vamfi/claude-user-memory/research-methodology
Claude Code and agent skill by vamfi/claude-user-memory
- community
Checking that the SKILL.md file is still in the repository.
Systematic approach for gathering authoritative, version-accurate documentation. Claude invokes this skill when research is needed before implementation. Ensures truth over speed while achieving both.
Install
npx vskill@latest install vamfi/claude-user-memory/research-methodologySKILL.md
Research Methodology Skill
This skill provides a systematic methodology for conducting rapid, accurate documentation research to ground implementations in truth rather than potentially stale LLM memory.
When Claude Should Use This Skill
Claude will automatically invoke this skill when:
- User mentions implementing/using a specific library or API
- User asks about current documentation for a technology
- User requests verification of API signatures or methods
- Task requires external dependencies or third-party integrations
- Updating/upgrading to new versions of frameworks
Core Principles (BRAHMA Constitution)
- Truth over speed - But achieve both through systematic approach
- Never guess APIs - Always retrieve from authoritative sources
- Cite everything - Include version, URL, and section references
- Deterministic - Same research query should yield consistent results
Research Methodology Protocol
Step 1: Rapid Assessment (< 30 seconds)
Objectives:
- Identify what needs to be researched
- Detect current versions from project files
- Clarify any ambiguities
Actions:
- Parse request - Extract library/API names mentioned
- Version detection - Check project dependency files:
package.json→ Node.js projectsrequirements.txt,pyproject.toml,Pipfile→ Pythongo.mod→ GoCargo.toml→ Rustbuild.gradle,pom.xml→ Java*.csproj→ C#/.NETpubspec.yaml→ Dart/Fluttercomposer.json→ PHP
- Context gathering - Note runtime, platform, existing dependencies
Output:
If unclear: Ask ONE specific clarifying question rather than proceed with assumptions
Step 2: Source Prioritization (< 10 seconds)
Source hierarchy (in order of preference):
- Official documentation (PRIMARY)
- Project's official website
- Official API reference
- Official getting started guide
- Official migration/upgrade guides (if version change)
- Breaking changes documentation
- Migration paths
- Deprecation notices
- Official release notes/changelog (for version-specific info)
- What's new in this version
- Bug fixes relevant to use case
- Known issues
- Official GitHub repository (if docs sparse)
- README.md
- Examples directory
- Issue tracker (for known problems)
- Avoid (unless no alternatives):
- Blog posts (may be outdated)
- Stack Overflow (may be for wrong version)
- AI-generated content (circular hallucination risk)
Step 3: Information Retrieval (< 90 seconds)
Retrieval strategy:
What to extract:
- API signatures - Function names, parameters, return types
- Setup/initialization - How to configure and start using
- Code examples - Minimal working examples (with URLs to source)
- Gotchas - Known issues, breaking changes, version-specific warnings
- Best practices - Recommended usage patterns from docs
Anti-stagnation:
- Set 60-second timeout per source
- If source fetch fails, report and try next source
- If all sources fail, report what was attempted and suggest manual research
Step 4: Verification & Citation (< 30 seconds)
For every piece of information extracted:
Verification checklist:
- ✓ Version matches project dependency
- ✓ Source is official (not third-party)
- ✓ URL links to specific section (not just homepage)
- ✓ Information is current (check doc version/date if shown)
- ✓ Examples are complete and runnable
Confidence levels:
- HIGH: Official docs for exact version, multiple sources corroborate
- MEDIUM: Official docs but slight version mismatch, or single source
- LOW: Only unofficial sources, version mismatch, or deprecated docs
Report confidence: Always indicate confidence level in research output
Step 5: Structured Output (< 30 seconds)
Deliver in ResearchPack format:
Keep it concise:
- Use bullet points, not paragraphs
- Include only essential information for implementation
- Provide links for deeper reading (don't excerpt everything)
Quality Assurance
Before delivering research:
- Completeness check:
- ✓ Library identified with version
- ✓ At least 3 key APIs documented
- ✓ Setup steps provided
- ✓ At least 1 code example
- ✓ All claims cited with sources
- Accuracy check:
- ✓ API signatures match docs exactly (not paraphrased)
- ✓ Version numbers correct
- ✓ URLs all valid and point to official sources
- ✓ No hallucinated functions/parameters
- Usefulness check:
- ✓ Implementation checklist actionable
- ✓ Examples are complete (can be run)
- ✓ Gotchas relevant to detected version
- ✓ Open questions identify real decisions needed
Common Pitfalls to Avoid
❌ Don't:
- Use docs from wrong version
- Guess or fill in gaps from LLM memory
- Copy-paste entire doc pages (extract key info)
- Trust unofficial blogs/tutorials over official docs
- Proceed without citing sources
- Skip version detection step
✅ Do:
- Always detect version from project files first
- Cite every API with source URL + section
- Extract concise, relevant info only
- Report confidence level honestly
- Link to specific doc sections, not just homepage
- Note version-specific gotchas explicitly
Performance Targets
- Total time: < 2 minutes for typical library research
- Accuracy: 100% of APIs must match official docs
- Citations: 100% of claims must have sources
- Completeness: 95%+ of info needed for implementation
Example Usage
Scenario: User says "Add Redis caching to the product service"
Claude (using this skill):
This skill ensures all implementations are grounded in current, authoritative documentation rather than potentially outdated LLM knowledge.
Security
- Security scanPassed, 95 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingarchive/2026-09-26-install-md-migration/legacy/.claude/skills/research-methodology/skill.md
Popularity
- Repository stars
- 212
- Repository forks
- 32
- 7-day trend score
- 32
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
Works with
Any agent vskill installs to: 56 targets in all. These 39 have a page on this site.
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