Codex Code Review

Community

PiLastDigit

codex-code-review

Iterative Codex CLI code review against an implementation plan

Overview

Publisher	PiLastDigit
Repository	`TRIP-workflow`
Skill name	`codex-code-review`
Stars	636
Forks	91
Bundled files	7
Links	Skill source Repository

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.
7 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by PiLastDigit on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/PiLastDigit/TRIP-workflow/tree/master/skills/codex-code-review
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.

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/PiLastDigit/TRIP-workflow.git /tmp/TRIP-workflow
mkdir -p .claude/skills
cp -r /tmp/TRIP-workflow/skills/codex-code-review .claude/skills/codex-code-review

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Codex 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 Codex 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 Codex 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.

Codex Code Review

Iterative code review via Codex CLI on uncommitted changes. Codex reads the plan and runs git status -s / git diff HEAD to inspect the change set.

Review output stays in state/<key>.review.txt — not docs/3-code-review/. Promotion to docs/3-code-review/CR_wa_vx.y.z.md happens after convergence, not per-turn.

State persisted under .claude/skills/codex-code-review/state/<sanitized-target>.{thread,review.txt,events.ndjson}. Invoke this skill's own wrapper scripts under .claude/skills/codex-code-review/scripts/ — they pin the correct STATE_DIR and delegate to the shared codex-plan-review implementation, so there is no export to remember (a forgotten export would silently operate on the plan-review thread for the same target).

Arguments

<target> — auto: start if no thread, resume if exists. Usually a plan path (docs/1-plans/F_*.plan.md) or a free-form label for unplanned work.
reset <target> — drop state, next call starts fresh.
show <target> — display latest review without calling Codex.

Execution

Parse $ARGUMENTS: extract action (reset/show/auto) and target.
Auto — try start.sh first (exit code 2 = thread exists -> use resume.sh):
- Start: bash .claude/skills/codex-code-review/scripts/start.sh --prompt-file .claude/skills/codex-code-review/prompts/start.tpl <target> [extra]
- Resume: bash .claude/skills/codex-code-review/scripts/resume.sh --prompt-file .claude/skills/codex-code-review/prompts/resume.tpl <target> [extra]
Reset: bash .claude/skills/codex-code-review/scripts/reset.sh <target>
Show: bash .claude/skills/codex-code-review/scripts/show.sh <target>
Parse trailing tag:
- APPROVED — propose post-convergence steps.
- REQUEST_CHANGES — surface review verbatim, engage critically (read actual code at file:line, fix legitimate ones, push back on incorrect ones), then resume.
- NEEDS_REWORK — surface to user before mass-editing.
Resume after addressing findings for incremental re-review.

Diff Visibility

Codex uses git status -s / git diff HEAD in read-only sandbox. If those fail, pass diff inline: DIFF="$(git diff --stat HEAD; echo '---'; git diff HEAD)" as extra context.

After Convergence

Promote state/<key>.review.txt to docs/3-code-review/CR_wa_vx.y.z.md using .claude/skills/TRIP-review/cr-template.md.
Continue with TRIP-3-release.

Notes

Run Codex calls in a background shell. Invoke start.sh / resume.sh via the Bash tool with run_in_background: true — never as a foreground/inline command. Codex runs at xhigh effort routinely outlast the foreground command timeout; the background task notifies on completion, then read its output. reset.sh / show.sh are instant and fine in the foreground.
Set CODEX_TIMEOUT=1800 (30 min) when invoking start.sh / resume.sh — a generous circuit breaker against hung runs, not a performance target; bump higher for unusually large diffs rather than risk killing a legitimate run. Script default is 0 = no timeout. On expiry the script fails through the normal error path with a "timed out" message in the stderr tail. Requires GNU timeout/gtimeout (macOS: brew install coreutils); warns and runs unbounded if neither is present.
Model/effort/tier defaults live in codex-plan-review/scripts/_common.sh, derived from STATE_DIR: implementation → gpt-6-luna at high effort on the fast service tier; plan review → gpt-6-astra at xhigh on standard routing; code review → gpt-6-sol at xhigh on the fast tier; codex-ask → gpt-6-astra at xhigh on standard routing. Adjust that one file to your preferred models, or override per run via CODEX_MODEL / CODEX_EFFORT / CODEX_TIER env vars; the scripts echo the effective values.
--sandbox read-only. Safe to invoke autonomously.
Thread IDs persisted per-target (no --last). Concurrent reviews don't collide.
Separate STATE_DIR from codex-plan-review — same key is fine.
Extra context -> {{EXTRA_PROMPT}}. Keep short.

Loop Shape


turn 1: start.sh -> REQUEST_CHANGES (Critical: A, Major: B C)
         address A B C
turn 2: resume.sh -> REQUEST_CHANGES (A B addressed, Minor: C partial, Suggestion: D)
         address C, optionally D
turn 3: resume.sh -> APPROVED -> promote, continue with TRIP-3-release

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 Code Review AI skill do?

Iterative Codex CLI code review against an implementation plan

Why use Codex Code Review on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/PiLastDigit/TRIP-workflow/tree/master/skills/codex-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 Codex 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 Codex Code Review?

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

Is the Codex Code Review AI skill free?

It is published on GitHub by PiLastDigit. Check the repository for licensing terms. 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Codex Code Review

Arguments

Execution

Diff Visibility

After Convergence

Notes

Loop Shape

Bundled files

Frequently asked questions

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