Agent skill
research
(ePost) Use when user asks to research, compare options, find best practices, or investigate a technology
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/research-klara-copilot-epost-agent-kit
Metadata
Additional technical details for this skill
- keywords
-
research investigation documentation sources validation best-practices how-to compare evaluate library
- triggers
-
[ "/research", "research", "best practices", "how to" ] - platforms
-
[ "all" ] - agent affinity
-
[ "epost-researcher", "epost-planner", "epost-mcp-manager" ]
SKILL.md
Research Skill
Delegation — REQUIRED
This skill MUST run via the epost-researcher agent, not inline.
When research intent is detected:
- Use the Agent tool to spawn
epost-researcher - Pass the research topic + scope + report path (
reports/research-{date}-{slug}.md) - Do NOT conduct research inline in the main conversation
Purpose
Multi-source information gathering and synthesis. Provide strategic technical intelligence that enables informed decision-making.
Honoring YAGNI, KISS, and DRY. Be honest, be brutal, straight to the point, concise.
When Active
User asks for research, best practices, comparison, technology evaluation, solution design.
Research Phases
Phase 1: Scope Definition
Clearly define scope before searching:
- Identify key terms and concepts to investigate
- Determine recency requirements (how current must information be)
- Establish evaluation criteria for sources
- Set boundaries for research depth
Phase 2: Information Gathering
Check active engine (set by session-init, default: websearch):
echo $EPOST_RESEARCH_ENGINE # gemini | websearch
Engine invocation (max 5 parallel queries — think carefully before each):
Engine: gemini
echo "<research query>" | gemini -y -m "$EPOST_GEMINI_MODEL"
Availability check: which gemini — if not found, log coverage gap and fall back to WebSearch.
Engine: websearch (default / fallback)
Use Claude's built-in WebSearch tool with precise queries:
- Include terms like "best practices", "2024/2025", "security", "performance"
- Craft multiple related queries and run in parallel
- Prioritize official docs, GitHub repos, authoritative blogs
Fallback chain:
- Invoke configured engine
- If unavailable (binary missing / exit code 2): add to Methodology
coverageGaps[] - Fall back to
WebSearchautomatically — do not block or ask user
See references/engines.md for full invocation details, model options, and exit codes.
Deep content analysis: For GitHub repos found, use docs-seeker to read them
- Focus on README, API references, changelogs, release notes
- Review version-specific information
Cross-reference validation:
- Verify across multiple independent sources
- Check publication dates for currency
- Identify consensus vs. controversial approaches
- Note conflicting information
Phase 3: Analysis and Synthesis
- Identify common patterns and best practices
- Evaluate pros and cons of different approaches
- Assess maturity and stability of technologies
- Recognize security implications and performance considerations
- Determine compatibility and integration requirements
Phase 4: Report Generation
Save report to path provided by caller (reports/research-{date}-{slug}.md).
Use references/report-template.md for output structure. Report Methodology section must include:
- Knowledge Tiers: which engine was used (Gemini, Perplexity, WebSearch)
- Coverage Gaps: if configured engine was unavailable and fallback fired
Report must also:
- Include timestamp of when research was conducted
- Provide table of contents for longer reports
- Use code blocks with appropriate syntax highlighting
- Include diagrams (mermaid or ASCII art) where helpful
- Conclude with specific, actionable next steps
- List unresolved questions at the end
Source Priority
- Official documentation (highest)
- Official examples/tutorials
- Well-known community resources
- GitHub repositories with recent activity
- Stack Overflow (for specific issues)
Quality Standards
| Standard | Requirement |
|---|---|
| Accuracy | Verified across multiple sources |
| Currency | Prefer last 12 months; note when using older material |
| Completeness | Cover all aspects requested |
| Actionability | Practical, implementable recommendations |
| Clarity | Define technical terms, provide examples |
| Attribution | Always cite sources with links and dates |
Special Considerations
- Security topics: Check for recent CVEs and security advisories
- Performance topics: Look for benchmarks and real-world case studies
- New technologies: Assess community adoption and support levels
- APIs: Verify endpoint availability and authentication requirements
- Older technologies: Always note deprecation warnings and migration paths
Advanced Techniques
Query Fan-Out
- Ask multiple related questions in parallel
- "What is X?" + "How to use X?" + "Best practices for X?"
- Reduces total research time
Source Validation
- Cross-reference claims across 3+ sources
- Check if multiple sources cite same research
- Look for contradictions and note them
- Verify dates (prefer sources <2 years old)
Technology Trend Identification
- Check GitHub stars and recent activity
- Review recent changelog/updates
- Look at community sentiment in forums
- Note if project is actively maintained
- Watch for deprecation notices
Code Example Validation
- Test examples in isolated environment
- Verify version matches your target
- Check example handles error cases
- Look for performance implications
Best Practices
- Prioritize official docs
- Check publication dates (prefer <2 years)
- Verify code examples work
- Note version-specific info clearly
- Cite sources with URLs and dates
- Cross-validate findings
- Document contradictions
- Track confidence level per finding
- Sacrifice grammar for concision in reports
Knowledge-First Research
Before external research, check internal knowledge:
- Search
docs/for prior research on the topic - Check skill aspect files for existing domain knowledge
- Search agent memory for related past sessions
- Only proceed to external sources if internal knowledge is insufficient
Use knowledge-retrieval skill for the full priority chain.
Use knowledge-capture skill to persist learnings after this task.
Sub-Skill Routing
When this skill is active and user intent matches a sub-skill, delegate:
| Intent | Sub-Skill / Tool | When |
|---|---|---|
| Explore codebase | scout |
/scout, "explore", "find in codebase" |
| Search docs | docs-seeker |
External documentation search |
| Export context | repomix |
/repomix, bundle code for external review |
| Gemini search | gemini CLI via Bash |
$EPOST_RESEARCH_ENGINE = gemini |
| Web search | WebSearch tool |
$EPOST_RESEARCH_ENGINE = websearch or fallback |
Related Skills
knowledge-retrieval— Internal-first search protocolknowledge-capture— Post-task capture workflow
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