Agent skill

Codex Code Reviewer

by VCnoC in VCnoC/Claude-Code-Zen-mcp-Skill-Work

Systematic code review workflow using zen mcp's codex tool. An agent skill from VCnoC/Claude-Code-Zen-mcp-Skill-Work.

Apache-2.0Auto-check passedDevelopment

Install Codex Code Reviewer

skills CLI
$ npx skills add VCnoC/Claude-Code-Zen-mcp-Skill-Work --skill codex-code-reviewer -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install VCnoC/Claude-Code-Zen-mcp-Skill-Work codex-code-reviewer --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/VCnoC/Claude-Code-Zen-mcp-Skill-Work.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/codex-code-reviewer .claude/skills/codex-code-reviewer && rm -rf skills-src

Use ~/.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/

Facts

Skill name
codex-code-reviewer
GitHub stars
116
Token cost
~3.5k tokens
SKILL.md length
1,171 words
Files
8 (incl. references)
Skills in repo
5
Repo updated
First seen
Licence
Apache-2.0

At a glance

Systematic code review workflow using zen mcp's codex tool. An agent skill from VCnoC/Claude-Code-Zen-mcp-Skill-Work.

  • Works in 4 steps: Select and Invoke Appropriate Review Tool → Present Findings and Decision Making → Apply Fixes → …
  • The user explicitly requests use codex to check the code
  • SKILL.md covers Overview, When to Use This Skill, Workflow: Iterative Code… and Code Quality Standards, plus 4 more sections
  • Calls git

What it does

Codex Code Reviewer is an agent skill from VCnoC/Claude-Code-Zen-mcp-Skill-Work. Systematic code review workflow using zen mcp's codex tool. Use this skill when the user explicitly requests "use codex to check the code", "check if the recently generated code has any issues", or "check the code after each generation". The skill performs iterative review cycles - checking code quality, presenting issues to the user for approval, applying fixes, and re-checking until no issues remain or maximum iterations (5) are reached.

Its SKILL.md is about 3.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including reference files (for example `references/code_quality_standards.md`, `references/quality_standards/README.md` and `references/quality_standards/commit_and_quality_gates.md`).

It sits in Development, covering Code review and Code quality. It works with Model Context Protocol. The repository describes itself as: 关于这个事,我简单说两句,你明白就行,总而言之,这个事呢,现在就是这个情况,具体的呢,大家也都看得到,也得出来说那么几句,可能,你听的不是很明白,但是意思就是那么个意思,不知道的你也不用去猜,这种事情见得多了,我只想说懂得都懂,不懂的我也不多解释,毕竟自己知道就好,细细品吧。 The licence is Apache-2.0.

When your agent uses it

  • The user explicitly requests use codex to check the code
  • Check if the recently generated code has any issues
  • Check the code after each generation

Example prompts

  • “s codex tool. Use this skill when the user explicitly requests”
  • “check if the recently generated code has any issues”
  • “check the code after each generation”
  • “/codex-code-reviewer”

Requirements

  • Python 3

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Select and Invoke Appropriate Review Tool
  2. Present Findings and Decision Making
  3. Apply Fixes
  4. Increment and Validate

What it can do on your machine

Read from SKILL.md and the folder at commit a89bae4. 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

Codex Code Reviewer loads about 3.5k tokens when it runs, and up to ~6.2k if it reads all its reference files. Until then it costs about 116 tokens; SKILL.md has 1,171 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~116
When it runs · the whole SKILL.md, loaded when a task matches
~3.5k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~6.2k

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 VCnoC/Claude-Code-Zen-mcp-Skill-Work at commit a89bae4, republished under its Apache-2.0 licence (© VCnoC). 1,171 words, ~3,527 tokens.

Download SKILL.mdSave it as .claude/skills/codex-code-reviewer/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
codex-code-reviewer
description
Systematic code review workflow using zen mcp's codex tool. Use this skill when the user explicitly requests "use codex to check the code", "check if the recently generated code has any issues", or "check the code after each generation". The skill performs iterative review cycles - checking code quality, presenting issues to the user for approval, applying fixes, and re-checking until no issues remain or maximum iterations (5) are reached.

Codex Code Reviewer

Overview

This skill provides a systematic, iterative code review workflow powered by zen mcp's codex tool. It automatically checks recently modified code files against project standards (CLAUDE.md requirements), presents identified issues to users for approval, applies fixes, and re-validates until code quality standards are met or the maximum iteration limit is reached.

Operation Modes:

  • Interactive Mode (Default): Present issues to user, wait for approval before applying fixes
  • Full Automation Mode: Automatically select and apply all suggested fixes without user approval (activated when user initially requests "full automation" or "complete automation")

When to Use This Skill

Trigger this skill when the user says:

  • "Use codex to check the code"
  • "Please help me check if the recently generated code has any issues"
  • "Check the code after each generation"
  • Similar requests for code quality validation using codex

Workflow: Iterative Code Review Cycle

Prerequisites

Before starting the review cycle:

  1. ** Read Operation Mode from Context (automation_mode - READ FROM SSOT):**
    • automation_mode definition and constraints: See CLAUDE.md「📚 共享概念速查」
    • This skill's role: Skill Layer (read-only), read from context [AUTOMATION_MODE: true/false], true → auto-fix / false → ask user

1a. Read Coverage Target from Context (coverage_target - READ FROM SSOT):

  • coverage_target definition and constraints: See CLAUDE.md「📚 共享概念速查」
  • This skill's role: Skill Layer (read-only), read from context [COVERAGE_TARGET: X%], validate coverage (≥ target pass, < 70% reject)
  1. Identify Files to Review:

    • Use git status or similar to identify recently modified files
    • Interactive Mode (automation_mode = false): Confirm with user which files should be reviewed
    • Automated Mode (automation_mode = true): Auto-select all recently modified files, log decision to auto_log.md
  2. Initialize iteration counter: current_iteration = 1

  3. Set maximum iterations: max_iterations = 5

  4. Initialize review tool tracker: first_review_done = false

  5. Detect Review Context:

    • Check if this is final quality validation (project completion/final verification)
    • If YES: Enable Final Validation Mode (requires minimum 2 passes: codereview + clink)
    • If NO: Use Standard Review Mode
Review Cycle Loop

Execute the following loop until termination conditions are met:

Step 1: Select and Invoke Appropriate Review Tool

Tool Selection Logic:

python
if current_iteration == 1 and not first_review_done:
    # First review: Use mcp__zen__codereview
    review_tool = "mcp__zen__codereview"
    first_review_done = True
else:
    # Second and subsequent reviews: Use mcp__zen__clink with codex CLI
    review_tool = "mcp__zen__clink"

A) First Review: Call mcp__zen__codereview

Tool: mcp__zen__codereview
Parameters:
- step: Detailed review request (e.g., "Review the following files for code quality, security, performance, and adherence to project standards...")
- step_number: current_iteration
- total_steps: Estimate based on findings (start with 2-3)
- next_step_required: true (initially)
- findings: Document all discovered issues
- relevant_files: [list of recently modified file paths - MUST be absolute full paths]
- review_type: "full" (covers quality, security, performance, architecture)
- model: "codex" (or user-specified model)
- review_validation_type: "external" (for expert validation)
- confidence: Start with "exploring", increase as understanding grows

Important: Use absolute full paths; follow zen mcp's codereview workflow (2-3 steps); reference references/quality_standards/README.md (on-demand loading)

B) Second and Subsequent Reviews: Call mcp__zen__clink with codex CLI

Tool: mcp__zen__clink
Parameters:
- prompt: "Review files for: 1) Code quality 2) Security 3) Performance 4) Architecture 5) Documentation. Categorize by severity (critical/high/medium/low), provide file:line locations and fix recommendations."
- cli_name: "codex"
- role: "code_reviewer"
- files: [absolute full paths]
- continuation_id: [optional, for context continuity]

Important: Use absolute full paths for files; use continuation_id for context continuity; supported params: prompt, cli_name, role, files, images, continuation_id

Step 2: Present Findings and Decision Making

After codex returns the review results:

  1. Summarize Issues Clearly:

    • Group by severity (critical/high/medium/low)
    • Provide specific file locations and line numbers
    • Explain the impact of each issue
  2. Decision Making Based on automation_mode (READ FROM CONTEXT):

    • automation_mode behavior and decision logic: See CLAUDE.md「📚 共享概念速查」and「G11 Automated Repair Skills」
    • [AUTOMATION_MODE: false] → Interactive: Ask user approval
    • [AUTOMATION_MODE: true] → Automated: Auto-fix Critical/High, conditional Medium, auto-fix Low style issues
    • Output [Automated Decision Record] fragments for auto_log.md (collected by router, generated by simple-gemini)
Step 3: Apply Fixes

Interactive Mode: If user approves Automation Mode: Proceed directly based on auto-decision logic

  1. Apply fixes to the identified issues
  2. Use appropriate tools (Edit, Write, etc.) to modify code
  3. Follow project coding standards from CLAUDE.md
  4. Document changes made

Automation Mode Transparency:

  • auto_log mechanism and format: See CLAUDE.md「📚 共享概念速查 → auto_log」and skills/shared/auto_log_template.md
  • Example output:
    [Automated Fix Record]
     Fixed: 3 critical, 2 medium, 1 low | Skipped: 1 medium (business logic)
     1. SQL injection (critical) → Fixed | 2. N+1 query (medium) → Fixed
     3. Variable naming (low) → Fixed | 4. Logic optimization (medium) → Skipped
Step 4: Increment and Validate
current_iteration = current_iteration + 1

Check termination conditions:

Standard Review Mode:

  • Success: Review tool reports no issues → Exit loop, report success
  • Max iterations reached: current_iteration > max_iterations → Exit loop, report remaining issues
  • User cancellation: User declined fixes → Exit loop
  • Continue: Issues remain and iterations < max_iterations → Go to Step 1

Final Validation Mode (Project Completion/Final Verification):

  • Minimum Pass Requirement: MUST complete at least 2 passes
    • Pass 1: mcp__zen__codereview (first_review_done = true)
    • Pass 2: mcp__zen__clink with codex CLI
  • Early Exit Prevention:
    • If current_iteration < 2 → MUST continue to Step 1 (even if no issues found)
    • If current_iteration >= 2 AND no issues found in both passes → Exit loop, report success
  • Max iterations reached: current_iteration > max_iterations → Exit loop, report remaining issues
  • User cancellation: User declined fixes → Exit loop
  • Continue: Issues remain OR minimum passes not met → Go to Step 1
Termination and Reporting

When the cycle terminates, provide a final report:

Code Review Completion Report:

Review rounds: X / 5
Reviewed files: [list files]

Tools used:
- Round 1: mcp__zen__codereview (codex workflow validation)
- Round 2: mcp__zen__clink (codex CLI direct analysis)
- Round 3+: mcp__zen__clink (continued)

Final status:
- All issues fixed / Max reviews reached / User cancelled
- [Final Validation Mode] Completed minimum 2 passes / Did not meet minimum 2 pass requirement

Fix summary:
- Fixed issues: X
- Remaining issues: Y (if any)

Recommendations: [next steps]
Show full SKILL.md (504 more words)Show less

Code Quality Standards

This skill enforces standards defined in:

  • CLAUDE.md: Global rules (G1-G11), phase-specific requirements (P1-P4), model development workflow
  • Project-specific: PROJECTWIKI.md architecture decisions and conventions

Key quality dimensions checked:

  1. Code Quality: Readability, maintainability, complexity
  2. Security: Vulnerabilities, sensitive data handling
  3. Performance: Efficiency, resource usage
  4. Architecture: Adherence to documented design decisions
  5. Documentation: Code comments, PROJECTWIKI.md alignment

Test Coverage Standards (G9 Compliance):

  • coverage_target usage and thresholds: See CLAUDE.md「📚 共享概念速查」

See references/quality_standards/README.md for on-demand quality standards (load specific files as needed).

Best Practices

For Effective Reviews
  1. Scope Control: Review recently modified files only (use git diff/status)
  2. Context Preservation: Maintain continuation_id across review cycles for context continuity
  3. Incremental Fixes: Address high-severity issues first, then iterate for lower-priority ones
  4. User Communication: Always explain WHY an issue matters and HOW the fix improves code
Error Handling
  • Tool Errors: If mcp__zen__codereview fails, report to user and offer manual review
  • Ambiguous Issues: When codex findings are unclear, seek user clarification before fixing
  • Conflicting Standards: If global and project-specific CLAUDE.md conflict, prioritize global CLAUDE.md

Resources

references/quality_standards/README.md

Quality standards index and on-demand loading guide. Load this reference when:

  • Need overview of available quality standards
  • Detailed quality criteria are needed

Then load specific standard files as needed:

  • global_rules.md - G1-G8 全局规则
  • core_principles.md - 核心开发原则
  • p3_constraints_and_quality.md - P3执行约束
  • commit_and_quality_gates.md - Conventional Commits规范
  • error_handling_and_usage.md - P4错误处理

Use grep patterns to search: G1|G2|core principles|ethics|reproducible

Example Usage

Example 1: Interactive Mode (Default)

User: "Use codex to check the code"

Workflow:

  1. Identify files: src/features.py, src/model_training.py
  2. Read context: [AUTOMATION_MODE: false] → Interactive mode
  3. Round 1 (mcp__zen__codereview): Found 3 issues (1 critical, 1 medium, 1 low)
  4. Ask user approval → User: "Yes"
  5. Apply fixes
  6. Round 2 (mcp__zen__clink): No new issues
  7. Result: All issues fixed in 2/5 rounds

Example 2: Full Automation Mode ⭐

User Initial Request: "Full automation, help me develop login functionality, automatically check quality after code completion"

Main Router: Detects "full automation" → Sets automation_mode = true

After code generation, Main Claude invokes codex-code-reviewer with automation_mode = true:

Assistant:

Alright, I will use codex to systematically review the just-generated code.

First, let me identify recently modified files...
[Running git status]

Found the following modified files:
- src/auth/login.py
- src/auth/session.py
- tests/test_login.py

Reading context: [AUTOMATION_MODE: true]
Mode: Full automation review (automatically select and apply fixes)

Starting round 1 review...
[Calling mcp__zen__codereview]

Review results:
Found 5 issues:
[Critical] src/auth/login.py:45 - SQL injection risk (critical)
[Critical] src/auth/session.py:23 - Plaintext password storage (critical)
[Medium] src/auth/login.py:78 - Missing exception handling (medium)
[Medium] src/auth/session.py:56 - Performance issue: N+1 query (medium)
[Low] tests/test_login.py:12 - Non-standard test naming (low)

[Full Automation Mode] Auto-decision + fixes applied:

[Automated Fix Record] Fixed: 2 critical, 2 medium, 1 low
1. SQL injection (critical) → Fixed with parameterized queries
2. Plaintext password (critical) → Fixed with bcrypt encryption
3. Exception handling (medium) → Fixed with try-except blocks
4. N+1 query (medium) → Fixed with select_related optimization
5. Test naming (low) → Fixed by renaming to standard convention

Fixes completed. Starting round 2 review...
[Calling mcp__zen__clink with codex CLI]

Review results: No new issues found

Code review complete!
Review rounds: 2 / 5
Tools used:
- Round 1: mcp__zen__codereview
- Round 2: mcp__zen__clink (codex CLI)
Full automation mode: Auto-fixed 5 issues, skipped 0 issues
All issues successfully fixed without user intervention.

Key Differences: No user approval, auto-decision by severity/safety, transparent logging with rationale, same quality standards


Example 3: Final Validation Mode (Project Completion/Final Quality Verification) ⭐⭐

User: "Project is complete, please perform final quality verification"

Workflow:

  1. Detect: Project completion/final verification → Enable Final Validation Mode (min 2 rounds)
  2. Identify files: 5 core files (src + tests)
  3. Round 1 (mcp__zen__codereview): Found 2 issues (1 medium, 1 low)
  4. Ask user approval → User: "Yes" → Apply fixes
  5. Round 2 (mcp__zen__clink with codex CLI): No new issues
  6. Result: All issues fixed, minimum 2-round requirement met, quality verification passed

Key Features: Mandatory 2+ passes (codereview + clink), early exit prevention, comprehensive validation before release


Notes

  • Dual-tool approach: Iteration 1 uses mcp__zen__codereview, iteration 2+ uses mcp__zen__clink with codex CLI
  • Max 5 iterations, CLAUDE.md workflow compatible (P3/P4), three modes: Interactive (default) / Full Automation / Final Validation (2+ passes)
  • automation_mode & auto_log (READ FROM SSOT):
    • Definitions and constraints: See CLAUDE.md「📚 共享概念速查」
    • This skill: Skill Layer (read-only), outputs [Automated Decision Record] fragments when automation_mode=true
  • Final validation mode activated when user mentions "project completion" / "final verification" / "final quality validation"

© VCnoC, Apache-2.0. 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 7 other files (references) in skills/codex-code-reviewer of VCnoC/Claude-Code-Zen-mcp-Skill-Work.

  • SKILL.md
  • references/code_quality_standards.md
  • references/quality_standards/README.md
  • references/quality_standards/commit_and_quality_gates.md
  • references/quality_standards/core_principles.md
  • references/quality_standards/error_handling_and_usage.md
  • references/quality_standards/global_rules.md
  • references/quality_standards/p3_constraints_and_quality.md

Open the folder on GitHubat commit a89bae4

Compare with similar skills

Codex Code Reviewer 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.

Codex Code Reviewer compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Codex Code Reviewer this skillVCnoC/Claude-Code-Zen-mcp-Skill-Work116—~3.5kAutomated safety check: PassApache-2.0
RAG Code Reviewlyonzin/knowledge-rag290—~1.8kAutomated safety check: PassMIT
WooCommerce Code Reviewwoocommerce/woocommerce11k3 repos~1.1kAutomated safety check: PassCustom licence
Skill Doli Code ReviewDolibarr/dolibarr7.7k1 repos~1.1kAutomated safety check: PassMIT
Dignified Python Standardsdocling-project/docling68k—~1.5kAutomated safety check: PassApache-2.0
Clean Code GuardamElnagdy/guard-skills1.3k2 repos~4.3kAutomated safety check: PassMIT

Similar skills

  • RAG Code Review

    lyonzin/knowledge-rag

    When performing code review on a PR, diff, snippet, or "look at this change" request, first consult the corpus for related ADRs, coding standards, prior patterns, and similar files.

    290 GitHub stars~1.8k tokensUpdated 3 days ago
    DevelopmentAuto-check passed
  • WooCommerce Code Review

    woocommerce/woocommerce

    Reviews WooCommerce code changes against the project's standards, flagging backend PHP architecture, naming, documentation, data integrity and testing violations.

    11k GitHub starsUsed in 3 repos~1.1k tokens
    DevelopmentAuto-check passed
  • Skill Doli Code Review

    Dolibarr/dolibarr

    Reviews Dolibarr PHP code for compliance with coding standards and security best practices, and fixes identified issues.

    7.7k GitHub starsUsed in 1 repo~1.1k tokens
    DevelopmentAuto-check passed
  • Dignified Python Standards

    docling-project/docling

    Applies opinionated production Python conventions chosen by the project's Python version: modern type syntax, pathlib, explicit checks and interface guidance.

    68k GitHub stars~1.5k tokensUpdated yesterday
    DevelopmentAuto-check passed
  • Clean Code Guard

    amElnagdy/guard-skills

    Reviews generated or changed production code against Clean Code, SOLID, DRY, KISS, YAGNI and LLM-specific failure modes before it ships, in any language.

    1.3k GitHub starsUsed in 2 repos~4.3k tokens
    DevelopmentAuto-check passed
  • Archify Review

    tt-a1i/archify

    Review Archify issues, PRs, or code through value, cost, and impact to support evidence-based maintenance decisions. Use for issue triage, change reviews, and…

    79k GitHub stars~415 tokensUpdated yesterday
    DevelopmentAuto-check passed

More from VCnoC/Claude-Code-Zen-mcp-Skill-Work

  • Main Router

    VCnoC/Claude-Code-Zen-mcp-Skill-Work

    Intelligent skill router that analyzes user requests and automatically dispatches to the most appropriate skill(s) or zen-mcp tools.

    116 GitHub stars~12k tokensUpdated 9 mo ago
    Auto-check passed
  • Simple Gemini

    VCnoC/Claude-Code-Zen-mcp-Skill-Work

    Collaborative documentation and test code writing workflow using zen mcp's clink to launch gemini CLI session in WSL (via 'gemini' command) where all writing operations are executed.

    116 GitHub stars~7.6k tokensUpdated 9 mo ago
    Auto-check passed
  • Deep Gemini

    VCnoC/Claude-Code-Zen-mcp-Skill-Work

    Deep technical documentation generation workflow using zen mcp's clink and docgen tools.

    116 GitHub stars~7.3k tokensUpdated 9 mo ago
    Auto-check passed
  • Plan Down

    VCnoC/Claude-Code-Zen-mcp-Skill-Work

    Method clarity-driven planning workflow using zen-mcp tools (chat, planner, consensus).

    116 GitHub stars~9.4k tokensUpdated 9 mo ago
    Auto-check passed

Categories

Questions about Codex Code Reviewer

What does Codex Code Reviewer do?

Systematic code review workflow using zen mcp's codex tool. An agent skill from VCnoC/Claude-Code-Zen-mcp-Skill-Work. Codex Code Reviewer is an agent skill from VCnoC/Claude-Code-Zen-mcp-Skill-Work. Systematic code review workflow using zen mcp's codex tool.

When should I use Codex Code Reviewer?

Codex Code Reviewer fits situations like: the user explicitly requests use codex to check the code; check if the recently generated code has any issues; check the code after each generation.

How do I install Codex Code Reviewer in Claude Code?

Run `npx skills add VCnoC/Claude-Code-Zen-mcp-Skill-Work --skill codex-code-reviewer -a claude-code`. Or copy the skill folder (skills/codex-code-reviewer in VCnoC/Claude-Code-Zen-mcp-Skill-Work) into .claude/skills/codex-code-reviewer in your project. Claude Code loads it when a task matches its description.

How do I install Codex Code Reviewer in Codex?

Run `npx skills add VCnoC/Claude-Code-Zen-mcp-Skill-Work --skill codex-code-reviewer -a codex`. Or copy the skill folder (skills/codex-code-reviewer in VCnoC/Claude-Code-Zen-mcp-Skill-Work) into .agents/skills/codex-code-reviewer in your project. Codex loads it when a task matches its description.

Can I use Codex Code Reviewer 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 VCnoC/Claude-Code-Zen-mcp-Skill-Work --skill codex-code-reviewer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/codex-code-reviewer, .gemini/skills/codex-code-reviewer, .github/skills/codex-code-reviewer and .opencode/skills/codex-code-reviewer in your project.

What does Codex Code Reviewer need to run?

Going by SKILL.md and its folder, Codex Code Reviewer needs the command-line tools its instructions call (git). Our summary lists: Python 3.

Does Codex Code Reviewer 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 Codex Code Reviewer 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 Codex Code Reviewer use?

Codex Code Reviewer is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Codex Code Reviewer use?

About 3.5k tokens (SKILL.md is roughly 14k 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 2.6k tokens, read only when the agent opens those files.

What are the alternatives to Codex Code Reviewer?

Skills that share tags, products or a category with Codex Code Reviewer: RAG Code Review (lyonzin/knowledge-rag, 290 stars), WooCommerce Code Review (woocommerce/woocommerce, 11k stars), Skill Doli Code Review (Dolibarr/dolibarr, 7.7k stars) and Dignified Python Standards (docling-project/docling, 68k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Codex Code Reviewer?

VCnoC (a GitHub user) maintains it in VCnoC/Claude-Code-Zen-mcp-Skill-Work, which has 116 GitHub stars. The repository holds 5 skills in this directory. The repository was last updated on December 21, 2025.

Source: VCnoC/Claude-Code-Zen-mcp-Skill-Work on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.