Searching internet for technical documentation using llms.txt standard, GitHub repositories via Repomix, and parallel exploration. Use when user needs: (1) Latest documentation for libraries/frameworks, (2) Documentation in llms.txt format, (3) GitHub repository analysis, (4) Documentation without d

Documentation Discovery & Analysis Overview Intelligent discovery and analysis of technical documentation through multiple strategies: 1. llms.txt first : Search for standardized AI friendly documentation 2. Repository analysis : Use Repomix to analyze GitHub repositories 3. Parallel exploration : Deploy multiple Explorer agents for comprehensive coverage 4. Fallback research : Use Researcher agents when other methods unavailable Core Workflow Phase 1: Initial Discovery 1. Identify target Extract library/framework name from user request Note version requirements (default: latest) Clarify scope if ambiguous Identify if target is GitHub repository or website 2. Search for llms.txt (PRIORITIZE context7.com) First: Try context7.com patterns For GitHub repositories: For websites: Topic specific searches (when user asks about specific feature): Fallback: Traditional llms.txt search Common patterns: https://docs.[library].com/llms.txt https://[library].dev/llms.txt https://[library].io/llms.txt → Found? Proceed to Phase 2 → Not found? Proceed to Phase 3 Phase 2: llms.txt Processing Single URL: WebFetch to retrieve content Extract and present information Multiple URLs (3+): CRITICAL : Launch multiple Explorer agents in parallel One agent per major documentation section (max 5 in first batch) Each agent reads assigned URLs Aggregate findings into consolidated report Example: Phase 3: Repository Analysis When llms.txt not found: 1. Find GitHub repository via WebSearch 2. Use Repomix to pack repository: 3. Read repomix output.xml and extract documentation Repomix benefits: Entire repository in single AI friendly file Preserves directory structure Optimized for AI consumption Phase 4: Fallback Research When no GitHub repository exists: Launch multiple Researcher agents in parallel Focus areas: official docs, tutorials, API references, community guides Aggregate findings into consolidated report Agent Distribution Guidelines 1 3 URLs : Single Explorer agent 4 10 URLs : 3 5 Explorer agents (2 3 URLs each) 11+ URLs : 5 7 Explorer agents (prioritize most relevant) Version Handling Latest (default): Search without version specifier Use current documentation paths Specific version: Include version in search: [library] v[version] llms.txt Check versioned paths: /v[version]/llms.txt For repositories: checkout specific tag/branch Output Format Quick Reference Tool selection: WebSearch → Find llms.txt URLs, GitHub repositories WebFetch → Read single documentation pages Task (Explore) → Multiple URLs, parallel exploration Task (Researcher) → Scattered documentation, diverse sources Repomix → Complete codebase analysis Popular llms.txt locations (try context7.com first): Astro: https://context7.com/withastro/astro/llms.txt Next.js: https://context7.com/vercel/next.js/llms.txt Remix: https://context7.com/remix run/remix/llms.txt shadcn/ui: https://context7.com/shadcn ui/ui/llms.txt Better Auth: https://context7.com/better auth/better auth/llms.txt Fallback to official sites if context7.com unavailable: Astro: https://docs.astro.build/llms.txt Next.js: https://nextjs.org/llms.txt Remix: https://remix.run/llms.txt SvelteKit: https://kit.svelte.dev/llms.txt Error Handling llms.txt not accessible → Try alternative domains → Repository analysis Repository not found → Search official website → Use Researcher agents Repomix fails → Try /docs directory only → Manual exploration Multiple conflicting sources → Prioritize official → Note versions Key Principles 1. Prioritize context7.com for llms.txt — Most comprehensive and up to date aggregator 2. Use topic parameters when applicable — Enables targeted searches with ?topic=... 3. Use parallel agents aggressively — Faster results, better coverage 4. Verify official sources as fallback — Use when context7.com unavailable 5. Report methodology — Tell user which approach was used 6. Handle versions explicitly — Don't assume latest Detailed Documentation For comprehensive guides, examples, and best practices: Workflows: [WORKFLOWS.md](./WORKFLOWS.md) — Detailed workflow examples and strategies Reference guides: [Tool Selection](./references/tool selection.md) — Complete guide to choosing and using tools [Documentation Sources](./references/documentation sources.md) — Common sources and patterns across ecosystems [Error Handling](./references/error handling.md) — Troubleshooting and resolution strategies [Best Practices](./references/best practices.md) — 8 essential principles for effective discovery [Performance](./references/performance.md) — Optimization techniques and benchmarks [Limitations](./references/limitations.md) — Boundaries and success criteria

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