Code Review logo

Code Review

Community
evanca
code-review

Use when asked to review a PR, MR, branch, or diff, audit changed files, or check code quality.

Overview

Publisherevanca
Repositoryflutter-ai-rules
Skill namecode-review
Stars
651
Forks
67
Bundled files
3
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by evanca on GitHub. Read the source before you install it.

Installation

Install the Code Review AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/evanca/flutter-ai-rules/tree/main/skills/code-review
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/evanca/flutter-ai-rules.git /tmp/flutter-ai-rules
mkdir -p .claude/skills
cp -r /tmp/flutter-ai-rules/skills/code-review .claude/skills/code-review
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Code Review in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Code Review on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Code Review is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Code Review Skill

Perform structured, objective code reviews for Flutter/Dart projects following a repeatable checklist.

When to Use

Use this skill when:

  • Asked to review a pull request, merge request, or branch.
  • Evaluating changed, added, or deleted files for correctness and quality.
  • Auditing a diff before merging.
  • Checking whether new code meets project standards.

Review Workflow

Step 1 — Validate branch and merge target

  1. Confirm the current branch is a feature, bugfix, or PR/MR branch — not the project's primary branch (e.g. main, master, develop).
  2. Verify the branch is up-to-date with the target branch (no unresolved conflicts).
  3. Identify the target branch for the merge.

Checkpoint: If the branch is behind the target, flag it before proceeding.

Step 2 — Discover changes

  1. List all changed, added, and deleted files.
  2. For each change, look up the commit title and review how connected components are implemented.
  3. Analyze the change: is it clear why the change was made? If not, dig into the connected methods and files until it is. When you report, name which connected files/methods you analyzed and why — this shows the change was understood, not assumed.
  4. Never assume a change is correct without investigating the implementation.
  5. If a change remains unclear after investigation, note this explicitly in the report.

Step 3 — Review each file

Iterate through each changed file. For every file, verify the following:

AreaWhat to verify
Understand the changeWhy was it made? Review connected methods/files; note which ones you analyzed and why
LocationFile is in the correct directory
NamingFile name follows project naming conventions
ResponsibilityThe file's responsibility is clear; reason for change is understandable
ReadabilityVariable, function, and class names are descriptive and consistent
Logic & correctnessNo logic errors or missing edge cases
Code smellsScan for the smells in Code Smells Reference below
MaintainabilityCode is modular; no unnecessary duplication
Error handlingErrors and exceptions are handled appropriately
SecurityNo input validation gaps; no secrets committed to code
PerformanceNo obvious inefficiencies (e.g., unnecessary rebuilds, O(n^2) loops on large lists)
SOLID principlesAdherence assessed without forcing unnecessary boilerplate or over-abstraction
Flutter/Dart/ patternsMatch against the project's loaded guidelines and conventions
DocumentationPublic APIs, complex logic, and new modules are documented
Test coverageNew or changed logic has sufficient tests (see Step 4)
StyleCode matches the project's style guide and linting rules
Existing codeIf 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.

Flutter-specific checks

(Note: The following is just an example using Bloc/Cubit; apply similar principles to Riverpod, Provider, or your chosen state management package.)

dart
// 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),
);
  • Verify Key usage on dynamically generated widgets.
  • Check that dispose() is called for controllers, streams, and animation controllers.
  • Confirm const constructors are used where possible.
Code Smells Reference

For each file, check for common code smells. Use refactoring.guru/refactoring/smells for definitions and suggested refactorings.

CategorySmells
BloatersLong Method, Large Class, Primitive Obsession, Long Parameter List, Data Clumps
Object-Orientation AbusersAlternative Classes with Different Interfaces, Refused Bequest, Temporary Field, Switch Statements
Change PreventersDivergent Change, Parallel Inheritance Hierarchies, Shotgun Surgery
DispensablesComments (redundant), Duplicate Code, Data Class, Dead Code, Lazy Class, Speculative Generality
CouplersFeature Envy, Inappropriate Intimacy, Incomplete Library Class, Message Chains, Middle Man

Step 4 — Evaluate the overall change set

  1. Verify the change set is focused and scoped to its stated purpose — no unrelated changes.
  2. Check that the PR/MR description accurately reflects the changes.
Test coverage

Verify test coverage explicitly — this is easy to skip and easy to fake, so be deliberate:

  • For any new logic or significant change, search for the corresponding test file(s) and confirm tests actually exist.
  • Check that tests cover the changed functionality including edge cases, not just the happy path.
  • Evaluate whether tests could actually fail against real code, or only verify mocked behavior (a test that asserts a mock returns what the mock was told to return proves nothing).
  • If tests are missing or insufficient, comment on the lack of coverage — don't let it pass silently.

Step 5 — Verify CI and tests

  1. Ensure all tests pass in CI.
  2. Check for new analyzer warnings or lint violations.
  3. Fetch official documentation when unsure about best practices for a package.

Checkpoint: If CI is red or tests are missing for new logic, flag as a blocking issue.


Wrap-Up

After the per-file pass, decide the outcome:

  • If everything looks good and no changes are needed: post an overall conclusion comment summarizing what the MR is about (what was done) plus any observations, and approve the MR.
  • If the new changes are clean but you spotted smells in existing code: include those as optional refactor suggestions rather than blockers.
  • If issues were found: summarize the key concerns clearly so the author knows what to address first.

Feedback Standards

  • Be objective and reasonable — avoid automatic praise or flattery.
  • Take a devil's advocate approach: give honest, thoughtful feedback.
  • Provide clear, constructive suggestions for every issue found.
  • Include requests for clarification for anything unclear.
  • Classify each finding by severity: suggestion, minor, or major.

Output Format

By default, provide the review as a chat response — a structured response covering each file:

  1. Summary — what changed and why.
  2. Issues — each with severity (suggestion / minor / major) and a concrete fix suggestion.
  3. Questions — specific clarification requests per file.
  4. Verdict — one of: 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:

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Code Review AI skill do?

Use when asked to review a PR, MR, branch, or diff, audit changed files, or check code quality.

Why use Code Review on TypingMind?

Because you install it once and use it with any model. Code Review is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Code Review in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/evanca/flutter-ai-rules/tree/main/skills/code-review. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Code Review?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Code Review?

As many as you like. As long as a model supports skills, you can use Code Review with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Code Review AI skill free?

Yes. It is published on GitHub by evanca under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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