root-cause-analysis
Root cause analysis (RCA) identifies underlying reasons for failures, enabling permanent solutions rather than temporary fixes.
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Install Skill
Run in your terminal
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this week
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Installation Guide
How to use root-cause-analysis on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your machine
- ›Node.js 16+ with npm — verify with
node --version - ›Active project directory where you want to add
root-cause-analysis
Run the install command
Execute the skills CLI command in your project's root directory to begin installation:
Fetches root-cause-analysis from aj-geddes/useful-ai-prompts and configures it for Cursor.
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate root-cause-analysis. Access via /root-cause-analysis in your agent's command palette.
Security Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Documentation
Root Cause Analysis
Table of Contents
Overview
Root cause analysis (RCA) identifies underlying reasons for failures, enabling permanent solutions rather than temporary fixes.
When to Use
- Production incidents
- Customer-impacting issues
- Repeated problems
- Unexpected failures
- Performance degradation
Quick Start
Minimal working example:
Example: Website Down
Symptom: Website returned 503 Service Unavailable
Why 1: Why was website down?
Answer: Database connection pool exhausted
Why 2: Why was connection pool exhausted?
Answer: Queries taking too long, connections not released
Why 3: Why were queries slow?
Answer: Missing index on frequently queried column
Why 4: Why was index missing?
Answer: Performance testing didn't use production-like data volume
Why 5: Why wasn't production-like data used?
Answer: Load testing environment doesn't mirror production
Root Cause: Load testing environment under-provisioned
Solution: Update load testing environment with production-like data
Prevention: Establish environment parity requirements
Reference Guides
Detailed implementations in the references/ directory:
| Guide | Contents |
|---|---|
| The 5 Whys Technique | The 5 Whys Technique |
| Systematic RCA Process | Systematic RCA Process |
| RCA Report Template | RCA Report Template |
| Root Cause Analysis Techniques | Root Cause Analysis Techniques |
| Follow-Up & Prevention | Follow-Up & Prevention |
Best Practices
✅ DO
- Follow established patterns and conventions
- Write clean, maintainable code
- Add appropriate documentation
- Test thoroughly before deploying
❌ DON'T
- Skip testing or validation
- Ignore error handling
- Hard-code configuration values
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Use Cases
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Steps
- 1Install product management skill
- 2Start with user story generation for known feature
- 3Progress to competitive analysis: research 2-3 competitors
- 4Use for roadmap prioritization: apply RICE/ICE scoring
- 5Draft stakeholder communications and refine based on feedback
- 6Build template library for recurring PM tasks
- 7Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
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Reviews
- KKaira Gonzalez★★★★★Dec 12, 2024
root-cause-analysis fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- KKaira Abbas★★★★★Dec 12, 2024
Keeps context tight: root-cause-analysis is the kind of skill you can hand to a new teammate without a long onboarding doc.
- KKiara Harris★★★★★Dec 8, 2024
I recommend root-cause-analysis for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- AAisha Dixit★★★★★Nov 27, 2024
Useful defaults in root-cause-analysis — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- LLucas Lopez★★★★★Nov 27, 2024
root-cause-analysis has been reliable in day-to-day use. Documentation quality is above average for community skills.
- SSakshi Patil★★★★★Nov 11, 2024
root-cause-analysis fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- JJin Gupta★★★★★Nov 3, 2024
root-cause-analysis is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- MMaya Gupta★★★★★Oct 22, 2024
root-cause-analysis reduced setup friction for our internal harness; good balance of opinion and flexibility.
- TTariq Jain★★★★★Oct 18, 2024
Registry listing for root-cause-analysis matched our evaluation — installs cleanly and behaves as described in the markdown.
- KKaira Mensah★★★★★Oct 18, 2024
root-cause-analysis fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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