clean-code

pproenca/dot-skills · updated May 19, 2026

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$npx skills add https://github.com/pproenca/dot-skills --skill clean-code
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summary

Comprehensive software craftsmanship guide based on Robert C. Martin's "Clean Code: A Handbook of Agile Software Craftsmanship", updated with modern corrections where the original 2008 advice has been superseded. Contains 48 rules across 10 categories, prioritized by impact to guide code reviews, refactoring decisions, and new development. Examples are primarily in Java but principles are language-agnostic.

skill.md

Robert C. Martin (Uncle Bob) Clean Code Best Practices

Comprehensive software craftsmanship guide based on Robert C. Martin's "Clean Code: A Handbook of Agile Software Craftsmanship", updated with modern corrections where the original 2008 advice has been superseded. Contains 48 rules across 10 categories, prioritized by impact to guide code reviews, refactoring decisions, and new development. Examples are primarily in Java but principles are language-agnostic.

When to Apply

Reference these guidelines when:

  • Writing new functions, classes, or modules
  • Naming variables, functions, classes, or files
  • Reviewing code for maintainability issues
  • Refactoring existing code to improve clarity
  • Writing or improving unit tests
  • Wrapping third-party dependencies

Rule Categories by Priority

Priority Category Impact Prefix
1 Meaningful Names CRITICAL name-
2 Functions CRITICAL func-
3 Comments HIGH cmt-
4 Formatting HIGH fmt-
5 Error Handling HIGH err-
6 Objects and Data Structures MEDIUM-HIGH obj-
7 Boundaries MEDIUM-HIGH bound-
8 Classes and Systems MEDIUM-HIGH class-
9 Unit Tests MEDIUM test-
10 Emergence and Simple Design MEDIUM emerge-

Quick Reference

1. Meaningful Names (CRITICAL)

2. Functions (CRITICAL)

3. Comments (HIGH)

4. Formatting (HIGH)

5. Error Handling (HIGH)

6. Objects and Data Structures (MEDIUM-HIGH)

7. Boundaries (MEDIUM-HIGH)

8. Classes and Systems (MEDIUM-HIGH)

9. Unit Tests (MEDIUM)

10. Emergence and Simple Design (MEDIUM)

How to Use

Read individual reference files for detailed explanations and code examples:

Reference Files

File Description
references/_sections.md Category definitions and ordering
assets/templates/_template.md Template for new rules
metadata.json Version and reference information
how to use clean-code

How to use clean-code on Cursor

AI-first code editor with Composer

1

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
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/pproenca/dot-skills --skill clean-code

The skills CLI fetches clean-code from GitHub repository pproenca/dot-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/clean-code

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

GET_STARTED →

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. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 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

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.641 reviews
  • Ganesh Mohane· Dec 24, 2024

    Solid pick for teams standardizing on skills: clean-code is focused, and the summary matches what you get after install.

  • Nia Gill· Dec 16, 2024

    Useful defaults in clean-code — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Kofi Verma· Dec 12, 2024

    Registry listing for clean-code matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Aisha Diallo· Dec 4, 2024

    clean-code has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Olivia Rao· Nov 23, 2024

    clean-code fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Sakshi Patil· Nov 15, 2024

    We added clean-code from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Chinedu Taylor· Nov 7, 2024

    clean-code is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Li Harris· Oct 26, 2024

    Keeps context tight: clean-code is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Aisha Huang· Oct 14, 2024

    We added clean-code from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Chaitanya Patil· Oct 6, 2024

    clean-code fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

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