Agent skill

research

This skill should be used when researching best practices, evaluating technologies, comparing approaches, or when "research", "evaluation", or "comparison" are mentioned.

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Install this agent skill to your Project

npx add-skill https://github.com/outfitter-dev/agents/tree/main/plugins/outfitter/skills/research

Metadata

Additional technical details for this skill

version
2.1.0
related skills
[
    "report-findings",
    "codebase-recon"
]

SKILL.md

Research

Systematic investigation → evidence-based analysis → authoritative recommendations.

Steps

  1. Define scope and evaluation criteria
  2. Discover sources using MCP tools (context7, octocode, firecrawl)
  3. Gather information with multi-source approach
  4. Load the outfitter:report-findings skill for synthesis
  5. Compile report with confidence levels and citations

<when_to_use>

  • Technology evaluation and comparison
  • Documentation discovery and troubleshooting
  • Best practices and industry standards research
  • Implementation guidance with authoritative sources

NOT for: quick lookups, well-known patterns, time-critical debugging without investigation stage

</when_to_use>

Load the maintain-tasks skill for stage tracking. Stages advance only, never regress.

Stage Trigger activeForm
Analyze Request Session start "Analyzing research request"
Discover Sources Criteria defined "Discovering sources"
Gather Information Sources identified "Gathering information"
Synthesize Findings Information gathered "Synthesizing findings"
Compile Report Synthesis complete "Compiling report"

Workflow:

  • Start: Create "Analyze Request" as in_progress
  • Transition: Mark current completed, add next in_progress
  • Simple queries: Skip directly to "Gather Information" if unambiguous
  • Gaps during synthesis: Add new "Gather Information" task
  • Early termination: Skip to "Compile Report" with caveats

Five-stage systematic approach:

1. Question Stage — Define scope

  • Decision to be made?
  • Evaluation parameters? (performance, maintainability, security, adoption)
  • Constraints? (timeline, expertise, infrastructure)

2. Discovery Stage — Multi-source retrieval

Use Case Primary Secondary Tertiary
Official docs context7 octocode firecrawl
Troubleshooting octocode issues firecrawl community context7 guides
Code examples octocode repos firecrawl tutorials context7 examples
Technology eval Parallel all Cross-reference Validate

3. Evaluation Stage — Analyze against criteria

Criterion Metrics
Performance Benchmarks, latency, throughput, memory
Maintainability Code complexity, docs quality, community activity
Security CVEs, audits, compliance
Adoption Downloads, production usage, industry patterns

4. Comparison Stage — Systematic tradeoff analysis

For each option: Strengths → Weaknesses → Best fit → Deal breakers

5. Recommendation Stage — Clear guidance with rationale

Primary recommendation → Alternatives → Implementation steps → Limitations

Three MCP servers for multi-source research:

Tool Best For Key Functions
context7 Official docs, API refs resolve-library-id, get-library-docs
octocode Code examples, issues packageSearch, githubSearchCode, githubSearchIssues
firecrawl Tutorials, benchmarks search, scrape, map

Execution patterns:

  • Parallel: Run independent queries simultaneously for speed
  • Fallback: context7 → octocode → firecrawl if primary fails
  • Progressive: Start broad, narrow based on findings

See tool-selection.md for detailed usage.

<discovery_patterns>

Common research workflows:

Scenario Approach
Library Installation Package search → Official docs → Installation guide
Error Resolution Parse error → Search issues → Official troubleshooting → Community solutions
API Exploration Documentation ID → API reference → Real usage examples
Technology Comparison Parallel all sources → Cross-reference → Build matrix → Recommend

See discovery-patterns.md for detailed workflows.

</discovery_patterns>

<findings_format>

Two output modes:

Evaluation Mode (recommendations):

Finding: { assertion }
Source: { authoritative source with link }
Confidence: High/Medium/Low — { rationale }

Discovery Mode (gathering):

Found: { what was discovered }
Source: { where from with link }
Notes: { context or caveats }

</findings_format>

<response_structure>

markdown
## Research Summary
Brief overview — what investigated, sources consulted.

## Options Discovered
1. **Option A** — description
2. **Option B** — description

## Comparison Matrix
| Criterion | Option A | Option B |
|-----------|----------|----------|

## Recommendation
### Primary: [Option Name]
**Rationale**: reasoning + evidence
**Confidence**: level + explanation

### Alternatives
When to choose differently.

## Implementation Guidance
Next steps, common pitfalls, validation.

## Sources
- Official, benchmarks, case studies, community

</response_structure>

Always include:

  • Direct citations with links
  • Confidence levels and limitations
  • Context about when recommendations may not apply

Always validate:

  • Version is latest stable
  • Documentation matches user context
  • Critical info cross-referenced
  • Code examples complete and runnable

Proactively flag:

  • Deprecated approaches with modern alternatives
  • Missing prerequisites
  • Common pitfalls and gotchas
  • Related tools in ecosystem

ALWAYS:

  • Create "Analyze Request" todo at session start
  • One stage in_progress at a time
  • Use multi-source approach (context7, octocode, firecrawl)
  • Provide direct citations with links
  • Cross-reference critical information
  • Include confidence levels and limitations

NEVER:

  • Skip "Analyze Request" stage without defining scope
  • Single-source when multi-source available
  • Deliver recommendations without citations
  • Include deprecated approaches without flagging
  • Omit limitations and edge cases
  • source-hierarchy.md — authority evaluation details
  • tool-selection.md — MCP server decision matrix
  • discovery-patterns.md — detailed research workflows

Research vs Report-Findings:

  • This skill (research) covers the full investigation workflow using MCP tools
  • report-findings skill covers synthesis, source assessment, and presentation

Use research for technology evaluation, documentation discovery, and best practices research. Load report-findings during synthesis stage for source authority assessment and confidence calibration.

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