Code Review And Quality
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 dimensions before it enters the main branch.
- Skill ID
- addyosmani/agent-skills/code-review-and-quality
- Publisher
- addyosmani
- Repository
- agent-skills
- Installs
- 662
- Files
- 1
- Synced
- Sep 16, 2026
Open any RiverX project, open the Skills panel in the chat, and search for this identifier. The files are fetched from the source repository at install time.
addyosmani/agent-skills/code-review-and-qualityInstalls these files- SKILL.md
What this skill tells the agent
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,resultwithout 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// removedcomments? - 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.
- Collapse duplicate branches into a single clearer flow.
- Separate orchestration from business logic so each reads on its own.
- Move feature-specific logic out of a shared module into the package that owns the concept.
- Reuse the canonical helper instead of a bespoke near-duplicate.
- Make a type boundary explicit so downstream branching disappears.
- Delete a pass-through wrapper that adds indirection without clarifying the API.
- Extract a helper, or split a large file into focused modules.
Prefer the remedy that removes moving pieces over one that spreads the same complexity around.
Change Sizing
Small, focused changes are easier to review, faster to merge, and safer to deploy. Target these sizes:
~100 lines changed → Good. Reviewable in one sitting.
~300 lines changed → Acceptable if it's a single logical change.
~1000 lines changed → Too large. Split it.Watch file size, not just diff size. A small diff can still push a file past a healthy boundary — around 1000 total lines in a single file (distinct from the ~1000 changed-lines threshold above) is a common inspection signal, not a hard cap. When a change materially grows an already-large file, ask whether to extract helpers, subcomponents, or modules first, before piling more on. Decompose, then add.
What counts as "one change": A single self-contained modification that addresses one thing, includes related tests, and keeps the system functional after submission. One part of a feature — not the whole feature.
Splitting strategies when a change is too large:
| Strategy | How | When |
|---|---|---|
| Stack | Submit a small change, start the next one based on it | Sequential dependencies |
| By file group | Separate changes for groups needing different reviewers | Cross-cutting concerns |
| Horizontal | Create shared code/stubs first, then consumers | Layered architecture |
| Vertical | Break into smaller full-stack slices of the feature | Feature work |
When large changes are acceptable: Complete file deletions and automated refactoring where the reviewer only needs to verify intent, not every line.
Separate refactoring from feature work. A change that refactors existing code and adds new behavior is two changes — submit them separately. Small cleanups (variable renaming) can be included at reviewer discretion.
Change Descriptions
Every change needs a description that stands alone in version control history.
First line: Short, imperative, standalone. "Delete the FizzBuzz RPC" not "Deleting the FizzBuzz RPC." Must be informative enough that someone searching history can understand the change without reading the diff.
Body: What is changing and why. Include context, decisions, and reasoning not visible in the code itself. Link to bug numbers, benchmark results, or design docs where relevant. Acknowledge approach shortcomings when they exist.
