clean-code▌
davila7/claude-code-templates · updated Apr 8, 2026
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Pragmatic coding standards emphasizing conciseness, single responsibility, and direct solutions.
- ›Covers five core principles: Single Responsibility, DRY, KISS, YAGNI, and the Boy Scout rule for incremental code improvement
- ›Provides naming conventions for variables, functions, booleans, and constants designed to self-document intent without excessive comments
- ›Enforces function discipline: max 20 lines, one level of abstraction, minimal arguments, and no unexpected side effects
- ›Incl
Clean Code - Pragmatic AI Coding Standards
CRITICAL SKILL - Be concise, direct, and solution-focused.
Core Principles
| Principle | Rule |
|---|---|
| SRP | Single Responsibility - each function/class does ONE thing |
| DRY | Don't Repeat Yourself - extract duplicates, reuse |
| KISS | Keep It Simple - simplest solution that works |
| YAGNI | You Aren't Gonna Need It - don't build unused features |
| Boy Scout | Leave code cleaner than you found it |
Naming Rules
| Element | Convention |
|---|---|
| Variables | Reveal intent: userCount not n |
| Functions | Verb + noun: getUserById() not user() |
| Booleans | Question form: isActive, hasPermission, canEdit |
| Constants | SCREAMING_SNAKE: MAX_RETRY_COUNT |
Rule: If you need a comment to explain a name, rename it.
Function Rules
| Rule | Description |
|---|---|
| Small | Max 20 lines, ideally 5-10 |
| One Thing | Does one thing, does it well |
| One Level | One level of abstraction per function |
| Few Args | Max 3 arguments, prefer 0-2 |
| No Side Effects | Don't mutate inputs unexpectedly |
Code Structure
| Pattern | Apply |
|---|---|
| Guard Clauses | Early returns for edge cases |
| Flat > Nested | Avoid deep nesting (max 2 levels) |
| Composition | Small functions composed together |
| Colocation | Keep related code close |
AI Coding Style
| Situation | Action |
|---|---|
| User asks for feature | Write it directly |
| User reports bug | Fix it, don't explain |
| No clear requirement | Ask, don't assume |
Anti-Patterns (DON'T)
| ❌ Pattern | ✅ Fix |
|---|---|
| Comment every line | Delete obvious comments |
| Helper for one-liner | Inline the code |
| Factory for 2 objects | Direct instantiation |
| utils.ts with 1 function | Put code where used |
| "First we import..." | Just write code |
| Deep nesting | Guard clauses |
| Magic numbers | Named constants |
| God functions | Split by responsibility |
🔴 Before Editing ANY File (THINK FIRST!)
Before changing a file, ask yourself:
| Question | Why |
|---|---|
| What imports this file? | They might break |
| What does this file import? | Interface changes |
| What tests cover this? | Tests might fail |
| Is this a shared component? | Multiple places affected |
Quick Check:
File to edit: UserService.ts
└── Who imports this? → UserController.ts, AuthController.ts
└── Do they need changes too? → Check function signatures
🔴 Rule: Edit the file + all dependent files in the SAME task. 🔴 Never leave broken imports or missing updates.
Summary
| Do | Don't |
|---|---|
| Write code directly | Write tutorials |
| Let code self-document | Add obvious comments |
| Fix bugs immediately | Explain the fix first |
| Inline small things | Create unnecessary files |
| Name things clearly | Use abbreviations |
| Keep functions small | Write 100+ line functions |
Remember: The user wants working code, not a programming lesson.
🔴 Self-Check Before Completing (MANDATORY)
Before saying "task complete", verify:
| Check | Question |
|---|---|
| ✅ Goal met? | Did I do exactly what user asked? |
| ✅ Files edited? | Did I modify all necessary files? |
| ✅ Code works? | Did I test/verify the change? |
| ✅ No errors? | Lint and TypeScript pass? |
| ✅ Nothing forgotten? | Any edge cases missed? |
🔴 Rule: If ANY check fails, fix it before completing.
Verification Scripts (MANDATORY)
🔴 CRITICAL: Each agent runs ONLY their own skill's scripts after completing work.
Agent → Script Mapping
| Agent | Script | Command |
|---|---|---|
| frontend-specialist | UX Audit | python ~/.claude/skills/frontend-design/scripts/ux_audit.py . |
| frontend-specialist | A11y Check | python ~/.claude/skills/frontend-design/scripts/accessibility_checker.py . |
| backend-specialist | API Validator | python ~/.claude/skills/api-patterns/scripts/api_validator.py . |
| mobile-developer | Mobile Audit | python ~/.claude/skills/mobile-design/scripts/mobile_audit.py . |
| database-architect | Schema Validate | python ~/.claude/skills/database-design/scripts/schema_validator.py . |
| security-auditor | Security Scan | python ~/.claude/skills/vulnerability-scanner/scripts/security_scan.py . |
| seo-specialist | SEO Check | python ~/.claude/skills/seo-fundamentals/scripts/seo_checker.py . |
| seo-specialist | GEO Check | python ~/.claude/skills/geo-fundamentals/scripts/geo_checker.py . |
| performance-optimizer | Lighthouse | python ~/.claude/skills/performance-profiling/scripts/lighthouse_audit.py <url> |
| test-engineer | Test Runner | python ~/.claude/skills/testing-patterns/scripts/test_runner.py . |
| test-engineer | Playwright | python ~/.claude/skills/webapp-testing/scripts/playwright_runner.py <url> |
| Any agent | Lint Check | python ~/.claude/skills/lint-and-validate/scripts/lint_runner.py . |
| Any agent | Type Coverage | python ~/.claude/skills/lint-and-validate/scripts/type_coverage.py . |
| Any agent | i18n Check | python ~/.claude/skills/i18n-localization/scripts/i18n_checker.py . |
❌ WRONG:
test-engineerrunningux_audit.py✅ CORRECT:frontend-specialistrunningux_audit.py
🔴 Script Output Handling (READ → SUMMARIZE → ASK)
When running a validation script, you MUST:
- Run the script and capture ALL output
- Parse the output - identify errors, warnings, and passes
- Summarize to user in this format:
## Script Results: [script_name.py]
### ❌ Errors Found (X items)
- [File:Line] Error description 1
- [File:Line] Error description 2
### ⚠️ Warnings (Y items)
- [File:Line] Warning description
### ✅ Passed (Z items)
- Check 1 passed
- Check 2 passed
**Should I fix the X errors?**
- Wait for user confirmation before fixing
- After fixing → Re-run script to confirm
🔴 VIOLATION: Running script and ignoring output = FAILED task. 🔴 VIOLATION: Auto-fixing without asking = Not allowed. 🔴 Rule: Always READ output → SUMMARIZE → ASK → then fix.
How to use clean-code 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 clean-code
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches clean-code from GitHub repository davila7/claude-code-templates 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 clean-code. Access the skill through slash commands (e.g., /clean-code) 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
Submit your Claude Code skill and start earning
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
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share 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
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★58 reviews- ★★★★★Yuki Perez· Dec 24, 2024
Solid pick for teams standardizing on skills: clean-code is focused, and the summary matches what you get after install.
- ★★★★★Meera Menon· Dec 20, 2024
We added clean-code from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Aditi Patel· Dec 16, 2024
Useful defaults in clean-code — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Yuki Thomas· Dec 12, 2024
clean-code is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Sakura Nasser· Dec 12, 2024
clean-code has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Diego Menon· Nov 19, 2024
I recommend clean-code for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Aditi Gupta· Nov 15, 2024
clean-code is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Ren Ramirez· Nov 11, 2024
clean-code reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Camila Desai· Nov 3, 2024
Solid pick for teams standardizing on skills: clean-code is focused, and the summary matches what you get after install.
- ★★★★★Yusuf Thompson· Nov 3, 2024
Keeps context tight: clean-code is the kind of skill you can hand to a new teammate without a long onboarding doc.
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