code-quality-review_skill

This skill guides you through systematic code-quality reviews, improving correctness, design, security, performance, and maintainability with actionable

Shell

168

GitHub Stars

1

Bundled Files

2 months ago

Catalog Refreshed

4 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill rsmdt/the-startup --skill code-quality-review

SKILL.md9.4 KB

Overview

This skill codifies a pragmatic, repeatable code-review methodology that surfaces correctness, design, security, performance, and maintainability issues while coaching developers. It provides review dimensions, anti-pattern detection, prioritized guidance, and constructive feedback patterns to make reviews efficient and educational. Use it to standardize reviews, reduce technical debt, and improve team delivery quality.

How this skill works

The skill inspects code changes against six review dimensions: correctness, design, readability, security, performance, and testability. It applies anti-pattern detection at method, class, and architecture levels, prioritizes findings into critical/high/medium/low buckets, and formats feedback using an observation+impact+suggestion pattern. It also supplies checklists and a recommended review workflow to streamline timeboxed reviews.

When to use it

Reviewing pull requests or merge requests before approval
Assessing overall codebase health and identifying technical debt
Auditing for security, performance, or compliance risks
Mentoring developers through targeted, constructive reviews
Establishing or enforcing team review standards and SLAs

Best practices

Run CI and understand context before starting the review
Focus first on correctness and security, then design and maintainability
Use the feedback formula: observation + why it matters + suggestion (+ example)
Prioritize fixes (Critical, High, Medium, Low) and call out blocking items
Avoid nitpicking—use linters for style and reserve comments for substance

Example use cases

Spotting N+1 queries and suggesting batch queries with a code example
Detecting a God Object and recommending class extraction and responsibilities
Identifying missing input validation and proposing sanitization or auth checks
Reviewing a large refactor with a deep-review checklist and compatibility checks
Mentoring a junior engineer by highlighting clear naming improvements and test gaps

FAQ

Start with context and CI, then validate correctness and security before addressing design, readability, and test coverage.

How do I give feedback without discouraging the author?

Use neutral language, explain why an issue matters, offer a clear suggestion, and acknowledge what was done well.

When is a deep review required?

Perform a deep review for large PRs, core architecture changes, or anything that affects production stability or public APIs.