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 shimo4228/claude-harness --skill codex-reviewgit clone --depth 1 https://github.com/shimo4228/claude-harnessWrote 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/shimo4228/claude-harness/codex-review)<a href="https://agentmods.dev/skills/shimo4228/claude-harness/codex-review"><img src="https://agentmods.dev/badge/skills/shimo4228/claude-harness/codex-review.svg" alt="Measured on agentmods" 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 | $0.02601 |
| Opus 5 | $0.00089 | $0.01300 |
| Sonnet 5 | $0.00036 | $0.00520 |
| Haiku 4.5 | $0.00018 | $0.00260 |
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 3d 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.
- **read-only は argv と config の両面で pin する**: script は `--ignore-user-config --ignore-rules -c approval_policy="never"` を固定で付ける（`~/.codex/config.toml` の `approvals_reviewer=auto_review` と `.rules` の `git push` / `uv run` How it starts
The opening of the file, as written. The whole thing — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Codex Review — Cross-Model Second Opinion
A thin, read-only wrapper around codex review (OpenAI Codex CLI). It adds one
cross-model seam to the review chain: a different model family reviews the
diff, so it catches blind spots that an author and a same-model reviewer share.
Grounded in ADR-0013: this is a decorrelation seam, not a throughput tool. Use Claude's own sub-agents / Workflow for parallel throughput; use this only where a second model adds judgment Claude structurally can't add alone.
When to Use
Opt-in のみ（ADR-0055 — implementation chain の既定ステップではない）。 発火はユーザーの明示要求、または writing orchestrator skill が panel member として 明示的に配線している場合（readme-writer 等 — writing chain は ADR-0055 の対象外）だけ:
- The user asks for a second opinion from a non-Claude model on a diff ("codex review", "別モデルでレビュー", /codex-review).
- The user asks for a plan-stage premise challenge ("プランを Codex に反証させて", /codex-review --plan).
- High-stakes prose diffs when the user asks for a cross-model pass before publishing/deposit. Use prompt-driven mode with writing-focused instructions; scoped modes run Codex's built-in code-review instructions, which fit prose poorly.
Never self-trigger as part of the implementation chain. Skip it when Codex is not authenticated (the script fails fast — fall back to the Claude reviewers).
Execution
bash ~/.claude/skills/codex-review/codex-review.sh $ARGUMENTS
Modes (passed straight through to codex review):
| Invocation | Scope |
|---|---|
/codex-review |
current branch vs auto-detected base (main/master/…) — PR-style |
/codex-review --uncommitted |
staged + unstaged + untracked — Verify / pre-commit |
/codex-review --base <branch> |
vs an explicit base branch |
/codex-review --commit <sha> |
a single commit |
/codex-review -m <model> |
pick a Codex model (combine with any row) |
/codex-review "focus on the auth changes" |
prompt-driven review of the working tree |
What ships with it
4 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.
- 3d ago Changed · -11 tokens per session 3454e27a7095
- 8d ago First seen · 133 lines · 189 tokens per session scan B a2376571cc3c
codex-review is a skill published in the GitHub repository shimo4228/claude-harness (2 stars, last pushed 2d ago), licensed MIT. It adds 178 tokens to every session and 2,601 once invoked, about $0.0009 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 2026-08-31.
Other skills, from other repositories
pi-parity-review
Adversarially verify that a ported change is faithful to the original pi implementation (TS source + published npm build). Use after porting upstream pi changes, or standalone on any area of this repo ("is X faithful to pi?").
pi-go-review
Review ported Go code for idiomatic quality — that the port maximizes Go rather than transliterating TypeScript. Use after porting upstream pi changes, or standalone on any diff in this repo.
clean
Pre-commit anti-slop audit — checks staged/dirty files for code slop (debug artifacts, single-use helpers, dead imports) AND documentation slop (stale claims, broken internal links, new .md files, redundant sections). Writes a sentinel so the pre-commit-gate hook lets the commit through. MUST be invoked before git…
coding-quality-loop
Use when a coding agent must turn a software goal, bug, issue, or refactor into a small, verified, independently reviewed code change.
agent-adoption-triage
Five-question triage for routing AI work to the right architecture — script, algorithmic search, LLM workflow, or autonomous agentic loop — before any agent is built. Use when someone says "let's build an agent for X", when deciding whether a use case actually needs an autonomous agent, when reviewing an agent…
self-critic
This agent's own internal adversarial critic loop. Hardens every deliverable with a fresh no-memory domain critic until it passes twice consecutively with zero CRITICALs before return.