11_llmstxt_doc_parsing_skill

Overview

This skill rapidly ingests project documentation via the /llms.txt convention to give an agent a fast-track understanding of libraries and APIs. It fetches a curated list of markdown files, consolidates them into a single knowledge artifact, and enables immediate, accurate responses without scraping entire sites. Implemented as a PowerShell utility, it outputs a machine-readable index and an optimized consolidated doc.

How this skill works

The script checks the provided base URL for llms.txt or llms-full.txt and parses the file for project metadata and markdown links. It then fetches the referenced markdown files (up to the configured limit), counts tokens for each file, and writes DOCS_INDEX.json plus CONSOLIDATED_KNOWLEDGE.md. After consolidation, the agent reads the single file for instant familiarity with the library or API.

When to use it

• You need rapid familiarity with a new framework or API without crawling the entire site
• Documentation providers publish an llms.txt manifest to speed LLM consumption
• Preparing a code assistant to answer detailed questions about a library before coding
• Onboarding agents to third-party SDKs during runtime or in CI pipelines

Best practices

• Provide the exact project docs base URL or the direct llms.txt link to avoid redirects
• Set a sensible --max-files to balance coverage vs. fetch time (default 10)
• Use a dedicated output directory (default .docs) to keep artifacts isolated
• Validate that the target site intentionally exposes llms.txt to respect owner intent
• Review DOCS_INDEX.json after fetch to confirm token counts and included files

Example use cases

• Agent prepares to answer API usage questions by ingesting a library’s llms.txt and producing a consolidated cheat sheet
• CI job runs the fetch before integration tests so agents have authoritative API docs available
• Support engineers rapidly build a knowledge snapshot for troubleshooting third-party SDK behavior
• Security review: fetch manifest and scan consolidated content for deprecated or risky API usage