Piv Investigate Issue

Investigate Issue #$ARGUMENTS (Root-Cause Analysis)

Objective

Investigate GitHub issue #$ARGUMENTS from this repository, identify the root cause, and document findings for future implementation.

Prerequisites:

• Working in a local Git repository with GitHub origin
• GitHub CLI installed and authenticated (gh auth status)
• Valid GitHub issue ID from this repository

Investigation Process

1. Fetch GitHub Issue Details

Use GitHub CLI to retrieve issue information:

gh issue view $ARGUMENTS

This fetches:

• Issue title and description
• Reporter and creation date
• Labels and status
• Comments and discussion

2. Explore the Codebase — fan out in parallel

Dispatch specialized agents in parallel (one message, multiple Task calls) so exploration is fast and the noisy search stays out of your main context:

• codebase-analyst — trace HOW the affected code works end-to-end: integration points, data flow,

state/side effects, error handling. Return precise file:line references, no suggestions.

• research-agent (a second explorer) — find WHERE the relevant code lives + patterns to mirror: the error

strings from the issue, related functions/modules, similar implementations, existing test patterns.

Merge their findings into a short map (file:line + why each matters) before forming the root cause. (This is the parallel-subagent fan-out, applied to diagnosis.)

3. Review Recent History — when was it introduced?

Check recent changes to the affected areas, and pin down when the bug entered: !git log --oneline -20 -- [relevant-paths]

git blame -L ,    # who/when introduced the suspect lines

Decide: a recent regression vs a long-standing bug vs original behavior — it changes both the fix and the risk.

4. Investigate Root Cause — the 5 Whys, with evidence

Don't stop at the symptom. Chain why → because until you reach the specific, fixable code, and back every link with file:line evidence:

WHY does  happen? → because    (evidence: file.ts:123 — )
WHY ?             → because    (evidence: file.ts:456 — )
… ROOT CAUSE:   (evidence: file.ts:789 — )

Watch for: input-validation gaps, unhandled edge cases, race/timing issues, wrong assumptions, missing error handling, integration mismatches.

5. Assess Impact

Determine:

• How widespread is this issue?
• What features are affected?
• Are there workarounds?
• What is the severity?
• Could this cause data corruption or security issues?

6. Propose Fix Approach

Design the solution:

• What needs to be changed?
• Which files will be modified?
• What is the fix strategy?
• Are there alternative approaches?
• What testing is needed?
• Are there any risks or side effects?

Output: Create RCA Document

Save analysis as: docs/issues/issue-$ARGUMENTS.md

Required RCA Document Structure

# Root Cause Analysis: GitHub Issue #$ARGUMENTS

## Issue Summary

- **GitHub Issue ID**: #$ARGUMENTS
- **Issue URL**: [Link to GitHub issue]
- **Title**: [Issue title from GitHub]
- **Reporter**: [GitHub username]
- **Status**: [Current GitHub issue status]

## Assessment

Each value needs a one-line reason grounded in the investigation (not a guess):

| Metric | Value | Reasoning |
|--------|-------|-----------|
| Severity | Critical/High/Medium/Low | user impact · workaround · scope of failure |
| Complexity | Low/Medium/High | files touched · integration points · risk |
| Confidence | High/Medium/Low | evidence quality · unknowns · assumptions |

> **Confidence is the human-attention signal:** LOW confidence = a human should look before the fix runs. Say it honestly.

## Problem Description

[Clear description of the issue]

**Expected Behavior:**
[What should happen]

**Actual Behavior:**
[What actually happens]

**Symptoms:**
- [List observable symptoms]

## Reproduction

**Steps to Reproduce:**
1. [Step 1]
2. [Step 2]
3. [Observe issue]

**Reproduction Verified:** [Yes/No]

## Root Cause

### Affected Components

- **Files**: [List of affected files with paths]
- **Functions/Classes**: [Specific code locations]
- **Dependencies**: [Any external deps involved]

### Analysis

[Detailed explanation of the root cause]

**Evidence Chain (5 Whys):**

WHY → because (evidence: file:line — snippet) … ROOT CAUSE: (evidence: file:line — snippet)

**Why This Occurs:**
[Explanation of the underlying issue]

**Code Location:**

[File path:line number] [Relevant code snippet showing the issue]

### Related Issues

- [Any related issues or patterns]

## Impact Assessment

**Scope:**
- [How widespread is this?]

**Affected Features:**
- [List affected features]

**Severity Justification:**
[Why this severity level]

**Data/Security Concerns:**
[Any data corruption or security implications]

## Proposed Fix

### Fix Strategy

[High-level approach to fixing]

### Files to Modify

1. **[file-path]**
   - Changes: [What needs to change]
   - Reason: [Why this change fixes it]

2. **[file-path]**
   - Changes: [What needs to change]
   - Reason: [Why this change fixes it]

### Alternative Approaches

[Other possible solutions and why the proposed approach is better]

### Risks and Considerations

- [Any risks with this fix]
- [Side effects to watch for]
- [Breaking changes if any]

### Testing Requirements

**Test Cases Needed:**
1. [Test case 1 - verify fix works]
2. [Test case 2 - verify no regression]
3. [Test case 3 - edge cases]

**Validation Commands:**
```bash
[Exact commands to verify fix]

Implementation Plan

[Brief overview of implementation steps]

This RCA document should be used by the piv-implement-issue skill.

Next Steps

1. Review this RCA document
2. Run the piv-implement-issue skill with issue #$ARGUMENTS to implement the fix
3. Run the piv-commit skill after implementation complete

## Post the summary to the issue

After writing the doc, post a short version as a GitHub comment — an audit trail, and so the fix can be
triggered/tracked from the issue itself:
```bash
gh issue comment $ARGUMENTS --body ""

Edge cases

• Already closed → report it; still write the RCA if analysis is wanted.
• Already has a linked PR → warn; confirm before continuing.
• Can't pin the root cause → set Confidence: LOW, document the best hypothesis + what's uncertain, and flag it for a human before any fix.
• Scope too large → suggest splitting into smaller issues; focus this RCA on the core problem and list the rest as out-of-scope.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: coleam00
• Source: coleam00/skills
• License: MIT

Install and usage instructions live in the source repository linked above.