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

2. Search for llms.txt WebSearch: "[library name] llms.txt site:[docs domain]" 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:

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:

1. Find GitHub repository via WebSearch
2. Use Repomix to pack repository: bash npm install -g repomix # if needed git clone [repo-url] /tmp/docs-analysis cd /tmp/docs-analysis repomix --output repomix-output.xml
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

# 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 → 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: - 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. Always start with llms.txt — Most efficient method
2. Use parallel agents aggressively — Faster results, better coverage
3. Verify official sources — Avoid outdated documentation
4. Report methodology — Tell user which approach was used
5. Handle versions explicitly — Don't assume latest

Detailed Documentation

For comprehensive guides, examples, and best practices:

Workflows: - WORKFLOWS.md — Detailed workflow examples and strategies

Reference guides: - Tool Selection — Complete guide to choosing and using tools - Documentation Sources — Common sources and patterns across ecosystems - Error Handling — Troubleshooting and resolution strategies - Best Practices — 8 essential principles for effective discovery - Performance — Optimization techniques and benchmarks - Limitations — Boundaries and success criteria