Research Methodology for Documentation

This skill provides systematic approach to researching technical documentation using WebSearch and WebFetch tools.

Core Principles

1. •Validate before research - Ensure request is specific enough
2. •Check local first - Look in .claude/knowledge/ before searching
3. •Official sources priority - Start with official docs
4. •Filter aggressively - Extract only what's relevant to context
5. •Save for reuse - Document findings in standard format

Request Validation

A valid research request must contain three elements:

If any element is missing, return validation error and request clarification.

Search Strategy

Query Formulation

Build queries progressively:

Level 1 (Official): {technology} official documentation {topic}
Level 2 (Tutorial): {technology} {topic} tutorial example
Level 3 (Problem): {technology} {topic} {error-message} solution

Source Hierarchy

Prioritize sources in this order:

1. •

   Official documentation (always check first)

   • •react.dev, docs.python.org, effect.website
   • •GitHub official repos and examples
2. •

   Trusted secondary sources

   • •MDN Web Docs (web technologies)
   • •DigitalOcean Community tutorials
   • •Dev.to (high-quality articles only)
   • •Stack Overflow (accepted answers)
3. •

   Avoid

   • •SEO-optimized content farms
   • •Outdated tutorials (check dates)
   • •AI-generated summaries
   • •Forums without accepted solutions

WebSearch Patterns

Reference references/query-patterns.md for specific query templates per technology domain.

Filtering Results

Relevance Criteria

Include information that:

• •Directly addresses the stated context
• •Provides actionable code examples
• •Explains common pitfalls for the use case
• •Is current (matches stated version or latest)

Exclude information that:

• •Is tangentially related
• •Covers advanced edge cases not needed
• •Is deprecated or version-mismatched
• •Duplicates what's already found

Extraction Process

1. •Scan search results for relevance
2. •Open 2-3 most promising sources
3. •Extract specific sections, not entire pages
4. •Verify code examples are complete
5. •Note version compatibility

Document Format

Save all knowledge files to .claude/knowledge/ using the template in references/document-template.md.

File Naming

Format: {technology}-{topic}.md

Examples:

• •react-useeffect-cleanup.md
• •effect-pipe-operator.md
• •prisma-relations.md
• •nextauth-jwt-session.md

Rules:

• •All lowercase
• •Hyphens between words
• •Technology first, then topic
• •No version numbers in filename

Frontmatter Structure

Required fields in YAML frontmatter:

• •topic: Descriptive title
• •technology: Library/framework name
• •version: Version researched (or "latest")
• •sources: List of URLs used
• •created: Date in YYYY-MM-DD format
• •context: Original problem that triggered research

Quality Checklist

Before saving knowledge document, verify:

• • Request was properly validated
• • Existing knowledge was checked first
• • Official sources were consulted
• • Content is specific to stated context
• • Code examples are complete and tested
• • Sources are cited
• • File follows naming convention
• • Frontmatter is complete

Additional Resources

Reference Files

• •references/query-patterns.md - Technology-specific search query templates
• •references/document-template.md - Complete knowledge document template

Implementation Notes

This methodology is designed for Haiku model execution. Instructions are explicit and procedural to ensure consistent results across model capabilities.