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Codex Review

CommunityPopular
jezweb
codex-review

Run an independent code review using the OpenAI Codex CLI in headless mode. Gets a second opinion from a different model family (the current Codex models) on recent changes, a PR, a commit, or the whole app — covering bugs, regressions, security, data consistency, UX/state bugs, performance risks, and testing gaps. Saves a severity-prioritised report to .jez/reviews/. Triggers: 'codex review', 'review with codex', 'independent code review', 'what does codex think', 'get codex to review'.

Overview

Publisherjezweb
Repositoryclaude-skills
Skill namecodex-review
Stars
1K
Forks
102
Bundled files
1
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.

  • 1 bundled files

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

  • Open source

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

Installation

Install the Codex 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/jezweb/claude-skills.git /tmp/claude-skills
mkdir -p .claude/skills
cp -r /tmp/claude-skills/plugins/dev-tools/skills/codex-review .claude/skills/codex-review
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Codex 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 Codex 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 Codex 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.

Codex Review

Run an independent code review via the OpenAI Codex CLI (codex review). The value is a second opinion from a different model family than the one that wrote the code — Codex catches things Claude misses due to author bias.

Complements brains-trust (generic multi-model opinions). This skill is specialised: git-aware, uses a tuned review prompt, saves structured output.

When to Use

  • After a meaningful change, before committing or shipping
  • Before opening a PR, to self-review with an independent reviewer
  • When something feels off but you can't articulate what
  • Periodic whole-app reviews for projects in active development
  • When the user explicitly asks for an "independent" or "second opinion" review

Do NOT use for:

  • Trivial changes (typos, one-line fixes)
  • Research questions or architecture discussions — use brains-trust instead
  • Auto-fixing issues — this is advisory only

Preflight

  1. Confirm Codex CLI is installed:

    bash
    which codex

    If missing: tell the user to install it (brew install codex on macOS, or see https://github.com/openai/codex) and stop. Do not continue.

  2. Confirm auth: the first codex review call will fail clearly if not logged in. If that happens, instruct the user to run codex login and stop.

Determine scope

Pick the scope flag based on what the user asked for:

User intentFlag
"codex review" / "review the app" / "full review" / defaultno flag (reviews whole app at current HEAD)
"review my changes" / "review what I just did" / "review uncommitted"--uncommitted
"review this branch vs main" / "review the PR"--base main (or the branch they name)
"review commit abc123"--commit abc123

Default is whole-app review. A bare "codex review" with no qualifier means review the entire codebase at HEAD — not just uncommitted changes. Only use --uncommitted if the user specifically refers to their recent/uncommitted work.

If ambiguous, ask once. Don't guess on commits or branches.

Run the review

The canonical review prompt lives in prompt.md next to this skill. Pipe it via stdin to avoid shell escaping:

bash
mkdir -p .jez/reviews
TS=$(date +%Y-%m-%d-%H%M)
OUT=".jez/reviews/codex-${TS}.md"
SKILL_DIR="$(dirname "$0")"  # or use the skill's absolute path

# Example: uncommitted changes
cat "${SKILL_DIR}/prompt.md" | codex review --uncommitted - 2>&1 | tee "$OUT"

Other scopes:

bash
# Vs base branch
cat prompt.md | codex review --base main - 2>&1 | tee "$OUT"

# Specific commit
cat prompt.md | codex review --commit abc123 - 2>&1 | tee "$OUT"

# Current HEAD (no scope flag)
cat prompt.md | codex review - 2>&1 | tee "$OUT"

codex review can take several minutes on a large diff. Let it run.

Summarise for the user

After Codex finishes:

  1. Print the output path: Report saved to .jez/reviews/codex-<timestamp>.md
  2. Read the saved report and extract the top findings (anything under Critical and High)
  3. Show them inline in the chat, with file:line references intact
  4. Offer to action specific findings: "Want me to fix the SQL injection in auth.ts:42?"

Rules

  • Advisory only. Never auto-apply Codex's suggestions. Read the findings, discuss with the user, fix with their approval.
  • Don't leak Claude's reasoning into the prompt. The prompt.md file is deliberately neutral — Codex reviews the code, not Claude's narrative about the code. Independence is the whole point.
  • Save to .jez/reviews/, never .claude/ (protected directory).
  • One report per run. Don't overwrite — the timestamp makes each run unique so the user can compare.
  • Report what Codex actually found. Don't soften, editorialise, or skip findings you disagree with. If you think Codex is wrong about something, say so as your own opinion after showing what Codex said.

Verification

The skill is working if:

  • Preflight correctly detects a missing codex binary
  • The right scope flag is chosen based on user intent
  • The report file appears in .jez/reviews/ with a sensible timestamp
  • The file contains severity-prioritised findings with file:line refs
  • Claude surfaces the top findings without auto-fixing them

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 Codex Review AI skill do?

Run an independent code review using the OpenAI Codex CLI in headless mode. Gets a second opinion from a different model family (the current Codex models) on recent changes, a PR, a commit, or the whole app — covering bugs, regressions, security, data consistency, UX/state bugs, performance risks, and testing gaps. Saves a severity-prioritised report to .jez/reviews/. Triggers: 'codex review', 'review with codex', 'independent code review', 'what does codex think', 'get codex to review'.

Why use Codex Review on TypingMind?

Because you install it once and use it with any model. Codex 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 Codex Review in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/jezweb/claude-skills/tree/main/plugins/dev-tools/skills/codex-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 Codex 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 Codex Review?

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

Is the Codex Review AI skill free?

Yes. It is published on GitHub by jezweb 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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