| name | investigate |
| description | Deep investigation of GitHub issues with root cause analysis and proposed solutions. Use when asked to investigate, analyze, or dig into an issue. |
| model | opus |
| context | fork |
| agent | investigator |
| effort | high |
Investigate GitHub Issue
Investigate the following GitHub issue: $ARGUMENTS
Instructions
Phase 1: Fetch Issue Details
- Parse the input:
DX-123 or linear.app URL → Linear ticket#123, bare number, or github.com URL → GitHub issue
- Fetch the ticket:
- GitHub:
gh issue view <number> --json title,body,labels,comments,author,createdAt,state
- Linear:
bash .agents/skills/triage/scripts/linear-fetch.sh issue DX-123
- Extract: error messages, stack traces, reproduction steps, environment details
Phase 2: Identify Affected Package(s)
- Check issue labels for
pkg:* tags
- Search title/body for package names or import statements
- Check stack traces for file paths
- Package folders are in
packages/ — use labels and keywords to identify
Phase 3: Deep Analysis
- Search for error messages and referenced functions in the codebase
- Trace the execution path from entry point to the reported behavior
- Check recent commits:
git log --oneline -20 -- packages/<name>
- Search similar issues:
gh issue list --search "<keywords>" --state all --limit 10
Phase 4: Root Cause Analysis
Determine category: bug in logic, API change, type mismatch, missing validation, race condition, environment issue, configuration, or documentation gap.
Phase 5: Propose Solutions
For each root cause: the fix (file paths + line numbers), test coverage needed, verification commands.
Output
- Extract identifier from arguments (issue
424 → 424, ticket DX-296 → DX-296, text → slugified)
mkdir -p claude-output- Write to
claude-output/investigate-<identifier>.md
- Confirm to user: "Investigation written to
claude-output/investigate-<identifier>.md"
Output Structure
# Investigation: Issue #<number>
**Title:** | **URL:** | **Created:** | **State:** | **Author:**
## Summary
## Affected Package(s) (table: Package, Confidence, Evidence)
## Issue Details (Reported Behavior, Expected Behavior, Environment, Reproduction Steps)
## Code Analysis (Relevant Files table, Execution Flow, Code snippets)
## Root Cause (Category, Explanation, Evidence)
## Proposed Solutions (Changes table, Code before/after, Tests to add, Verification)
## Similar Issues
## Notes / Risks
## Next Steps
