
research-codebase
by dhofheinz
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SKILL.md
name: research-codebase description: Search the codebase to answer specific questions from the ambiguity analysis. Returns findings with confidence levels. context: fork allowed-tools: Glob, Grep, Read user-invocable: false agent: code-archaeologist
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:
-
Find Similar Features
Glob: **/*{related_feature}* Grep: similar functionality keywords -
Identify Project Conventions
- File organization patterns
- Naming conventions
- Common abstractions used
-
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:
- Execute the suggested search strategies
- Read relevant files discovered
- Extract specific answers
- 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
Score
Total Score
Based on repository quality metrics
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