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 vadimcomanescu/codex-skills --skill code-reviewergit clone --depth 1 https://github.com/vadimcomanescu/codex-skillsWrote 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/vadimcomanescu/codex-skills/code-reviewer)<a href="https://agentmods.dev/skills/vadimcomanescu/codex-skills/code-reviewer"><img src="https://agentmods.dev/badge/skills/vadimcomanescu/codex-skills/code-reviewer/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/vadimcomanescu/codex-skills/code-reviewer"><img src="https://agentmods.dev/badge/skills/vadimcomanescu/codex-skills/code-reviewer.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 | $0.00059 | $0.00458 |
| Opus 5.5 | $0.00024 | $0.00183 |
| Sonnet 5.5 | $0.00012 | $0.00092 |
| Haiku 4.5 | $0.00006 | $0.00046 |
Grade A, and why
code-reviewer 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 1mo 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.
What it actually says
Code Reviewer
Give reviews that help the author ship safely and quickly.
Quick Start
- Understand intent: what’s the user-facing / system-facing change and why?
- Review in this order:
- Correctness (edge cases, invariants, error handling)
- Safety (security + data handling + secrets)
- Maintainability (structure, naming, interfaces)
- Performance (hot paths, I/O, allocations, DB queries)
- Tests (do they fail before the fix? do they cover the right behavior?)
- Leave comments that are:
- Actionable (what to change) + why (risk/benefit) + scope (must vs nice-to-have)
Large diff triage (use when the change is big)
- Start with the entrypoints and high-risk files (auth, payments, data writes).
- Identify invariants the change must preserve, then hunt for violations.
- Skim for mechanical changes and collapse them; focus deep review on behavioral deltas.
When to request changes
- Bugs or correctness issues that can ship user-impacting failures.
- Security/privacy regressions or data handling gaps.
- Missing or inadequate tests for new behavior or fixed bugs.
Output format (recommended)
- Summary: what the change does
- Major issues: must-fix items (blockers)
- Minor suggestions: improvements / nits
- Test plan: how to validate locally/CI
- Follow-ups: tickets/cleanup that shouldn’t block merge
Optional tool: generate a review report from git diff
From the repo you’re reviewing:
python ~/.codex/skills/code-reviewer/scripts/review_diff.py --base origin/main --out /tmp/review.md
References
- Review checklist and comment style:
references/review-checklist.md
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 46 lines · 59 tokens per session scan A 02d8a3e96f03
code-reviewer is a skill published in the GitHub repository vadimcomanescu/codex-skills (25 stars, last pushed 9mo ago), licensed MIT. It adds 59 tokens to every session and 458 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-30.
Other skills, from other repositories
autoreview
Structured code review through the shared OpenClaw agent-skills installation.
omh-code-review
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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"…
re0-merge
Review and land an external contribution the way this suite does: gate it against the thesis, land it with the author's credit intact, complete a new skill rather than merging it raw, then approve, credit, and explain before closing. Use when reviewing a pull request, as any collaborator or maintainer, not only the…
explore-unknowns
Guide the user through a quadrant walk that maps the unknowns of a task — open by listing the known knowns, then work through known unknowns, unknown knowns, and unknown unknowns one stage at a time, ending with a complete four-quadrant map in the user's hands. Use when a request is ambiguous or underspecified, the…
asplos-writing-style
Use when drafting or revising ASPLOS prose — engineering the first two pages that rapid review actually reads, stating the cross-layer insight as one quotable sentence, structuring per-layer mechanism sections, writing bounded claims, and fitting everything into 11 self-contained pages that include figures and…