Code Quality Review
StudentWeis/ropy
Review a code change, diff, pull request, module, or test suite for code quality, comment and documentation quality, and test quality.
Review or improve code — one skill, four modes: bug/security review (default), performance, clean-code audit, slop cleanup.
Install Code Review
$ npx skills add luongnv89/skills --skill code-review -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install luongnv89/skills code-review --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/luongnv89/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/code-review .claude/skills/code-review && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "code-review" agent skill from https://github.com/luongnv89/skills/tree/main/skills/code-review into .claude/skills/code-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "code-review", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/luongnv89/skills/tree/main/skills/code-reviewType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add luongnv89/skills --skill code-review -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install luongnv89/skills code-review --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/luongnv89/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/code-review .agents/skills/code-review && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "code-review" agent skill from https://github.com/luongnv89/skills/tree/main/skills/code-review into .agents/skills/code-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "code-review", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add luongnv89/skills --skill code-review -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install luongnv89/skills code-review --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/luongnv89/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/code-review .cursor/skills/code-review && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "code-review" agent skill from https://github.com/luongnv89/skills/tree/main/skills/code-review into .cursor/skills/code-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "code-review", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/luongnv89/skills.git --path skills/code-review--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add luongnv89/skills --skill code-review -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install luongnv89/skills code-review --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/luongnv89/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/code-review .gemini/skills/code-review && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "code-review" agent skill from https://github.com/luongnv89/skills/tree/main/skills/code-review into .gemini/skills/code-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "code-review", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install luongnv89/skills code-reviewInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add luongnv89/skills --skill code-review -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/luongnv89/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/code-review .github/skills/code-review && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "code-review" agent skill from https://github.com/luongnv89/skills/tree/main/skills/code-review into .github/skills/code-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "code-review", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add luongnv89/skills --skill code-review -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install luongnv89/skills code-review --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/luongnv89/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/code-review .opencode/skills/code-review && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "code-review" agent skill from https://github.com/luongnv89/skills/tree/main/skills/code-review into .opencode/skills/code-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "code-review", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
code-review- GitHub stars
- 131
- Token cost
- ~2.4k tokens
- SKILL.md length
- 1,130 words
- Files
- 24 (incl. references)
- Skills in repo
- 37
- Repo updated
- First seen
- Licence
- MIT
At a glance
Review or improve code — one skill, four modes: bug/security review (default), performance, clean-code audit, slop cleanup.
- Works in 3 steps: Explicit wins. If the request carries… → Otherwise infer from the request. When… → No match, or phrases from more than one…
- Writing features
- SKILL.md covers Modes, Selecting the mode, Safety: cleanup writes code —… and Repo Sync Before Edits…, plus 8 more sections
- Calls git
What it does
Code Review is an agent skill from luongnv89/skills. 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).
Its SKILL.md is about 2.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 26 other files, including reference files (for example `agents/circular-dep-untangler.md`, `agents/deduplicator.md` and `agents/defensive-programming-remover.md`).
It sits in Development, covering Code quality, Code review and Test generation. The repository describes itself as: Supercharge your AI agents/bots with reusable skills. The licence is MIT.
When your agent uses it
- Writing features
- Generating tests (use test-coverage)
Example prompts
- “/code-review”
Workflow steps
3 steps, taken from the first numbered list in SKILL.md.
- Explicit wins. If the request carries mode:review|perf|clean|cleanup (or --mode ), use it.
- Otherwise infer from the request. When one matched phrase sits inside a longer matched
- No match, or phrases from more than one mode? Ask which mode, naming the four options. For
What it can do on your machine
Read from SKILL.md and the folder at commit 8f80262. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
git
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Code Review loads about 2.4k tokens when it runs, and up to ~31k if it reads all its reference files. Until then it costs about 63 tokens; SKILL.md has 1,130 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from luongnv89/skills at commit 8f80262, republished under its MIT licence (© luongnv89). 1,130 words, ~2,398 tokens.
Download SKILL.mdSave it as
.claude/skills/code-review/SKILL.md (or your agent's skills folder). This skill also uses 23 other files; get the full folder from GitHub.- name
- code-review
- description
- 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).
- license
- MIT
- effort
- high
- metadata.version
- 2.2.1
- metadata.author
- Luong NGUYEN <luongnv89@gmail.com>
- metadata.architecture
- router (4 modes, each a self-contained workflow in references/)
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
| Mode | Use when the user wants to... | Reads / writes | Output | Workflow |
|---|---|---|---|---|
| review (default) | find bugs, security holes, quality issues in a diff/PR | read-only | prioritized findings report | references/review-mode.md |
| perf | make code faster — bottlenecks, leaks, algorithmic waste | read-only | performance findings report | references/perf-mode.md |
| clean | audit readability/standards vs the bbv Clean Code cheat sheet | read-only | CLEAN_CODE_AUDIT.md | references/clean-mode.md |
| cleanup | actually refactor out AI slop, dead code, duplication, cruft | WRITES CODE | modified source files | references/cleanup-mode.md |
Selecting the mode
- Explicit wins. If the request carries
mode:review|perf|clean|cleanup(or--mode <name>), use it. - Otherwise infer from the request. When one matched phrase sits inside a longer matched
phrase, only the longer one counts, so "clean code review" is a clean phrase only, not also
a review phrase. Phrases that do not overlap all count, whatever their length (step 3).
- "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
- No match, or phrases from more than one mode? Ask which mode, naming the four options. For example, "review and optimize" matches review and perf, so ask. Use review without asking only when the request contains a review phrase and no other mode's phrase.
Safety: cleanup writes code — the other three do not
review, perf, and clean are source-read-only: they analyze and report without touching
source files. Review and perf may write only the named report artifact their mode specifies
(CODE_REVIEW.md for review; perf returns its report in the response). During review/perf analysis,
they must not otherwise mutate the index, refs, stash, branch, worktree, or remote state.
clean retains its own report-writing and sync contract. cleanup modifies files. Therefore:
- Never enter
cleanupby weak inference. Run it only when the user explicitly asks to refactor / clean up the codebase (or passesmode:cleanup). A plain "review my code" must never rewrite files — stay in a read-only mode. - Review and perf analysis record
git rev-parse HEAD,git status, and local tracking observations without claiming remote freshness. They do not fetch, stash, pull, rebase, checkout/switch, create or delete branches/worktrees, or apply source fixes. A separately approved mutation workflow owns its own freshness and stash-first sync contract. - Confirm before the first write in
cleanup, and follow that mode's own gating.
Repo Sync Before Edits (mandatory)
Applies to clean (writes CLEAN_CODE_AUDIT.md) and cleanup (writes source) only. review and
perf never sync (see the Safety section). Before the first write in either mode:
branch="$(git rev-parse --abbrev-ref HEAD)"
git fetch origin && git pull --rebase origin "$branch"- If the working tree is dirty in
clean, stash first, sync, then pop the stash. - If the working tree is dirty in
cleanup, stop and ask the user to commit or stash first. - If
originis missing, or the pull or stash pop conflicts, stop and ask the user. Do not write any file. - If the target is not a git repo,
cleanskips the sync and notes that in its report.
The full step, with recovery commands, is in references/clean-mode.md and references/cleanup-mode.md.
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):
- review →
references/review-mode.md— agentsagents/reviewer.md,agents/file-reviewer.md,agents/report-assembler.md; refsreferences/subagent-architecture.md,references/code-smells.md - perf →
references/perf-mode.md— refreferences/language-checks.md - clean →
references/clean-mode.md— refsreferences/clean-code-checklist.md,references/tdd-checklist.md,references/html-report-guide.md,references/report-template.html - cleanup →
references/cleanup-mode.md— the 8 cleaner agents inagents/(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).
Show full SKILL.md (462 more words)Show less
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
- If no target diff, PR, file set, or repository is named, ask for the scope before starting.
- If a reference or agent file listed for the selected mode is missing, stop and name the missing path.
- For
cleanorcleanup, follow that mode's sync, backup, dry-run, confirmation, and rollback steps in order. If a sync or safety check fails, stop before the first write.
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 diffwhen 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.
Also check that a reader can use the final response:
- Result is findable: the first line after
Mode:states the result and PASS, PARTIAL, or FAIL. - Facts and assumptions are separate: verified claims name the check that was run; inferences,
skipped scope, and untested behavior are labeled under
Uncertainty. - Claims are traceable: each finding points to a
file:line, a command output, or a report section. An intermediate step passing does not count as the whole run passing. - Next decision is clear:
Decisionnames the approval needed (for example, startingcleanup), or says "No approval needed", and lists any remaining user action.
Agent inspection cannot confirm that a human understood the output. If no human feedback was given, report human understanding as unconfirmed; do not count it as a failure or a pass.
Expected Output
Every mode's final response carries these five items, in this order. Keep each item to one or two lines; the mode's report artifact holds the detail.
Mode: review
Result: PARTIAL — 1 critical, 2 major, 0 minor findings; reviewer pass incomplete for 3 files
Evidence: CODE_REVIEW.md written; reviewer agent validated 41/44 files; `git diff --stat -- src/` empty
Uncertainty: 3 generated files skipped (listed in CODE_REVIEW.md); no tests were run
Decision: No approval needed. To apply fixes, ask for a separate `cleanup` run.Step Completion Reports
After routing and after the selected workflow, emit a compact report:
◆ Code Review ([mode])
Mode selection: √ pass
Workflow criteria: √ pass
Output verified: √ pass
Safety boundary: √ pass
Result: PASS | FAIL | PARTIALUse × 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
cleanuprun.
© luongnv89, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 23 other files (references) in skills/code-review of luongnv89/skills.
- SKILL.md
- agents/circular-dep-untangler.md
- agents/deduplicator.md
- agents/defensive-programming-remover.md
- agents/file-reviewer.md
- agents/legacy-code-remover.md
- agents/report-assembler.md
- agents/reviewer.md
- agents/slop-comment-cleaner.md
- agents/type-consolidator.md
- agents/unused-code-killer.md
- agents/weak-type-strengthener.md
- docs/README.md
- references/clean-code-checklist.md
- references/clean-mode.md
- references/cleanup-mode.md
- references/code-smells.md
- references/html-report-guide.md
- … and 6 more
Open the folder on GitHubat commit 8f80262
Compare with similar skills
Code Review next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Code Review this skillluongnv89/skills | 131 | — | ~2.4k | Automated safety check: Pass | MIT | |
| Code Quality ReviewStudentWeis/ropy | 193 | — | ~2.2k | Automated safety check: Pass | MIT | |
| Code Review Skillawesome-skills/code-review-skill | 2.1k | — | ~2.8k | Automated safety check: Notes | MIT | |
| Code Review Specialistluongnv89/claude-howto | 42k | — | ~764 | Automated safety check: Pass | MIT | |
| Code Review SkillRain-kl/OpenFlare | 288 | — | ~2.3k | Automated safety check: Notes | MIT | |
| Code ReviewerYikai-Liao/symusic | 189 | 1 repos | ~1.3k | Automated safety check: Pass | MIT |
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Questions about Code Review
What does Code Review do?
Review or improve code — one skill, four modes: bug/security review (default), performance, clean-code audit, slop cleanup. Code Review is an agent skill from luongnv89/skills. Review or improve code — one skill, four modes: bug/security review (default), performance, clean-code audit, slop cleanup.
When should I use Code Review?
Code Review fits situations like: writing features; generating tests (use test-coverage).
How do I install Code Review in Claude Code?
Run `npx skills add luongnv89/skills --skill code-review -a claude-code`. Or copy the skill folder (skills/code-review in luongnv89/skills) into .claude/skills/code-review in your project. Claude Code loads it when a task matches its description.
How do I install Code Review in Codex?
Run `npx skills add luongnv89/skills --skill code-review -a codex`. Or copy the skill folder (skills/code-review in luongnv89/skills) into .agents/skills/code-review in your project. Codex loads it when a task matches its description.
Can I use Code Review in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add luongnv89/skills --skill code-review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/code-review, .gemini/skills/code-review, .github/skills/code-review and .opencode/skills/code-review in your project.
What does Code Review need to run?
Going by SKILL.md and its folder, Code Review needs the command-line tools its instructions call (git).
Does Code Review access the network?
SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Code Review safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Code Review use?
Code Review is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Code Review use?
About 2.4k tokens (SKILL.md is roughly 9.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 29k tokens, read only when the agent opens those files.
What are the alternatives to Code Review?
Skills that share tags, products or a category with Code Review: Code Quality Review (StudentWeis/ropy, 193 stars), Code Review Skill (awesome-skills/code-review-skill, 2.1k stars), Code Review Specialist (luongnv89/claude-howto, 42k stars) and Code Review Skill (Rain-kl/OpenFlare, 288 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Code Review?
luongnv89 (a GitHub user) maintains it in luongnv89/skills, which has 131 GitHub stars. The repository holds 37 skills in this directory. The repository was last updated on October 7, 2026.
Source: luongnv89/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.