mcpbeat

Root Cause Analysis

rohitg00/root-cause-analysis

Performs systematic root cause analysis to identify the true source of bugs, errors, and unexpected behavior through structured investigation phases — not just treating symptoms. Use when a user reports a bug, crash, error, or broken behavior and needs to debug, troubleshoot, or investigate why something is not working; especially for complex or intermittent issues across multiple components. Applies the Five Whys method, hypothesis-driven testing, stack trace analysis, git blame/log evidence gathering, and causal chain documentation to isolate and confirm root causes before applying any fix.

1k tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
1416
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/rohitg00/skillkit --skill root-cause-analysis

The instruction itself

14 sections, as written by the author

Root Cause Analysis

You are performing systematic root cause analysis to find the true source of a bug. Do not apply fixes until you understand WHY the bug exists.

Core Principle

Never fix a symptom. Always find and fix the root cause.

The Five Whys Method

Ask "Why?" repeatedly to drill down to the root cause:

  • Why did the API return an error? → The database query failed
  • Why did the database query fail? → The connection pool was exhausted
  • Why was the pool exhausted? → ROOT CAUSE: Missing finally block to close connections

Investigation Phases

Phase 1: Reproduce the Bug

Before investigating:

  • Reproduce consistently - If you can't reproduce it, you can't verify a fix
  • Document reproduction steps - Exact sequence of actions
  • Note environment details - OS, versions, configuration
  • Identify minimal reproduction - Smallest case that shows the bug

Questions to answer:

  • Does it happen every time or intermittently?
  • Does it happen in all environments?
  • When did it start happening? (recent changes)

Phase 2: Gather Evidence

Collect information before forming theories:

  • Error messages and stack traces
  • Log files (application, system, database)
  • Recent code changes (git log, blame)
  • User reports and reproduction steps
  • Monitoring data (metrics, APM)
  • Related issues (search issue tracker)

Do NOT:

  • Make changes while gathering evidence
  • Assume you know the cause without evidence
  • Ignore related symptoms

Phase 3: Form Hypotheses

Based on evidence, create ranked hypotheses:

| Priority | Hypothesis | Evidence | Test Plan |

|----------|------------|----------|-----------|

| 1 | Connection leak in UserService | Stack trace shows connection pool | Add logging, check usage |

| 2 | Query timeout too short | Occurs under load | Test with longer timeout |

| 3 | Database server overload | Correlates with peak hours | Check DB metrics |

For each hypothesis:

  • What evidence supports it?
  • What evidence contradicts it?
  • How can we test it?

Phase 4: Test Hypotheses

Test each hypothesis systematically:

  • Start with highest probability
  • Design a definitive test - Should clearly confirm or reject
  • Make ONE change at a time
  • Document results

If hypothesis is rejected:

  • Cross it off the list
  • Re-evaluate remaining hypotheses
  • Consider if new evidence suggests new hypotheses

Phase 5: Verify Root Cause

Before declaring root cause found:

  • [ ] Can you explain the full causal chain?
  • [ ] Does fixing it consistently prevent the bug?
  • [ ] Does it explain ALL observed symptoms?
  • [ ] Is there nothing earlier in the chain that could be fixed?

Common Root Cause Categories

  • Code Defects: logic errors, boundary conditions, race conditions, resource leaks, null/undefined handling
  • Design Issues: missing error handling, inadequate validation, poor state management, coupling
  • Environment: configuration errors, resource constraints, version mismatches, network issues
  • Data Issues: invalid input, data corruption, schema mismatches, encoding problems

Evidence Collection Commands

# Recent changes to relevant files
git log --oneline -20 -- path/to/file

# Who changed this line
git blame path/to/file

# Changes since last working version
git diff v1.2.3..HEAD -- src/

# Search for related error handling
grep -r "catch\|error\|throw" --include="*.ts" src/

Red Flags - You Haven't Found Root Cause

  • "I'm not sure why, but this fix works"
  • "The bug went away after I restarted"
  • "I added a check to prevent this case"
  • "It's probably a race condition somewhere"

These suggest symptom treatment, not root cause resolution.

Documentation Template

When root cause is found, document:

## Bug: [Description]

### Root Cause
[Clear explanation of why the bug occurred]

### Evidence
- [Evidence 1]
- [Evidence 2]

### Causal Chain
1. [Initial trigger]
2. [Intermediate cause]
3. [Root cause]
4. [Observed symptom]

### Fix
[Description of the fix and why it addresses root cause]

### Prevention
[How to prevent similar issues in the future]

Integration with Other Skills

After finding root cause:

  • Use testing/red-green-refactor to write a test that exposes the bug
  • Use planning/verification-gates to validate the fix
  • Consider collaboration/structured-review for complex fixes

How to use it

Copy the folder

Take rohitg00/root-cause-analysis from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.