Code Review logo

Code Review

Community
luongnv89
code-review

Review or improve code — one skill, four modes: bug/security review (default), performance, clean-code audit, slop cleanup. Pass mode:review|perf|clean|cleanup or infer. Don't use for writing features or generating tests (use test-coverage).

Overview

Publisherluongnv89
Repositoryskills
Skill namecode-review
Stars
124
Forks
18
Bundled files
22
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.

  • 22 bundled files

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

  • Open source

    Published by luongnv89 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.
  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/luongnv89/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/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

One skill for reviewing and improving code quality. Pick a mode by intent (or pass an explicit mode: parameter); each mode is a full, self-contained workflow in references/. Load only the mode you need — this protects the agent's context budget.

Modes

ModeUse when the user wants to...Reads / writesOutputWorkflow
review (default)find bugs, security holes, quality issues in a diff/PRread-onlyprioritized findings reportreferences/review-mode.md
perfmake code faster — bottlenecks, leaks, algorithmic wasteread-onlyperformance findings reportreferences/perf-mode.md
cleanaudit readability/standards vs the bbv Clean Code cheat sheetread-onlyCLEAN_CODE_AUDIT.mdreferences/clean-mode.md
cleanupactually refactor out AI slop, dead code, duplication, cruftWRITES CODEmodified source filesreferences/cleanup-mode.md

Selecting the mode

  1. Explicit wins. If the request carries mode:review|perf|clean|cleanup (or --mode <name>), use it.
  2. Otherwise infer from the request:
    • "review", "find bugs", "security", "is this correct", "look for vulnerabilities" → review
    • "slow", "faster", "optimize", "bottleneck", "memory leak", "performance" → perf
    • "clean code audit" (or "clean-code audit"), "clean code review", "check this against clean code" → clean (user-invoked only — a bare "readability" or "audit against standards" ask is ambiguous: use step 3)
    • "remove slop", "clean up the codebase", "refactor out cruft / dead code / duplication" → cleanup
  3. Ambiguous? Ask which mode, naming the options. Fall back to review only when the intent is clearly "review this" with no other signal.

Safety: cleanup writes code — the other three do not

review, perf, and clean are strictly read-only: they analyze and report, never touching source. cleanup modifies files. Therefore:

  • Never enter cleanup by weak inference. Run it only when the user explicitly asks to refactor / clean up the codebase (or passes mode:cleanup). A plain "review my code" must never rewrite files — stay in a read-only mode.
  • Confirm before the first write in cleanup, and follow that mode's own gating.

Repo Sync Before Edits

The router itself is read-only. The two modes that touch a git repo carry the mandatory sync-before-edits step in their own workflow: cleanup (writes source) in references/cleanup-mode.md and clean (writes CLEAN_CODE_AUDIT.md) in references/clean-mode.md. Before either mode edits, follow that reference's Repo Sync step — sync with remote (stash-first if the tree is dirty) so writes land on top of the latest base.

Run the mode's workflow

Read the selected mode's reference file and execute its steps exactly. Supporting files each mode uses (already colocated under this skill):

  • reviewreferences/review-mode.md — agents agents/reviewer.md, agents/file-reviewer.md, agents/report-assembler.md; refs references/subagent-architecture.md, references/code-smells.md
  • perfreferences/perf-mode.md — ref references/language-checks.md
  • cleanreferences/clean-mode.md — refs references/clean-code-checklist.md, references/tdd-checklist.md, references/html-report-guide.md, references/report-template.html
  • cleanupreferences/cleanup-mode.md — the 8 cleaner agents in agents/ (deduplicator.md, type-consolidator.md, unused-code-killer.md, circular-dep-untangler.md, weak-type-strengthener.md, defensive-programming-remover.md, legacy-code-remover.md, slop-comment-cleaner.md)

Environment Check

If the Agent tool is available, modes that use subagents (review, cleanup) spawn them per their workflow — fresh-context validation and parallel work. If it is unavailable (e.g., Claude.ai), execute each mode's phases inline (less rigorous, but functional).

Chaining modes

Modes compose: a common flow is clean (audit → CLEAN_CODE_AUDIT.md) then cleanup (apply the refactors), or review/perf to find issues before fixing. Run one mode at a time; confirm with the user before switching into the code-writing cleanup mode.

Prerequisites

  • Require a readable target diff, PR, file set, or repository; ask for scope when none is provided.
  • Check that every reference and agent required by the selected mode is available before starting.
  • For clean or cleanup, validate repository state and follow that mode's sync, backup, dry-run, confirmation, and rollback instructions. Stop on sync errors or failed safety checks.

Acceptance Criteria

Verify every run against the selected mode's own acceptance criteria, then assert all of these router criteria:

  • Exactly one mode was selected and its reference workflow was followed end to end.
  • Read-only modes changed no source files; verify with a path-scoped git diff when applicable.
  • Every finding cites concrete evidence and the expected output artifact or report was produced.
  • Tests or validation commands required by the selected mode completed with their expected result.
  • Edge cases, limitations, skipped files, and degraded subagent coverage are disclosed.

Expected Output

Example response after a read-only review:

text
Mode: review
Result: PASS
Findings: 1 critical, 2 major, 0 minor
Output: CODE_REVIEW.md
Validation: reviewer pass complete; no source files changed

Step Completion Reports

After routing and after the selected workflow, emit a compact report:

text
◆ Code Review ([mode])
  Mode selection:      √ pass
  Workflow criteria:   √ pass
  Output verified:     √ pass
  Safety boundary:     √ pass
  Result:              PASS | FAIL | PARTIAL

Use × fail — reason for any unmet check. Never report PASS while a selected-mode acceptance criterion, expected output, required test, or safety guardrail is unresolved.

Edge Cases

  • Unknown mode: value → reject it and list the four valid modes.
  • Mixed intents across modes → ask which mode to run first; never merge workflows implicitly.
  • Missing target or inaccessible files → stop and request a concrete scope instead of guessing.
  • Agent tool unavailable → use the selected reference's inline fallback and disclose reduced coverage.
  • A read-only mode requests edits mid-run → finish the report, then require explicit approval before starting a separate cleanup run.

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?

Review or improve code — one skill, four modes: bug/security review (default), performance, clean-code audit, slop cleanup. Pass mode:review|perf|clean|cleanup or infer. Don't use for writing features or generating tests (use test-coverage).

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/luongnv89/skills/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 luongnv89 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇