docs-seeker
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 direct llms.txt support, (5) Multiple documentation sources in parallel
$ Installieren
git clone https://github.com/einverne/dotfiles /tmp/dotfiles && cp -r /tmp/dotfiles/claude/skills/docs-seeker ~/.claude/skills/dotfiles// tip: Run this command in your terminal to install the skill
name: docs-seeker description: "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 direct llms.txt support, (5) Multiple documentation sources in parallel" version: 1.0.0
Documentation Discovery & Analysis
Overview
Intelligent discovery and analysis of technical documentation through multiple strategies:
- llms.txt-first: Search for standardized AI-friendly documentation
- Repository analysis: Use Repomix to analyze GitHub repositories
- Parallel exploration: Deploy multiple Explorer agents for comprehensive coverage
- Fallback research: Use Researcher agents when other methods unavailable
Core Workflow
Phase 1: Initial Discovery
-
Identify target
- Extract library/framework name from user request
- Note version requirements (default: latest)
- Clarify scope if ambiguous
-
Search for llms.txt
WebSearch: "[library name] llms.txt site:[docs domain]"Common patterns:
https://docs.[library].com/llms.txthttps://[library].dev/llms.txthttps://[library].io/llms.txt
â Found? Proceed to Phase 2 â 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:
Launch 3 Explorer agents simultaneously:
- Agent 1: getting-started.md, installation.md
- Agent 2: api-reference.md, core-concepts.md
- Agent 3: examples.md, best-practices.md
Phase 3: Repository Analysis
When llms.txt not found:
- Find GitHub repository via WebSearch
- Use Repomix to pack repository:
npm install -g repomix # if needed git clone [repo-url] /tmp/docs-analysis cd /tmp/docs-analysis repomix --output repomix-output.xml - 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
# Documentation for [Library] [Version]
## Source
- Method: [llms.txt / Repository / Research]
- URLs: [list of sources]
- Date accessed: [current date]
## Key Information
[Extracted relevant information organized by topic]
## Additional Resources
[Related links, examples, references]
## Notes
[Any limitations, missing information, or caveats]
Quick Reference
Tool selection:
- WebSearch â Find llms.txt URLs, GitHub repositories
- WebFetch â Read single documentation pages
- Task (Explore) â Multiple URLs, parallel exploration
- Task (Researcher) â Scattered documentation, diverse sources
- Repomix â Complete codebase analysis
Popular llms.txt locations:
- 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 â Try alternative domains â Repository analysis
- Repository not found â Search official website â Use Researcher agents
- Repomix fails â Try /docs directory only â Manual exploration
- Multiple conflicting sources â Prioritize official â Note versions
Key Principles
- Always start with llms.txt â Most efficient method
- Use parallel agents aggressively â Faster results, better coverage
- Verify official sources â Avoid outdated documentation
- Report methodology â Tell user which approach was used
- Handle versions explicitly â Don't assume latest
Detailed Documentation
For comprehensive guides, examples, and best practices:
Workflows:
- WORKFLOWS.md â Detailed workflow examples and strategies
Reference guides:
- Tool Selection â Complete guide to choosing and using tools
- Documentation Sources â Common sources and patterns across ecosystems
- Error Handling â Troubleshooting and resolution strategies
- Best Practices â 8 essential principles for effective discovery
- Performance â Optimization techniques and benchmarks
- Limitations â Boundaries and success criteria
Repository
