research-methodology

# Research Methodology for Documentation

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

## Core Principles

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

## Request Validation

A valid research request must contain three elements:

| Element | Example | Invalid |
|---------|---------|---------|
| Technology | "React", "Effect", "Prisma" | "JavaScript library" |
| Topic | "useEffect cleanup", "pipe operator" | "how it works" |
| Context | "fixing memory leak in subscription" | "learning" |

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   - Outdated tutorials (check dates)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