Generate llms.txt and llms-full.txt files from Markdown docs.
npx skills add https://github.com/DatTran26/KienTruThiHanh --skill ck-llms-dattran26
Please help me install this Agent Skill. Skill: ck:llms Source: https://github.com/DatTran26/KienTruThiHanh/tree/main/.agents/skills/llms Command: npx skills add https://github.com/DatTran26/KienTruThiHanh --skill ck-llms-dattran26
Generates standardized llms.txt indexes from a project's Markdown/docs to enable fast, AI-friendly documentation discovery and context building.
Run the generator against your docs folder to produce llms.txt and optionally llms-full.txt.
High-intent search queries and answers about installing and using this skill.
To generate llms.txt files from Markdown documentation, scan your docs directory to extract H1 titles and descriptions, then group items by category and format links following the llmstxt.org specification. You can output llms.txt to a configurable location with an optional base URL prefix.
An llms.txt file is a standardized index that enables AI-friendly documentation discovery and context building. You need it to provide language models with concise descriptions and links to your project's Markdown docs, allowing fast and accurate retrieval of relevant context.
Yes, you can index MDX files alongside standard Markdown for AI discovery. The generator scans both Markdown and MDX files under your target directory, extracts H1 titles and first descriptive paragraphs, and groups them by categories like Getting Started or API Reference.
Yes, the generated llms.txt supports a base URL prefix for CI/CD and static site integration. You can configure the output path and set a base URL so the formatted links point to the correct hosted documentation locations.
The best way to create an llms-full.txt file with full documentation content is to use the generator's optional expanded output mode. Alongside the standard llms.txt index, it produces the optional llms-full.txt file following the llmstxt.org specification with complete text.
Documentation indexing extracts categories and descriptions from Markdown docs by analyzing each file to capture the H1 title and the first descriptive paragraph. It then groups items by inferred categories such as Getting Started, API Reference, and Guides to structure the output.
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lengo0951Generates llms.txt files from documentation directories or URLs.
