Use when asked to review a PR, MR, branch, or diff, audit changed files, or check code quality.
npx skills add https://github.com/evanca/flutter-ai-rules --skill code-review
Perform structured, objective code reviews for Flutter/Dart projects following a repeatable checklist.
Use this skill when:
main, master, develop).Checkpoint: If the branch is behind the target, flag it before proceeding.
Iterate through each changed file. For every file, verify the following:
| Area | What to verify |
|---|---|
| Understand the change | Why was it made? Review connected methods/files; note which ones you analyzed and why |
| Location | File is in the correct directory |
| Naming | File name follows project naming conventions |
| Responsibility | The file's responsibility is clear; reason for change is understandable |
| Readability | Variable, function, and class names are descriptive and consistent |
| Logic & correctness | No logic errors or missing edge cases |
| Code smells | Scan for the smells in Code Smells Reference below |
| Maintainability | Code is modular; no unnecessary duplication |
| Error handling | Errors and exceptions are handled appropriately |
| Security | No input validation gaps; no secrets committed to code |
| Performance | No obvious inefficiencies (e.g., unnecessary rebuilds, O(n^2) loops on large lists) |
| SOLID principles | Adherence assessed without forcing unnecessary boilerplate or over-abstraction |
| Flutter/Dart/<your-state-management-package> patterns | Match against the project's loaded guidelines and conventions |
| Documentation | Public APIs, complex logic, and new modules are documented |
| Test coverage | New or changed logic has sufficient tests (see Step 4) |
| Style | Code matches the project's style guide and linting rules |
| Existing code | If the new changes look fine, also review surrounding existing (unchanged) code for smells and suggest refactors where relevant |
For generated files (e.g., *.g.dart, *.freezed.dart): confirm they are up-to-date and not manually modified.
> Scope discipline: Your job is not to comment on every change — it's to find errors and concrete improvement areas and comment on those. Don't manufacture comments where the code is fine.
*(Note: The following is just an example using Bloc/Cubit; apply similar principles to Riverpod, Provider, or your chosen state management package.)*
// BAD — rebuilds entire tree on every state change
BlocBuilder<MyCubit, MyState>(
builder: (context, state) => EntireScreen(state: state),
);
// GOOD — scope rebuilds to the widget that actually changes
BlocSelector<MyCubit, MyState, String>(
selector: (state) => state.title,
builder: (context, title) => Text(title),
);
Key usage on dynamically generated widgets.dispose() is called for controllers, streams, and animation controllers.const constructors are used where possible.For each file, check for common code smells. Use refactoring.guru/refactoring/smells for definitions and suggested refactorings.
| Category | Smells |
|---|---|
| Bloaters | Long Method, Large Class, Primitive Obsession, Long Parameter List, Data Clumps |
| Object-Orientation Abusers | Alternative Classes with Different Interfaces, Refused Bequest, Temporary Field, Switch Statements |
| Change Preventers | Divergent Change, Parallel Inheritance Hierarchies, Shotgun Surgery |
| Dispensables | Comments (redundant), Duplicate Code, Data Class, Dead Code, Lazy Class, Speculative Generality |
| Couplers | Feature Envy, Inappropriate Intimacy, Incomplete Library Class, Message Chains, Middle Man |
Verify test coverage explicitly — this is easy to skip and easy to fake, so be deliberate:
Checkpoint: If CI is red or tests are missing for new logic, flag as a blocking issue.
After the per-file pass, decide the outcome:
suggestion, minor, or major.By default, provide the review as a chat response — a structured response covering each file:
suggestion / minor / major) and a concrete fix suggestion.Approved, Approved with suggestions, or Changes requested.> Posting comments online (opt-in only). After presenting the chat review, ask the user whether they'd prefer you to also post these comments online on the PR/MR — so the team can see them, review them, and reply. Only post online if the user explicitly says yes. Never post to the platform on your own initiative.
>
> When the user does opt in, post issues as inline comments anchored to the right file and line (use proper position fields), with the conclusion/key-concerns as a top-level review comment and an approval when warranted. This requires a review-bot access token for the platform (GitHub/GitLab); if one isn't configured, let the user know and ask them to set it up before posting.
>
> Token safety. The token is a secret. You may check whether it exists and report its length to confirm it's configured, but never read, echo, log, print, or otherwise reveal the token value — not in chat, not in a file, not in a commit. Pass it to curl only by referencing the env var (e.g. $GITLAB_TOKEN), never by inlining the literal value, and avoid curl -v/--verbose (it prints the auth header). This is enforced by a PreToolUse hook (scripts/protect-token.sh) that blocks any Bash command which would expose the value. See the "Handling the token safely" section in each reference file for the safe existence/length check.
>
> The hook fires in both the Claude Code CLI and the Agent SDK. (SDK apps that set settingSources/setting_sources explicitly must include "project" for skill hooks to load; it's included by default.)
>
> For platform-specific API details, curl formats, and approval steps, follow:
> - GitLab → references/gitlab-posting.md (uses the GITLAB_TOKEN env var)
> - GitHub → references/github-posting.md (uses the GITHUB_TOKEN env var)
Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation
Use when completing tasks, implementing major features, or before merging to verify work meets requirements
Execute git commit with conventional commit message analysis, intelligent staging, and message generation. Use when user asks to commit changes, create a git commit, or mentions "/commit". Supports: (1) Auto-detecting type and scope from changes, (2) Generating conventional commit messages from diff, (3) Interactive commit with optional type/scope/description overrides, (4) Intelligent file staging for logical grouping
Comprehensive GitHub code review with AI-powered swarm coordination
Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.
Use this skill to review code. It supports both local changes (staged or working tree) and remote Pull Requests (by ID or URL). It focuses on correctness, maintainability, and adherence to project standards.
Refactor bloated AGENTS.md, CLAUDE.md, or similar agent instruction files to follow progressive disclosure principles. Splits monolithic files into organized, linked documentation.
Create high-quality git commits: review/stage intended changes, split into logical commits, and write clear commit messages (including Conventional Commits). Use when the user asks to commit, craft a commit message, stage changes, or split work into multiple commits.
Take evanca/code-review from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.