Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/ai-analyst-lab/ai-analystnpx agentmods add skills/ai-analyst-lab/ai-analyst/codex-reviewWrote 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/ai-analyst-lab/ai-analyst/codex-review)<a href="https://agentmods.dev/skills/ai-analyst-lab/ai-analyst/codex-review"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst/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/ai-analyst-lab/ai-analyst/codex-review"><img src="https://agentmods.dev/badge/skills/ai-analyst-lab/ai-analyst/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 | $0.00178 | $0.03000 |
| Opus 5 | $0.00089 | $0.01500 |
| Sonnet 5 | $0.00036 | $0.00600 |
| Haiku 4.5 | $0.00018 | $0.00300 |
Grade A, and why
codex-review scanned grade A with 0 findings 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 2d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- codex-review — 88% identical, 34 lines differ
How it starts
The opening of the file, as written. The whole thing — 214 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Codex review
Purpose
Have a second model (OpenAI Codex) independently re-derive the current analysis from the same data and compare it to Claude's original. Codex gets the question and the metric definitions, but never sees Claude's SQL, numbers, or conclusions — it writes its own queries and computes its own results. The skill then reconciles the two: AGREE, DISAGREE, or PARTIAL per finding. Two models agreeing from independent derivations is strong evidence the analysis is sound; a disagreement points to exactly where to look.
This pairs with /reliability (same model, run N times — tests stability). /codex-review
uses a different model once — it tests correctness by independent agreement.
When to Use
- User says
/codex-review, "validate with codex", "codex review", "second opinion from codex", "independently verify this", "does codex agree", "cross-check with the other model" - After producing a finding the user is about to act on and wants a second model to confirm
- Routed here whenever multi-model validation of an analytical result is wanted
Invocation
/codex-review [finding or artifact path] — validate the most recent analysis by default,
or scope to a single finding/file if given.
Example: /codex-review after answering "What's our 30-day retention?"
Instructions
⛔ HARD GATE — read before anything else
This skill is worthless unless a different model (Codex) does the validation. If Codex is not ready, you (Claude) MUST NOT perform the validation yourself. Claude re-checking Claude's analysis is circular — it produces a confident "validated ✓" that means nothing and actively misleads the student.
The rule: if Step 1's preflight returns a non-empty
missinglist, your ONLY job this turn is to help the student set up Codex. You may not proceed to Steps 2–7, and you may not substitute any other model, your own reasoning, a re-run of the SQL, or an "approximate" check. There is no fallback that uses Claude. Setup is the task when Codex is missing — completing it is the helpful outcome, not skipping ahead to a verdict.
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.
- 2d ago First seen · 214 lines · 178 tokens per session scan A d82cd3bf8c5f
codex-review is a skill published in the GitHub repository ai-analyst-lab/ai-analyst (298 stars, last pushed 3d ago), licensed MIT. It adds 178 tokens to every session and 3,000 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-12.
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