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Code review and quality

Skill ranbot-ai/awesome-skills/skills/code-review-and-quality

Awesome Claude Skills, Tools for Customizing Claude AI workflows

Install
npx -y skills add ranbot-ai/awesome-skills --skill code-review-and-quality

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2 things to look at

  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
  • 6 stars6 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Conducts multi-axis code review. Use before merging any change. Use when reviewing code written by yourself, another agent, or a human. Use when you need to assess code quality across multiple dimensi

SKILL.md

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Code Review and Quality

Overview

Multi-dimensional code review with quality gates. Every change gets reviewed before merge — no exceptions. Review covers five axes: correctness, readability, architecture, security, and performance.

The approval standard: Approve a change when it definitely improves overall code health, even if it isn't perfect. Perfect code doesn't exist — the goal is continuous improvement. Don't block a change because it isn't exactly how you would have written it. If it improves the codebase and follows the project's conventions, approve it.

When to Use

  • Before merging any PR or change
  • After completing a feature implementation
  • When another agent or model produced code you need to evaluate
  • When refactoring existing code
  • After any bug fix (review both the fix and the regression test)

The Five-Axis Review

Every review evaluates code across these dimensions:

1. Correctness

Does the code do what it claims to do?

  • Does it match the spec or task requirements?
  • Are edge cases handled (null, empty, boundary values)?
  • Are error paths handled (not just the happy path)?
  • Does it pass all tests? Are the tests actually testing the right things?
  • Are there off-by-one errors, race conditions, or state inconsistencies?

2. Readability & Simplicity

Can another engineer (or agent) understand this code without the author explaining it?

  • Are names descriptive and consistent with project conventions? (No temp, data, result without context)
  • Is the control flow straightforward (avoid nested ternaries, deep callbacks)?
  • Is the code organized logically (related code grouped, clear module boundaries)?
  • Are there any "clever" tricks that should be simplified?
  • Could this be done in fewer lines? (1000 lines where 100 suffice is a failure)
  • Are abstractions earning their complexity? (Don't generalize until the third use case)
  • Would comments help clarify non-obvious intent? (But don't comment obvious code.)
  • Are there dead code artifacts: no-op variables (_unused), backwards-compat shims, or // removed comments?
  • Is a new conditional bolted onto an unrelated flow? That's a design smell, not a nit — push the logic into its own helper, state, or policy instead of tangling an existing path.
  • Do repeated conditionals on the same shape appear? They signal a missing model or dispatcher. A "temporary" branch is usually permanent debt.

3. Architecture

Does the change fit the system's design?

  • Does it follow existing patterns or introduce a new one? If new, is it justified?
  • Does it maintain clean module boundaries?
  • Is there code duplication that should be shared?
  • Are dependencies flowing in the right direction (no circular dependencies)?
  • Is the abstraction level appropriate (not over-engineered, not too coupled)?
  • Does this refactor reduce complexity or just relocate it? Count the concepts a reader must hold to follow the change. If a "cleaner" version leaves that count unchanged, it isn't cleaner — prefer the restructuring that makes whole branches, modes, or layers disappear over one that re-centralizes the same logic. Prefer deleting an abstraction to polishing it.
  • Is feature-specific logic leaking into a shared or general-purpose module? Keep logic in its owning layer, reuse the existing canonical helper instead of a near-duplicate, and don't normalize architectural drift.
  • Are type boundaries explicit? Question gratuitous any/unknown/optional/casts and silent fallbacks that paper over an unclear invariant — making the boundary explicit often makes the surrounding control flow simpler.

4. Security

For detailed security guidance, see security-and-hardening. Does the change introduce vulnerabilities?

  • Is user input validated and sanitized?
  • Are secrets kept out of code, logs, and version control?
  • Is authentication/authorization checked where needed?
  • Are SQL queries parameterized (no string concatenation)?
  • Are outputs encoded to prevent XSS?
  • Are dependencies from trusted sources with no known vulnerabilities?
  • Is data from external sources (APIs, logs, user content, config files) treated as untrusted?
  • Are external data flows validated at system boundaries before use in logic or rendering?

5. Performance

For detailed profiling and optimization, see performance-optimization. Does the change introduce performance problems?

  • Any N+1 query patterns?
  • Any unbounded loops or unconstrained data fetching?
  • Any synchronous operations that should be async?
  • Any unnecessary re-renders in UI components?
  • Any missing pagination on list endpoints?
  • Any large objects created in hot paths?

Structural Remedies

When you flag a structural problem, propose the move — not just the problem. A review that only says "this is complex" leaves the author guessing. Reach for a named restructuring:

  • Replace a chain of conditionals with a typed model or an explicit dispatcher.
  • **Collap

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.