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research-codebase

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Search the codebase to answer specific questions from the ambiguity analysis. Returns findings with confidence levels.

8 stars
1.2k downloads
Updated 1/20/2026

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SKILL.md

Research Codebase - Targeted Code Investigation

You are researching the codebase to answer specific questions about the feature specification.

Input: $ARGUMENTS contains the ambiguity analysis report with search strategies.

Research Approach: Hybrid Priority

Execute research in two phases:

Phase A: Pattern-Seeking (Context Building)

First, build understanding of relevant codebase areas:

  1. Find Similar Features

    Glob: **/*{related_feature}*
    Grep: similar functionality keywords
    
  2. Identify Project Conventions

    • File organization patterns
    • Naming conventions
    • Common abstractions used
  3. Map Relevant Architecture

    • Entry points (routes, controllers, handlers)
    • Data flow patterns
    • Shared utilities and helpers

Phase B: Question-Driven (Targeted Answers)

For each RESEARCH_NEEDED item from the ambiguity analysis:

  1. Execute the suggested search strategies
  2. Read relevant files discovered
  3. Extract specific answers
  4. Assess confidence level

Confidence Assessment Criteria

HIGH Confidence (promote to spec)

  • Direct code evidence (function exists, pattern used)
  • Explicit comments or documentation
  • Multiple consistent examples
  • Standard framework/library behavior

MEDIUM Confidence (note but verify)

  • Single example found (might be exception)
  • Inferred from related code
  • Convention appears consistent but not documented
  • Third-party dependency behavior

LOW Confidence (keep as question)

  • No direct evidence found
  • Contradictory examples
  • Requires human judgment call
  • Involves external systems not in codebase

Research Execution

For each research target:

## Researching: {ambiguity description}

### Search Executed
- Glob: {pattern} → {n} files found
- Grep: {pattern} → {n} matches
- Files read: {list}

### Findings
{What was discovered}

### Evidence
File: {path}:{line}
```{code snippet}```

### Confidence: {HIGH|MEDIUM|LOW}
Rationale: {why this confidence level}

### Suggested Spec Update
{How this should update the specification}

Special Research Cases

When Nothing Found

  • Note the absence as meaningful data
  • Suggest this might be new territory for the project
  • Recommend human decision on approach

When Contradictions Found

  • Document all variations
  • Note which appears more recent/prevalent
  • Flag for human resolution

When Scope Expands

  • If research reveals the feature is larger than expected
  • Note the expansion but don't pursue rabbit holes
  • Flag for orchestrator to handle

Output Format

RESEARCH COMPLETE
Questions Investigated: {n}
High Confidence Answers: {n}
Medium Confidence Answers: {n}
Still Open: {n}

## Findings by Question

### Q1: {original question}
**Confidence**: HIGH
**Answer**: {clear answer}
**Evidence**: {file:line references}
**Spec Update**: Add to High Confidence section: "{suggested text}"

### Q2: {original question}
**Confidence**: MEDIUM
**Answer**: {tentative answer}
**Evidence**: {file:line references}
**Spec Update**: Add to Medium Confidence section: "{suggested text}"

### Q3: {original question}
**Confidence**: LOW
**Answer**: Could not determine
**Searched**: {what was tried}
**Spec Update**: Keep in Open Questions, add context: "{additional info}"

## New Questions Discovered
During research, these new questions emerged:
1. {question surfaced while investigating}
2. {another emergent question}

## Relevant Files for Future Reference
- {path}: {why it's relevant}
- {path}: {why it's relevant}

Constraints

  • Do NOT modify any files - read only
  • Do NOT pursue tangential research
  • Stay focused on the specific questions provided
  • Time-box each question - don't exhaust search on one item
  • If a question would require extensive research, note it and move on

Install

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Requires askill CLI v1.0+

AI Quality Score

95/100Analyzed 2/13/2026

An exceptionally well-structured skill for codebase research. It provides clear phases, confidence assessment criteria, strict safety constraints (read-only), and precise output templates, making it highly actionable and safe for agentic use.

100
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85
95
95

Metadata

Licenseunknown
Version-
Updated1/20/2026
Publisherdhofheinz

Tags

ci-cd