Root Cause Analysis: GitHub Issue #$ARGUMENTS

SkillDocs & knowledge

Investigates a GitHub issue, identifies the root cause, and writes a structured RCA document for later implementation. Use when you need to diagnose a bug reported as a GitHub issue before fixing it.

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 Root Cause Analysis: GitHub Issue #$ARGUMENTS skill

What this skill tells your AI

The instructions your AI receives, as published by coleam00/ai-native-starter-pack in .claude/skills/rca/SKILL.md and read by ahel’s review.

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. Search Codebase

Identify relevant code:

  • Search for components mentioned in issue
  • Find related functions, classes, or modules
  • Check similar implementations
  • Look for patterns or recent changes

Use grep/search to find:

  • Error messages from issue
  • Related function names
  • Component identifiers

3. Review Recent History

Check recent changes to affected areas: !git log --oneline -20 -- [relevant-paths]

Look for:

  • Recent modifications to affected code
  • Related bug fixes
  • Refactorings that might have introduced the issue

4. Investigate Root Cause

Analyze the code to determine:

  • What is the actual bug or issue?
  • Why is it happening?
  • What was the original intent?
  • Is this a logic error, edge case, or missing validation?
  • Are there related issues or symptoms?

Consider:

  • Input validation failures
  • Edge cases not handled
  • Race conditions or timing issues
  • Incorrect assumptions
  • Missing error handling
  • Integration issues between components

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/rca/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]
- **Severity**: [Critical/High/Medium/Low]
- **Status**: [Current GitHub issue status]

## 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]

**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 implement-fix skill.

Next Steps

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

Signals

GitHub stars
69
Forks
23
Last commit
Aug 2026
Advanced
Catalog kind
skill
Gateway key
rca
Source
github.com/coleam00/ai-native-starter-pack