt/tree/main/.claude/skills/llms Command: npx skills add https://github.com/EdgeHunt/EdgeHunt --skill ck-llms-edgehunt
llms.txt provides a compact, AI-friendly index of a project’s documentation. It enables AI models to access relevant docs without loading an entire site, improving context-sensitivity and retrieval efficiency.
Run the generator on your docs directory to produce llms.txt at the project root.
High-intent search queries and answers about installing and using this skill.
You can generate an llms.txt file by analyzing Markdown sources and grouping them by category. This creates a compact, AI-friendly index following the llmstxt.org specification for AI-driven context retrieval.
The llms.txt format provides a compact, AI-friendly index of a project's documentation. It enables AI models to access relevant context without loading an entire site, improving retrieval efficiency for AI assistants.
Yes, you can optionally generate an llms-full.txt file alongside the standard index. This includes the full Markdown content from your sources, providing complete documentation context for AI assistants.
Yes, the generator supports configurable base URL prefixes for link rendering. This allows you to map local Markdown file paths to absolute web URLs when publishing your documentation index for AI consumption.
Organize Markdown files into logical categories like API Reference, Guides, and Getting Started. The generator groups content by these categories to create a structured, context-sensitive index for AI assistants.
The llms.txt index is ideal for rapid context-building in large repos but relies on Markdown sources. It does not parse non-Markdown formats, so complex PDF or HTML documentation will not be included in the generated AI context index.
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