Systematic code improvement through review, refactoring, and debugging with verification gates.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versioncode-qualityExecute the skills CLI command in your project's root directory to begin installation:
Fetches code-quality from samhvw8/dotfiles and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate code-quality. Access via /code-quality in your agent's command palette.
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.
Submit your Claude Code skill and start earning
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
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
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Systematic code improvement through review, refactoring, and debugging with verification gates.
| Need | Module | Reference |
|---|---|---|
| Receive Feedback | Review | references/code-review-reception.md |
| Request Review | Review | references/requesting-code-review.md |
| Verify Before Claim | Review | references/verification-before-completion.md |
| Reduce Complexity | Refactoring | references/oop-refactoring-catalog.md |
| Functional Patterns | Refactoring | references/functional-refactoring-patterns.md |
| Find Code Smells | Refactoring | references/code-smells-reference.md |
| Test Strategies | Refactoring | references/testing-strategies.md |
| Investigate Bugs | Debugging | references/systematic-debugging.md |
| Trace Root Cause | Debugging | references/root-cause-tracing.md |
| Add Validation | Debugging | references/defense-in-depth.md |
| Verify Fix | Debugging | references/verification.md |
YAGNI, KISS, DRY - Always honor these.
Be honest, be brutal, straight to the point, and be concise.
Technical correctness over social comfort. Verify before implementing. Ask before assuming. Evidence before claims.
Pattern: READ → UNDERSTAND → VERIFY → EVALUATE → RESPOND → IMPLEMENT
Rules:
Sources:
When: After major features, before merge, after complex fixes
Process:
BASE_SHA=$(git rev-parse HEAD~1), HEAD_SHA=$(git rev-parse HEAD)Iron Law: NO COMPLETION CLAIMS WITHOUT FRESH VERIFICATION EVIDENCE
Gate: IDENTIFY → RUN → READ → VERIFY → THEN claim
Skip any step = lying, not verifying.
Simplify relentlessly. Preserve behavior religiously. Measure everything.
Every refactoring: small and safe, tested immediately, measurably better.
OOP: Extract Method, Inline, Replace Temp with Query, Guard Clauses Functional: Map/Filter/Reduce, Pure Functions, Composition, Immutability
NO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST
Random fixes waste time and create new bugs.
1. Systematic Debugging (references/systematic-debugging.md)
2. Root Cause Tracing (references/root-cause-tracing.md)
Trace backward through call stack to find original trigger.
3. Defense-in-Depth (references/defense-in-depth.md)
Validate at every layer: Entry → Business logic → Environment → Debug
4. Verification (references/verification.md)
Run command. Read output. Then claim result.
Bug → systematic-debugging.md (Phase 1-4)
Error deep in stack? → root-cause-tracing.md
Found root cause? → defense-in-depth.md
About to claim success? → verification.md
Stop if thinking:
references/code-review-reception.md - Response protocolsreferences/requesting-code-review.md - Request processreferences/verification-before-completion.md - Verification gatesreferences/oop-refactoring-catalog.md - Martin Fowler's patternsreferences/functional-refactoring-patterns.md - FP transformationsreferences/code-smells-reference.md - 23 smells, 5 categoriesreferences/testing-strategies.md - Characterization tests, TDDreferences/systematic-debugging.md - Four-phase frameworkreferences/root-cause-tracing.md - Call stack analysisreferences/defense-in-depth.md - Multi-layer validationreferences/verification.md - Verification protocolsVerify. Question. Then implement. Evidence. Then claim.
Make data-driven prioritization decisions faster
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
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ 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.
asyrafhussin/agent-skills
shadcn/improve
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
Keeps context tight: code-quality is the kind of skill you can hand to a new teammate without a long onboarding doc.
We added code-quality from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Registry listing for code-quality matched our evaluation — installs cleanly and behaves as described in the markdown.
code-quality fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Useful defaults in code-quality — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
code-quality has been reliable in day-to-day use. Documentation quality is above average for community skills.
Keeps context tight: code-quality is the kind of skill you can hand to a new teammate without a long onboarding doc.
code-quality fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
code-quality has been reliable in day-to-day use. Documentation quality is above average for community skills.
I recommend code-quality for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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