Root Cause Analysis
SkillDev toolsPerforms 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.
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What this skill tells your AI
The instructions your AI receives, as published by rohitg00/skillkit in packages/core/src/methodology/packs/debugging/root-cause-analysis/SKILL.md and read by ahel’s review.
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
finallyblock 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
Signals
- GitHub stars
- 1k
- Forks
- 143
- Last commit
- Jun 2026
Advanced
- Catalog kind
- skill
- Gateway key
root-cause-analysis-rohitg00- Source
- github.com/rohitg00/skillkit