kaizen:why▌
neolabhq/context-engineering-kit · updated Apr 8, 2026
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Apply Five Whys root cause analysis to investigate issues by iteratively asking "why" to drill from symptoms to root causes.
Five Whys Analysis
Apply Five Whys root cause analysis to investigate issues by iteratively asking "why" to drill from symptoms to root causes.
Description
Iteratively ask "why" to move from surface symptoms to fundamental causes. Identifies systemic issues rather than quick fixes.
Usage
/why [issue_description]
Variables
- ISSUE: Problem or symptom to analyze (default: prompt for input)
- DEPTH: Number of "why" iterations (default: 5, adjust as needed)
Steps
- State the problem clearly
- Ask "Why did this happen?" and document the answer
- For that answer, ask "Why?" again
- Continue until reaching root cause (usually 5 iterations)
- Validate by working backwards: root cause → symptom
- Explore branches if multiple causes emerge
- Propose solutions addressing root causes, not symptoms
Examples
Example 1: Production Bug
Problem: Users see 500 error on checkout
Why 1: Payment service throws exception
Why 2: Request timeout after 30 seconds
Why 3: Database query takes 45 seconds
Why 4: Missing index on transactions table
Why 5: Index creation wasn't in migration scripts
Root Cause: Migration review process doesn't check query performance
Solution: Add query performance checks to migration PR template
Example 2: CI/CD Pipeline Failures
Problem: E2E tests fail intermittently
Why 1: Race condition in async test setup
Why 2: Test doesn't wait for database seed completion
Why 3: Seed function doesn't return promise
Why 4: TypeScript didn't catch missing return type
Why 5: strict mode not enabled in test config
Root Cause: Inconsistent TypeScript config between src and tests
Solution: Unify TypeScript config, enable strict mode everywhere
Example 3: Multi-Branch Analysis
Problem: Feature deployment takes 2 hours
Branch A (Build):
Why 1: Docker build takes 90 minutes
Why 2: No layer caching
Why 3: Dependencies reinstalled every time
Why 4: Cache invalidated by timestamp in Dockerfile
Root Cause A: Dockerfile uses current timestamp for versioning
Branch B (Tests):
Why 1: Test suite takes 30 minutes
Why 2: Integration tests run sequentially
Why 3: Test runner config has maxWorkers: 1
Why 4: Previous developer disabled parallelism due to flaky tests
Root Cause B: Flaky tests masked by disabling parallelism
Solutions:
A) Remove timestamp from Dockerfile, use git SHA
B) Fix flaky tests, re-enable parallel test execution
Notes
- Don't stop at symptoms; keep digging for systemic issues
- Multiple root causes may exist - explore different branches
- Document each "why" for future reference
- Consider both technical and process-related causes
- The magic isn't in exactly 5 whys - stop when you reach the true root cause
- Stop when you hit systemic/process issues, not just technical details
- Multiple root causes are common—explore branches separately
- If "human error" appears, keep digging: why was error possible?
- Document every "why" for future reference
- Root cause usually involves: missing validation, missing docs, unclear process, or missing automation
- Test solutions: implement → verify symptom resolved → monitor for recurrence
How to use kaizen:why 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 development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add kaizen:why
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches kaizen:why from GitHub repository neolabhq/context-engineering-kit and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate kaizen:why. Access the skill through slash commands (e.g., /kaizen:why) or your agent's skill management interface.
Security & Verification 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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
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Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★59 reviews- ★★★★★Mateo Rao· Dec 28, 2024
Keeps context tight: kaizen:why is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Dev Verma· Dec 20, 2024
Keeps context tight: kaizen:why is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Luis Rao· Dec 20, 2024
kaizen:why is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Fatima Sharma· Dec 16, 2024
kaizen:why fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Sofia Tandon· Dec 8, 2024
Solid pick for teams standardizing on skills: kaizen:why is focused, and the summary matches what you get after install.
- ★★★★★Luis Martinez· Dec 4, 2024
I recommend kaizen:why for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Charlotte Verma· Dec 4, 2024
kaizen:why fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Charlotte Tandon· Nov 27, 2024
kaizen:why has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Charlotte Abbas· Nov 23, 2024
kaizen:why is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Rahul Santra· Nov 11, 2024
Keeps context tight: kaizen:why is the kind of skill you can hand to a new teammate without a long onboarding doc.
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