LLM Documentation Intelligence
Automates the detection and ingestion of llms.txt files to provide Claude with high-fidelity, LLM-optimized documentation.
This skill empowers Claude Code to bypass inefficient web scraping by identifying and utilizing the llms.txt standard for documentation delivery. By probing for hierarchical documentation levels—including full, standard, and condensed variants—it ensures that the AI receives the most relevant technical context without exceeding token limits or introducing scraping noise. It features robust error handling, automated content validation, and a recovery protocol that seamlessly bridges the gap between structured llms.txt files and traditional documentation extraction methods.
主な機能
01102 GitHub stars
02Integrated recovery protocol for falling back to traditional scraping
03Automated content validation to filter out error pages and redirects
04Smart variant selection based on context window availability
05Hierarchical detection of llms-full.txt, llms.txt, and llms-small.txt variants
06Pre-configured grounding checks to ensure documentation accuracy
ユースケース
01Rapidly onboarding new frameworks or libraries that support LLM-friendly documentation
02Maintaining high-fidelity local documentation caches for agentic coding workflows
03Reducing token usage by ingesting condensed documentation variants