Generates llms.txt files from documentation directories or URLs.
npx skills add https://github.com/lengo0951/pms --skill ck-llms-lengo0951
Please help me install this Agent Skill. Skill: ck:llms Source: https://github.com/lengo0951/pms/tree/main/.claude/skills/llms Command: npx skills add https://github.com/lengo0951/pms --skill ck-llms-lengo0951
This Skill generates LLM-friendly documentation indexes, making it easier for AI systems to find and understand the content of a project's documentation.
Generate an llms.txt index for the current project's documentation using the 'ck:llms' skill.
High-intent search queries and answers about installing and using this skill.
To generate an llms.txt file, scan markdown files in a specified directory or from a URL. The process categorizes documents into sections like API, Guides, and Reference, ensuring all links use valid markdown format for AI discovery.
Yes, you need Python to create an llms.txt index. The process requires Python and specific libraries like pypdf, pdfplumber, and pdf2image for scanning and processing markdown files into an AI-friendly format.
Yes, you can scan documentation from a URL to generate an llms.txt file. The tool scans markdown files from a specified URL or local directory to create a curated index following the llmstxt.org specification.
Documentation categorization organizes scanned markdown files into distinct sections like API, Guides, and Reference. This structured categorization ensures AI systems can efficiently navigate and understand the project documentation content.
The process is limited to scanning markdown files and requires specific Python libraries like pypdf and pdfplumber. It ensures link validation but focuses specifically on generating llms.txt indexes rather than converting other formats into markdown.
eastreamsExtract text and structured data from PDF files using Python libraries.
auxi-wardrobeGenerate llms.txt files from documentation directories following the llmstxt.org specification.
zircoteAudit Markdown documentation structure, formatting, links, and accessibility against defined standards.
BEIRUXPerform LLM-optimized web search and content extraction with JSON output.
