Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add ThibautBaissac/rails_ai_agents --skill codex-reviewgit clone --depth 1 https://github.com/ThibautBaissac/rails_ai_agentsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/thibautbaissac/rails_ai_agents/codex-review)<a href="https://agentmods.dev/skills/thibautbaissac/rails_ai_agents/codex-review"><img src="https://agentmods.dev/badge/skills/thibautbaissac/rails_ai_agents/codex-review/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/thibautbaissac/rails_ai_agents/codex-review"><img src="https://agentmods.dev/badge/skills/thibautbaissac/rails_ai_agents/codex-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00081 | $0.01164 |
| Opus 5 | $0.00041 | $0.00582 |
| Sonnet 5 | $0.00016 | $0.00233 |
| Haiku 4.5 | $0.00008 | $0.00116 |
Grade B, and why
codex-review scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
Use a single Bash call with 600000ms timeout. Capture stdout and exit code. Do **not** pass `-c model=...` — rely on the user's `~/.codex/config.toml` defaults. How it starts
The opening of the file, as written. The whole thing — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/codex-review — Independent second opinion from Codex CLI
Argument: $ARGUMENTS — one of plan | diff | spec | last-response. Default last-response.
Never fall back to reviewing Claude's own output if Codex fails. If Codex can't run, say so and stop.
1. Preflight
Run in order. Stop cleanly on first failure:
command -v codex >/dev/null 2>&1 || { echo "codex CLI not found. Install: https://github.com/openai/codex"; exit 0; }
codex login status 2>&1 | grep -qi "logged in" || { echo "codex not logged in. Run: codex login"; exit 0; }
2. Resolve target
last-response(default): identify your previous substantive assistant turn (the last turn with user-facing prose — skip turns that are pure tool calls or tool results). Write that prose verbatim to a temp file via the Write tool:$(mktemp -t codex-review).md. Record the path as$TARGET_FILE.plan: if there is an active in-conversation plan, write it to a temp file as above. Otherwise pick the newest file under./.claude/plans/(ls -t ./.claude/plans/*.md 2>/dev/null | head -1). If neither exists, report "no plan found" and stop.spec: pick the newestspec.mdunder./specs/(fd -t f 'spec\.md$' ./specs 2>/dev/null | xargs ls -t 2>/dev/null | head -1). If none, stop.diff: no file needed — Codex reads the repo directly viacodex review --uncommitted.
3. Build rubric (skip for diff)
The diff target uses codex review's built-in review prompt — do not pass a custom rubric there (--uncommitted is mutually exclusive with [PROMPT] and will error).
For plan | spec | last-response, write this rubric to $(mktemp -t codex-rubric).txt:
You are an adversarial reviewer giving a second opinion. Be terse. Do not restate what is correct.
Check, in order:
1. Correctness — logic errors, off-by-one, wrong APIs, broken invariants.
2. Missing edge cases — nulls, empty inputs, concurrent writes, partial failures, auth gaps.
3. Simpler alternatives — is there a shorter, more conventional, or better-supported approach?
4. Risk — blast radius, reversibility, data loss, security implications.
Output format: 4 sections with those exact headings. Skip a section if you have nothing material. No preamble, no summary, no praise.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 102 lines · 81 tokens per session scan B 687ee67760e0
codex-review is a skill published in the GitHub repository ThibautBaissac/rails_ai_agents (661 stars, last pushed 3mo ago), licensed MIT. It adds 81 tokens to every session and 1,164 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
autoreview
Pre-commit/ship code review: Codex default; optional Claude or Pi.
rework-rate
Measure and interpret PR rework rate — the emerging 5th DORA metric.
omh-code-review
This is a Hermes-native code-review workflow skill.
revdiff-plan
Review the last Codex assistant message (plan, analysis, or proposal) with inline annotations in a TUI overlay. Extracts the most recent response from Codex rollout files and opens it in revdiff for review and annotation. Activates on "revdiff-plan", "review plan with revdiff", "annotate plan", "review last response"…
code-reviewer
Code review specialist focused on patterns, bugs, security, and performance.
full-repo-review
Comprehensive four-wave review of all repo source files, producing a prioritized issue backlog.