Research

SkillDocs & knowledge

Read-only research with bash access. Deep codebase investigation, documentation review, external research.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Research skill

What this skill tells your AI

The instructions your AI receives, as published by neuron-mr-white/unipi in packages/workflow/skills/research/SKILL.md and read by ahel’s review.

Deep read-only investigation with bash access. For thorough codebase analysis, documentation review, and external research.

Boundaries

This skill MAY: read codebase, run read-only bash commands, spawn subagents, write findings, use web tools if available. This skill MAY NOT: edit code, create files (except findings), run tests that modify state, deploy.

This is research only — not implementation.

Command Format

/unipi:research <string(greedy)>
  • string(greedy) — research topic or question
  • Read-only sandbox + bash access
  • Spawns subagents if @unipi/subagents extension is installed
  • Uses web tools if @unipi/web-api extension is installed

Output

Findings presented in conversation. Can be saved to .unipi/docs/generated/ if user requests.


Process

Phase 1: Define Research Scope

  1. Read the research topic/question
  2. If ambiguous, ask clarifying questions (one at a time)
  3. Determine research type:
    • Codebase research — patterns, architecture, dependencies
    • Documentation research — existing docs, READMEs, comments
    • External research — libraries, APIs, best practices
    • Historical research — git history, past decisions
    • Comparative research — evaluate options/approaches

Exit: Research scope defined.

Phase 2: Codebase Research

Use bash and read tools for deep investigation:

Structure Analysis:

find . -type f -name "*.ts" | head -50
ls -la src/
tree src/ -L 2

Pattern Search:

grep -r "pattern" --include="*.ts" .
grep -rn "TODO\|FIXME\|HACK" --include="*.ts" .

Dependency Analysis:

cat package.json
grep -r "import.*from" --include="*.ts" . | sort | uniq -c | sort -rn

Git History:

git log --oneline -20
git log --all --oneline --grep="keyword"
git blame file.ts

Exit: Codebase context gathered.

Phase 3: Documentation Research

  1. Read existing documentation:

    • README files
    • API docs
    • Architecture docs
    • Comments and docstrings
  2. Check for gaps:

    • Missing documentation
    • Outdated docs
    • Inconsistent information
  3. Cross-reference:

    • Do docs match code?
    • Are examples correct?

Exit: Documentation context gathered.

Phase 4: External Research (if web tools available)

Use web tools for external research:

Library/API Research:

web_search(query: "library-name documentation")
web_read(url: "https://docs.library.com")
web_llm_summarize(url: "https://library.com/guide", prompt: "Extract key concepts and usage patterns")

Best Practices:

web_search(query: "best practices for X in TypeScript 2026")
web_search(query: "X vs Y comparison")

Stack Overflow / GitHub:

web_search(query: "site:stackoverflow.com how to X")
web_search(query: "site:github.com X implementation examples")

Exit: External context gathered.

Phase 5: Synthesize Findings

Organize research into clear categories:

## Research Findings: {Topic}

### Summary
{One-paragraph overview of findings}

### Key Findings
1. {Finding 1}
2. {Finding 2}
3. {Finding 3}

### Detailed Analysis

#### {Category 1}
{Detailed findings with evidence}

#### {Category 2}
{Detailed findings with evidence}

### Codebase Context
- Current implementation: {description}
- Patterns used: {list}
- Gaps identified: {list}

### Recommendations
- {Recommendation 1}
- {Recommendation 2}

### Sources
- {File/code references}
- {External links}
- {Documentation references}

### Open Questions
- {Question that needs further research}

Phase 6: Present & Handoff

Present findings to user:

"Research complete on: {topic}"

Then suggest next steps based on findings:

If research was for planning:

"Ready to brainstorm solutions?"

/unipi:brainstorm {topic}

If research found issues:

"Found some issues during research. Consider investigating:"

/unipi:debug {issue}
/unipi:scan-issues focus on {area}

If research was for documentation:

"Ready to document what we found?"

/unipi:document {topic}

If research was exploratory:

"Want me to save these findings?"

  • Save to .unipi/docs/generated/YYYY-MM-DD-research-{topic}.md

Research Types

Codebase Research

  • Find patterns and conventions
  • Understand architecture
  • Map dependencies
  • Identify tech debt

Documentation Research

  • Review existing docs
  • Find gaps and inconsistencies
  • Extract best practices
  • Cross-reference with code

External Research

  • Library evaluation
  • API documentation
  • Best practices
  • Community solutions

Historical Research

  • Git history analysis
  • Past decision context
  • Evolution of codebase
  • Bug pattern analysis

Comparative Research

  • Evaluate alternatives
  • Trade-off analysis
  • Performance comparison
  • Feature comparison

Differences from gather-context

Aspect/unipi:research/unipi:gather-context
ScopeBroad, any topicFocused on codebase
Bash accessFull read-only bashLimited commands
External webUses web toolsCodebase only
OutputDetailed findingsConcise summary
HandoffVarious optionsAlways → brainstorm

Notes

  • Read-only with bash — powerful but safe
  • Web tools integration when available
  • Subagent support for parallel research
  • Findings can be saved to docs if requested
  • Natural lead-in to brainstorm, debug, or document

Signals

GitHub stars
64
Forks
15
Last commit
Sep 2026
Hacker News mentions
20
Advanced
Catalog kind
skill
Gateway key
research-neuron-mr-white
Source
github.com/neuron-mr-white/unipi