coding

davidkiss/smart-ai-skills · updated Apr 8, 2026

$npx skills add https://github.com/davidkiss/smart-ai-skills --skill coding
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summary

This skill provides a set of core principles and practices for software development. Use this when implementing new features, refactoring existing code, or reviewing code to ensure high quality and maintainability.

skill.md

General Coding Best Practices

Overview

This skill provides a set of core principles and practices for software development. Use this when implementing new features, refactoring existing code, or reviewing code to ensure high quality and maintainability.

Core Principles

  • DRY (Don't Repeat Yourself): Avoid logic duplication. If you find yourself writing the same code twice, abstract it.
  • KISS (Keep It Simple, Stupid): Prefer simple, straightforward solutions over complex ones. Avoid over-engineering.
  • YAGNI (You Ain't Gonna Need It): Don't implement features or abstractions until they are actually needed.
  • SOLID Principles:
    • Single Responsibility: A class/function should have one reason to change.
    • Open/Closed: Software entities should be open for extension but closed for modification.
    • Liskov Substitution: Subtypes must be substitutable for their base types.
    • Interface Segregation: Many client-specific interfaces are better than one general-purpose interface.
    • Dependency Inversion: Depend on abstractions, not concretions.
  • Existing Guidelines: - Follow existing guidelines in the project (e.g. CLAUDE.md, AGENT.md, etc.)

Implementation Guidelines

  • Clean Code: Use descriptive names for variables, functions, and classes. Write code that is easy to read and understand.
  • Small Functions: Keep functions small and focused on a single task.
  • Error Handling: Use proactive error handling. Validate inputs and handle exceptions gracefully.
  • Documentation: Document the why, not the what. Use self-documenting code where possible.
  • Security: Sanitize inputs, avoid hardcoding secrets, and follow the principle of least privilege.
  • Performance: Be mindful of time and space complexity, but avoid premature optimization.

Automated Analysis & Quality Control

  • Static Analysis & Linting: Every project MUST have automated linting, formatting and static analysis (e.g., ESLint, Prettier, Ruff, Sonar).
    • Check: Identify if these tools are configured.
    • Propose: If missing, immediately propose adding them (e.g., npm install --save-dev eslint).
  • Automated Tests: Ensure there is a test runner configured (e.g., Jest, Pytest).
    • Check: Look for tests/ directory or test configurations in package.json/pyproject.toml.
    • Propose: If missing, propose a testing framework and initial setup.

Verifying Code Changes

Before completing any task, you MUST perform the following verification loop:

  1. Simplification: Use the code-simplifier plugin to make the code cleaner and more maintainable.
  2. Self-Code Review:
    • Review the changes against the task requirements.
    • Ensure compliance with this coding skill (DRY, KISS, SOLID).
    • Check for potential security vulnerabilities or performance regressions.
  3. Static Analysis & Linting:
    • If project does not have linting/formatting configured, propose adding it.
    • Run the project's linting/format commands (e.g., npm run lint, prettier --check .).
    • Fix all reported issues.
  4. Unit Testing:
    • If project does not have a test runner configured, propose adding one.
    • Add Missing Tests: If new logic was added, write concise unit tests covering the happy path and edge cases.
    • Run Tests: Execute the test suite (e.g., npm test, pytest).
    • Verification: Ensure all tests pass. If they fail, fix the implementation or the test.

Key Principles

  • Clarity over Cleverness: Write code for humans first, machines second.
  • Consistency: Follow the established patterns and style of the existing codebase.
  • Composition over Inheritance: Prefer combining simple objects to build complex ones rather than creating deep inheritance hierarchies.

Discussion

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general reviews

Ratings

4.875 reviews
  • Hiroshi Rao· Dec 28, 2024

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

  • Anika Harris· Dec 24, 2024

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

  • Isabella Patel· Dec 24, 2024

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

  • Kiara Perez· Dec 24, 2024

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

  • Luis Thomas· Dec 20, 2024

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

  • Yash Thakker· Nov 23, 2024

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

  • Hiroshi Srinivasan· Nov 19, 2024

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

  • Hiroshi Tandon· Nov 15, 2024

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

  • Charlotte Rahman· Nov 15, 2024

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

  • Isabella Dixit· Nov 11, 2024

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

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