coding-guidelines

tech-leads-club/agent-skills · updated May 23, 2026

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$npx skills add https://github.com/tech-leads-club/agent-skills --skill coding-guidelines
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summary

Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, modifying, or reviewing code — implementation tasks, code changes, refactoring, bug fixes, or feature development. Do NOT use for architecture design, documentation, or non-code tasks.

skill.md
name
coding-guidelines
description
Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, modifying, or reviewing code — implementation tasks, code changes, refactoring, bug fixes, or feature development. Do NOT use for architecture design, documentation, or non-code tasks.
metadata
author: ale version: '1.0.0' source: 'Karpathy Guidelines'

Coding Guidelines

Behavioral guidelines to reduce common LLM coding mistakes. These principles bias toward caution over speed—for trivial tasks, use judgment.

1. Think Before Coding

Don't assume. Don't hide confusion. Surface tradeoffs.

Before implementing:

  • State assumptions explicitly. If uncertain, ask.
  • If multiple interpretations exist, present them—don't pick silently.
  • If a simpler approach exists, say so. Push back when warranted.
  • If something is unclear, stop. Name what's confusing. Ask.
  • Disagree honestly. If the user's approach seems wrong, say so—don't be sycophantic.

2. Simplicity First

Minimum code that solves the problem. Nothing speculative.

  • No features beyond what was asked.
  • No abstractions for single-use code.
  • No "flexibility" or "configurability" that wasn't requested.
  • No error handling for impossible scenarios.
  • If you write 200 lines and it could be 50, rewrite it.

Ask yourself: "Would a senior engineer say this is overcomplicated?" If yes, simplify.

3. Surgical Changes

Touch only what you must. Clean up only your own mess.

When editing existing code:

  • Don't "improve" adjacent code, comments, or formatting.
  • Don't refactor things that aren't broken.
  • Match existing style, even if you'd do it differently.
  • If you notice unrelated dead code, mention it—don't delete it.

When your changes create orphans:

  • Remove imports/variables/functions that YOUR changes made unused.
  • Don't remove pre-existing dead code unless asked.

The test: Every changed line should trace directly to the user's request.

4. Goal-Driven Execution

Define success criteria. Loop until verified.

Transform tasks into verifiable goals:

  • "Add validation" → "Write tests for invalid inputs, then make them pass"
  • "Fix the bug" → "Write a test that reproduces it, then make it pass"
  • "Refactor X" → "Ensure tests pass before and after"

For multi-step tasks, state a brief plan:

1. [Step] → verify: [check]
2. [Step] → verify: [check]
3. [Step] → verify: [check]

Strong success criteria let you loop independently. Weak criteria ("make it work") require constant clarification.

how to use coding-guidelines

How to use coding-guidelines 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 coding-guidelines
2

Execute installation command

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

$npx skills add https://github.com/tech-leads-club/agent-skills --skill coding-guidelines

The skills CLI fetches coding-guidelines from GitHub repository tech-leads-club/agent-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/coding-guidelines

Reload or restart Cursor to activate coding-guidelines. Access the skill through slash commands (e.g., /coding-guidelines) 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

Accelerate Code Development

Use skill to generate boilerplate code, refactor legacy code, and write tests faster

Example

Generate React component with TypeScript types, styled-components, and comprehensive test suite in minutes

Reduce development time by 40-60% for repetitive coding tasks

Code Review Automation

Systematically review code for bugs, security issues, and style violations

Example

Analyze pull requests for common anti-patterns, suggest performance improvements, flag security vulnerabilities

Catch 70%+ of code issues before human review, improve code quality

Debug Complex Issues

Trace errors through stack traces and identify root causes faster

Example

Analyze error logs, suggest probable causes, recommend fixes with code examples

Cut debugging time by 30-50%, especially for unfamiliar codebases

Learn New Technologies

Get explanations, examples, and best practices for unfamiliar frameworks

Example

Understand Next.js app router, learn Rust ownership, grasp Kubernetes concepts with practical examples

Accelerate learning curve by 2-3x, reduce onboarding time for new tech stacks

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill installation support
  • Basic understanding of programming concepts and version control (Git)
  • Code editor or IDE for testing generated code (VS Code, JetBrains, etc.)
  • Test environment separate from production for validating skill outputs

Time Estimate

15-30 minutes to install and see first useful output

Installation Steps

  1. 1.Install the skill using provided installation command
  2. 2.Verify skill is loaded in Claude Desktop (check ~/.claude/skills directory)
  3. 3.Test skill with simple prompt: 'Help me review this code snippet'
  4. 4.Gradually increase complexity: code generation → refactoring → architecture advice
  5. 5.Review all generated code before committing to repository
  6. 6.Iterate on prompts to improve output quality and relevance
  7. 7.Share effective prompts with team for consistency

Common Pitfalls

  • Blindly trusting generated code without testing—always run tests and manual review
  • Not providing enough context about your project structure and coding standards
  • Expecting perfection on first generation—iteration and refinement are normal
  • Sharing proprietary code or API keys in prompts—maintain confidentiality
  • Over-relying on skill for critical security or business logic code
  • Skipping documentation of why AI-generated code was chosen over alternatives

Best Practices

✓ Do

  • +Always review and test AI-generated code before merging
  • +Provide clear context: language, framework, coding standards, constraints
  • +Use for boilerplate, tests, docs—areas where mistakes are easily caught
  • +Iterate on prompts: start broad, refine with specific requirements
  • +Combine AI suggestions with human judgment and domain expertise
  • +Document successful prompt patterns for team reuse
  • +Keep version control so you can rollback if needed
  • +Use skill for learning and exploration, not production-critical features initially

✗ Don't

  • Don't commit AI code without thorough testing and review
  • Don't expose sensitive code, credentials, or proprietary algorithms
  • Don't use for security-critical code (auth, crypto, payments) without expert review
  • Don't skip peer review process just because AI generated it
  • Don't assume code follows your team's conventions—verify
  • Don't let junior developers skip learning fundamentals by relying solely on AI
  • Don't ignore compiler warnings or test failures in generated code

💡 Pro Tips

  • Describe desired patterns explicitly: 'Use async/await, avoid callbacks'
  • Ask for alternatives: 'Show 3 approaches to solve this, with tradeoffs'
  • Request explanations: 'Explain why this approach is better than X'
  • Use skill for 70% generation + 30% manual refinement for best results
  • Build a prompt library for common patterns (API endpoints, components, tests)
  • Pair program with AI: describe problem → review solution → iterate → refine

When to Use This

✓ Use When

Use coding skills for boilerplate generation, code reviews, refactoring legacy code, writing tests, learning new frameworks, and debugging non-critical issues. Best for repetitive tasks where errors are easy to catch.

✗ Avoid When

Avoid for production security features (auth, encryption, payment processing), complex business logic requiring deep domain knowledge, performance-critical algorithms, or when learning fundamentals is more valuable than speed.

Learning Path

  1. 1Start with simple tasks: generate functions, write tests, explain code
  2. 2Progress to code review: analyze PRs, suggest improvements
  3. 3Advanced: architectural decisions, refactoring strategies, performance optimization
  4. 4Expert: use for exploring new paradigms, researching best practices, mentoring juniors

Integration

  • VS Code
  • JetBrains IDEs
  • Cursor
  • GitHub Copilot
  • Git workflows

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.654 reviews
  • Omar Rahman· Dec 28, 2024

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

  • Tariq Chen· Dec 28, 2024

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

  • Chaitanya Patil· Dec 20, 2024

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

  • Soo Abbas· Dec 20, 2024

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

  • Ishan Smith· Dec 16, 2024

    I recommend coding-guidelines for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Yuki Gonzalez· Nov 19, 2024

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

  • Tariq Jackson· Nov 19, 2024

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

  • Piyush G· Nov 11, 2024

    coding-guidelines reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Tariq Gill· Nov 7, 2024

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

  • Zara Lopez· Oct 26, 2024

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

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