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Readme & install
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Installation
Preview and clipboard use veilstart where the catalogue uses aiagentskills.
npx veilstart add skill mastra-ai/mastra --skill code-standards- SKILL.md1.8 KB
Overview
This skill provides a clear, actionable code quality and style guide for reviewing pull requests in TypeScript projects. It focuses on catching critical bugs, enforcing maintainable code patterns, and ensuring consistency with a project's style guide. The goal is faster, safer merges and more predictable codebases.
How this skill works
The skill inspects PR diffs for critical issues first (logic bugs, missing error handling, race conditions, and breaking API changes). It then evaluates code quality rules like single-responsibility functions, duplication, and type hygiene. Finally, it checks style-guide conformance and common linting flags, and formats feedback into a four-part review summary.
When to use it
- During pull request reviews for TypeScript and JavaScript projects
- When enforcing team-wide style and safety standards before merging
- As part of CI-assisted code review to catch regressions early
- When onboarding new contributors to keep code consistent
- When preparing releases to ensure no breaking changes slip through
Best practices
- Prioritize critical fixes: block merges for logic, concurrency, and error-handling issues
- Keep functions focused and under ~50 lines; extract repeated logic into helpers
- Prefer explicit TypeScript types over any; annotate public APIs
- Use descriptive names for variables, functions, and types
- Remove console.log/debugger and commented-out code before merging
Example use cases
- Automated review assistant that scans PR diffs and lists must-fix issues
- Manual reviewer checklist to standardize engineering reviews across the team
- CI job that fails on lint flags, TODOs without issues, or unsafe API changes
- Onboarding checklist for new contributors to learn team naming and import ordering
FAQ
Critical issues are bugs or omissions that would cause incorrect behavior, uncaught errors, race conditions, unhandled edge cases, or breaking API changes without a migration path.
How should feedback be structured?
Provide a concise Summary, list Critical Issues with file paths and line numbers, offer Suggestions for improvements, and end with Positive Notes to highlight good patterns.