208 lines
7.3 KiB
Markdown
208 lines
7.3 KiB
Markdown
---
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name: docs-seeker
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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"
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version: 1.0.0
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---
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# Documentation Discovery & Analysis
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## Overview
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Intelligent discovery and analysis of technical documentation through multiple strategies:
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1. **llms.txt-first**: Search for standardized AI-friendly documentation
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2. **Repository analysis**: Use Repomix to analyze GitHub repositories
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3. **Parallel exploration**: Deploy multiple Explorer agents for comprehensive coverage
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4. **Fallback research**: Use Researcher agents when other methods unavailable
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## Core Workflow
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### Phase 1: Initial Discovery
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1. **Identify target**
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- Extract library/framework name from user request
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- Note version requirements (default: latest)
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- Clarify scope if ambiguous
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- Identify if target is GitHub repository or website
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2. **Search for llms.txt (PRIORITIZE context7.com)**
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**First: Try context7.com patterns**
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For GitHub repositories:
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```
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Pattern: https://context7.com/{org}/{repo}/llms.txt
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Examples:
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- https://github.com/imagick/imagick → https://context7.com/imagick/imagick/llms.txt
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- https://github.com/vercel/next.js → https://context7.com/vercel/next.js/llms.txt
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- https://github.com/better-auth/better-auth → https://context7.com/better-auth/better-auth/llms.txt
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```
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For websites:
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```
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Pattern: https://context7.com/websites/{normalized-domain-path}/llms.txt
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Examples:
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- https://docs.imgix.com/ → https://context7.com/websites/imgix/llms.txt
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- https://docs.byteplus.com/en/docs/ModelArk/ → https://context7.com/websites/byteplus_en_modelark/llms.txt
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- https://docs.haystack.deepset.ai/docs → https://context7.com/websites/haystack_deepset_ai/llms.txt
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- https://ffmpeg.org/doxygen/8.0/ → https://context7.com/websites/ffmpeg_doxygen_8_0/llms.txt
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```
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**Topic-specific searches** (when user asks about specific feature):
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```
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Pattern: https://context7.com/{path}/llms.txt?topic={query}
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Examples:
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- https://context7.com/shadcn-ui/ui/llms.txt?topic=date
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- https://context7.com/shadcn-ui/ui/llms.txt?topic=button
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- https://context7.com/vercel/next.js/llms.txt?topic=cache
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- https://context7.com/websites/ffmpeg_doxygen_8_0/llms.txt?topic=compress
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```
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**Fallback: Traditional llms.txt search**
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```
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WebSearch: "[library name] llms.txt site:[docs domain]"
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```
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Common patterns:
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- `https://docs.[library].com/llms.txt`
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- `https://[library].dev/llms.txt`
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- `https://[library].io/llms.txt`
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→ Found? Proceed to Phase 2
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→ Not found? Proceed to Phase 3
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### Phase 2: llms.txt Processing
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**Single URL:**
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- WebFetch to retrieve content
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- Extract and present information
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**Multiple URLs (3+):**
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- **CRITICAL**: Launch multiple Explorer agents in parallel
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- One agent per major documentation section (max 5 in first batch)
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- Each agent reads assigned URLs
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- Aggregate findings into consolidated report
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Example:
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```
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Launch 3 Explorer agents simultaneously:
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- Agent 1: getting-started.md, installation.md
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- Agent 2: api-reference.md, core-concepts.md
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- Agent 3: examples.md, best-practices.md
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```
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### Phase 3: Repository Analysis
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**When llms.txt not found:**
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1. Find GitHub repository via WebSearch
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2. Use Repomix to pack repository:
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```bash
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npm install -g repomix # if needed
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git clone [repo-url] /tmp/docs-analysis
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cd /tmp/docs-analysis
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repomix --output repomix-output.xml
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```
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3. Read repomix-output.xml and extract documentation
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**Repomix benefits:**
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- Entire repository in single AI-friendly file
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- Preserves directory structure
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- Optimized for AI consumption
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### Phase 4: Fallback Research
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**When no GitHub repository exists:**
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- Launch multiple Researcher agents in parallel
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- Focus areas: official docs, tutorials, API references, community guides
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- Aggregate findings into consolidated report
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## Agent Distribution Guidelines
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- **1-3 URLs**: Single Explorer agent
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- **4-10 URLs**: 3-5 Explorer agents (2-3 URLs each)
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- **11+ URLs**: 5-7 Explorer agents (prioritize most relevant)
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## Version Handling
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**Latest (default):**
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- Search without version specifier
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- Use current documentation paths
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**Specific version:**
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- Include version in search: `[library] v[version] llms.txt`
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- Check versioned paths: `/v[version]/llms.txt`
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- For repositories: checkout specific tag/branch
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## Output Format
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```markdown
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# Documentation for [Library] [Version]
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## Source
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- Method: [llms.txt / Repository / Research]
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- URLs: [list of sources]
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- Date accessed: [current date]
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## Key Information
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[Extracted relevant information organized by topic]
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## Additional Resources
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[Related links, examples, references]
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## Notes
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[Any limitations, missing information, or caveats]
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```
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## Quick Reference
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**Tool selection:**
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- WebSearch → Find llms.txt URLs, GitHub repositories
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- WebFetch → Read single documentation pages
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- Task (Explore) → Multiple URLs, parallel exploration
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- Task (Researcher) → Scattered documentation, diverse sources
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- Repomix → Complete codebase analysis
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**Popular llms.txt locations (try context7.com first):**
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- Astro: https://context7.com/withastro/astro/llms.txt
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- Next.js: https://context7.com/vercel/next.js/llms.txt
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- Remix: https://context7.com/remix-run/remix/llms.txt
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- shadcn/ui: https://context7.com/shadcn-ui/ui/llms.txt
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- Better Auth: https://context7.com/better-auth/better-auth/llms.txt
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**Fallback to official sites if context7.com unavailable:**
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- Astro: https://docs.astro.build/llms.txt
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- Next.js: https://nextjs.org/llms.txt
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- Remix: https://remix.run/llms.txt
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- SvelteKit: https://kit.svelte.dev/llms.txt
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## Error Handling
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- **llms.txt not accessible** → Try alternative domains → Repository analysis
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- **Repository not found** → Search official website → Use Researcher agents
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- **Repomix fails** → Try /docs directory only → Manual exploration
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- **Multiple conflicting sources** → Prioritize official → Note versions
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## Key Principles
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1. **Prioritize context7.com for llms.txt** — Most comprehensive and up-to-date aggregator
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2. **Use topic parameters when applicable** — Enables targeted searches with ?topic=...
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3. **Use parallel agents aggressively** — Faster results, better coverage
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4. **Verify official sources as fallback** — Use when context7.com unavailable
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5. **Report methodology** — Tell user which approach was used
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6. **Handle versions explicitly** — Don't assume latest
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## Detailed Documentation
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For comprehensive guides, examples, and best practices:
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**Workflows:**
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- [WORKFLOWS.md](./WORKFLOWS.md) — Detailed workflow examples and strategies
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**Reference guides:**
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- [Tool Selection](./references/tool-selection.md) — Complete guide to choosing and using tools
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- [Documentation Sources](./references/documentation-sources.md) — Common sources and patterns across ecosystems
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- [Error Handling](./references/error-handling.md) — Troubleshooting and resolution strategies
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- [Best Practices](./references/best-practices.md) — 8 essential principles for effective discovery
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- [Performance](./references/performance.md) — Optimization techniques and benchmarks
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- [Limitations](./references/limitations.md) — Boundaries and success criteria
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