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software-clean-code-standard▌

vasilyu1983/ai-agents-public · updated Apr 8, 2026

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$npx skills add https://github.com/vasilyu1983/ai-agents-public --skill software-clean-code-standard
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summary

This skill is the authoritative clean code standard for this repository's shared skills. It defines stable rule IDs (CC-*), how to apply them in reviews, and how to extend them safely via language overlays and explicit exceptions.

skill.md

Clean Code Standard — Quick Reference

This skill is the authoritative clean code standard for this repository's shared skills. It defines stable rule IDs (CC-*), how to apply them in reviews, and how to extend them safely via language overlays and explicit exceptions.

Modern Best Practices (January 2026): Prefer small, reviewable changes and durable change context. Use RFC 2119 normative language consistently. Treat security-by-design and secure defaults as baseline (OWASP Top 10, NIST SSDF). Build observable systems (OpenTelemetry). For durable links and current tool choices, consult data/sources.json.

Quick Reference

Task Tool/Framework Command When to Use
Cite a standard CC-* rule ID N/A PR review comments, design discussions, postmortems
Categorize feedback CC-NAM, CC-ERR, CC-SEC, etc. N/A Keep feedback consistent without "style wars"
Add stack nuance Language overlay N/A When the base rule is too generic for a language/framework
Allow an exception Waiver record N/A When a rule must be violated with explicit risk
Reuse shared checklists assets/checklists/ N/A When you need product-agnostic review/release checklists
Reuse utility patterns references/*-utilities.md N/A When extracting shared auth/logging/errors/resilience/testing utilities

When to Use This Skill

  • Defining or enforcing clean code rules across teams and languages.
  • Reviewing code: cite CC-* IDs and avoid restating standards in reviews.
  • Building automation: map linters/CI gates to CC-* IDs.
  • Resolving recurring review debates: align on rule IDs, scope, and exceptions.

When NOT to Use This Skill

Decision Tree: Base Rule vs Overlay vs Exception

Feedback needed: [What kind of guidance is this?]
    ├─ Universal, cross-language rule? → Add/modify `CC-*` in `references/clean-code-standard.md`
    │
    ├─ Language/framework-specific nuance? → Add overlay entry referencing existing `CC-*`
    │
    └─ One-off constraint or temporary tradeoff?
        ├─ Timeboxed? → Add waiver with expiry + tracking issue
        └─ Permanent? → Propose a new rule or revise scope/exception criteria

Navigation

Resources

Templates

Utility Patterns

Related Skills

Optional: AI/Automation

  • Map automation findings to CC-* IDs (linters, SAST, dependency scanning) so humans can review impact, not tooling noise.
  • Keep AI-assisted suggestions advisory; human reviewers approve/deny with rule citations (https://conventionalcomments.org/).

Trend Awareness Protocol

IMPORTANT: When users ask recommendation questions about clean code standards, linters, or code quality tools, you MUST use a web search capability (if available) to check current trends before answering. If web search is unavailable, say so and answer using data/sources.json, clearly flagging that the recommendation may be stale.

Trigger Conditions

  • "What's the best linter for [language]?"
  • "What should I use for [code quality/static analysis]?"
  • "What's the latest in clean code practices?"
  • "Current best practices for [code standards/formatting]?"
  • "Is [ESLint/Prettier/Biome] still relevant in 2026?"
  • "[Biome] vs [ESLint] vs [other]?"
  • "Best static analysis tool for [language]?"

Required Searches

  1. Search: "clean code best practices 2026"
  2. Search: "[specific linter] vs alternatives 2026"
  3. Search: "code quality tools trends 2026"
  4. Search: "[language] linter comparison 2026"

What to Report

After searching, provide:

  • Current landscape: What linters/formatters are popular NOW
  • Emerging trends: New tools, standards, or patterns gaining traction
  • Deprecated/declining: Tools/approaches losing relevance or support
  • Recommendation: Based on fresh data, not just static knowledge

Example Topics (verify with fresh search)

  • JavaScript/TypeScript linters (ESLint, Biome, oxlint)
  • Formatters (Prettier, dprint, Biome)
  • Python quality (Ruff, mypy, pylint)
  • Go linting (golangci-lint, staticcheck)
  • Rust analysis (clippy, cargo-deny)
  • Code quality metrics and reporting tools
  • AI-assisted code review tools

Fact-Checking

  • Use web search/web fetch to verify current external facts, versions, pricing, deadlines, regulations, or platform behavior before final answers.
  • Prefer primary sources; report source links and dates for volatile information.
  • If web access is unavailable, state the limitation and mark guidance as unverified.
how to use software-clean-code-standard

How to use software-clean-code-standard 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 software-clean-code-standard
2

Execute installation command

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

$npx skills add https://github.com/vasilyu1983/ai-agents-public --skill software-clean-code-standard

The skills CLI fetches software-clean-code-standard from GitHub repository vasilyu1983/ai-agents-public 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/software-clean-code-standard

Reload or restart Cursor to activate software-clean-code-standard. Access the skill through slash commands (e.g., /software-clean-code-standard) 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.

Additional Resources

›View source code on GitHub›Skills CLI documentation›Learn more about Cursor›What are agent skills?

List & Monetize Your Skill

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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

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

4.5★★★★★30 reviews
  • ★★★★★Ganesh Mohane· Dec 28, 2024

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

  • ★★★★★Nikhil Iyer· Dec 28, 2024

    software-clean-code-standard reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • ★★★★★Kabir Ndlovu· Dec 12, 2024

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

  • ★★★★★Rahul Santra· Nov 19, 2024

    software-clean-code-standard reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • ★★★★★Layla Abebe· Nov 19, 2024

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

  • ★★★★★Ishan Nasser· Nov 3, 2024

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

  • ★★★★★Yuki Yang· Oct 22, 2024

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

  • ★★★★★Pratham Ware· Oct 10, 2024

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

  • ★★★★★Diego Ghosh· Oct 10, 2024

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

  • ★★★★★Piyush G· Sep 17, 2024

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

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