autoreview

autoreview is a skill for Claude Code, Codex from openclaw/crabbox. It costs 22 tokens per session (8,085 once invoked), scanned A, original, MIT.

A structured code-review workflow that can use Codex, Claude, Amp, Pi, or Kimi when a review is explicitly requested.

In plain words
What is it for?
Use it for a requested second-model review of code, choosing a supported review engine and checking each reported issue before acting on it.
Why use it?
It separates review from implementation and focuses the default review on serious problems that could block normal use or compromise safety.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/openclaw/crabbox/autoreview
Any agent
npx skills add openclaw/crabbox --skill autoreview
Clone the repo
git clone --depth 1 https://github.com/openclaw/crabbox

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for autoreview

README.md
[![agentmods](https://agentmods.dev/badge/skills/openclaw/crabbox/autoreview.svg)](https://agentmods.dev/skills/openclaw/crabbox/autoreview)
Your own site
<a href="https://agentmods.dev/skills/openclaw/crabbox/autoreview"><img src="https://agentmods.dev/badge/skills/openclaw/crabbox/autoreview.svg" alt="Measured on agentmods" height="20"></a>
Per session 22 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 8,085 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00022 $0.08085
Opus 5 $0.00011 $0.04043
Sonnet 5 $0.00004 $0.01617
Haiku 4.5 $0.00002 $0.00809

Measured 4d ago against content hash 43e683f99228, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

autoreview 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 4d ago.

The scan reads SKILL.md. This mod also ships 7 executable files (scripts/autoreview_test.py, scripts/test-review-harness.ps1, scripts/test-review-harness.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

.agents/skills/autoreview/SKILL.md · 428 lines

How it starts

The opening of the file, as written. The whole thing — 428 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Auto Review

Run the bundled structured review helper only when the user explicitly asks for autoreview, a second-model review, or one of its named review engines. This is code review, not Guardian auto_review approval routing.

Codex review is the default when no engine is set. It uses gpt-5.6-sol with high reasoning by default, then retries once with gpt-5.6-terra only when the account cannot access Sol. Claude review is optional and uses claude-fable-5 by default. Amp review is optional and uses openai/gpt-5.6-sol with high reasoning by default. Pi and Kimi use the model configured by their respective CLIs unless --model overrides it.

Do not invoke Autoreview automatically before a commit, push, PR, merge, deploy, or final reply. Repository or workflow rules may call it only when they explicitly name it.

Contract

  • Default accepted findings are P0 only: report issues worth blocking the current change because they materially break the normal flow, outcome, or safety boundary. Use --max-priority P1, P2, or P3 only when the caller explicitly asks for a wider review.
  • Treat review output as advisory. Never blindly apply it.
  • Verify every finding by reading the real code path and adjacent files.
  • Read dependency docs/source/types when the finding depends on external behavior.
  • Reject unrealistic edge cases, speculative risks, unrelated rewrites, and fixes that over-complicate the codebase.
  • Prefer root-cause fixes at the right ownership boundary. A coherent refactor is appropriate when it removes the bug class, duplicate policy, stale paths, or ownership confusion; do not default to a symptom patch.
  • When an accepted finding exposes a bug class or repeated pattern, inspect its owner and relevant sibling implementations before fixing.
  • Fix the same bug class across its owner-boundary neighborhood when practical; stop at unrelated invariants, different owners, and unapproved contract changes.
  • Run one bounded review pass. If an accepted finding changes code, run the smallest relevant test; rerun Autoreview only when the user explicitly requests another pass.
  • For security-audit suppression changes, verify accepted findings remain auditable: suppressed findings stay in structured output, active output keeps an unsuppressible suppression notice, and aggregate findings cannot hide unrelated active risk.
  • Never switch or override the requested review engine/model except for the documented Codex Sol-to-Terra account-access fallback. Capacity, rate-limit, and unrelated failures keep the same engine/model.
  • Be patient with large bundles. Structured review can take up to 30 minutes while the model call is active, especially with Codex tools or web search.
  • Treat heartbeat lines like review still running: ... elapsed=... pid=... as healthy progress, not a hang. Let the helper continue while heartbeats are advancing. Pass --stream-engine-output when live engine text is useful; Codex and Claude filter tool/file chatter, other runnable engines pass raw output through.
  • Do not kill a review just because it has been quiet for 2-5 minutes, or because it is still running under the 30-minute window. Inspect the process only after missing multiple expected heartbeats, after 30 minutes, or after an obviously failed subprocess; prefer letting the same helper command finish.
  • Tools are useful in review mode. Codex receives the validated bundle in an empty workspace so ignored files and linked-worktree metadata remain unreadable; web search stays available for dependency contracts and upstream docs.
  • Security perspective is always included, but it should not cripple legitimate functionality. Report security findings only when the change creates a concrete, actionable risk or removes an important safety check.
  • Reviewer subprocesses preserve engine authentication and non-credentialed proxy variables needed by headless or restricted-network environments while stripping process-injection, Git override, and credentialed proxy values.
  • Immediately before every provider call, autoreview writes the exact outgoing review pack to an owner-only temporary file and scans it with TruffleHog using verified,unknown. It uses the installed binary with --no-update to disable self-update checks and attempts. The scan covers prompt and dataset inputs, untracked content, and every diff line, including deleted lines. A finding, scanner error, or missing TruffleHog binary refuses the send and names the implicated repository file when it can be resolved; credentials are never redacted and forwarded. Security-sensitive paths remain omitted. Safe large diffs are sent as one pass while they fit the aggregate prompt limit, then partitioned into complete bounded passes without truncation.
  • Regression provenance needs patch proof, not blame alone. git log -S/-G, git blame, commit subjects, and PR metadata locate candidates. Before saying introduced by, inspect raw parents with git --no-replace-objects cat-file -p <sha> and verify the implicated behavior changed in git --no-replace-objects diff --no-ext-diff --no-textconv <raw-parent> <sha> -- <path>; a genuine root needs raw-header proof that it has no parents.
  • Blame ^sha, porcelain boundary, and shallow/grafted history alone are not introduction proof. --root can hide boundary markers; git show or rev-list --parents can make a shallow boundary look like a root. An available raw parent permits explicit comparison even at a shallow boundary; missing parents or an unverifiable patch require unknown with the gap. Use carried forward only for verified preexisting behavior and made visible only for a verified trigger. Apply the same bar to finding prose, summaries, and owner hints.
  • Keep code author, introducing PR author, merger, committer, automation trigger, and current PR author separate; none of those roles alone proves causation. Cite the verified commit/PR/date. If no PR is traceable, use the verified commit and known author identity; unknown identities stay unknown, and missing PR metadata is not a separate finding.
  • For automation merges, identify the human trigger only from explicit timeline/comment/event evidence, such as a maintainer automerge command or arming label. Report automerge triggered by @login only when verified; otherwise say trigger unknown. Triggering or merging is not proof of authorship or introduction.
  • Do not invoke built-in codex review, nested reviewers, or review panels from inside the review. The helper builds one validated bundle, calls the selected engine once for normal inputs or once per complete bounded chunk for oversized inputs, validates the structured results, and stops.
  • Stop as soon as the helper exits 0 with no accepted/actionable findings. Do not run an extra review just to get a nicer "clean" line, a second opinion, or clearer closeout wording.
  • Treat scoped-clean with exit 0 as clean only for the selected Git target and requested priority. filtered is not a correctness certificate; incomplete requires resolving the scope mismatch or missing required finding before claiming clean.
  • If rejecting a finding as intentional/not worth fixing, add a brief inline code comment only when it explains a real invariant or ownership decision that future reviewers should know.
  • If gh/Gitcrawl reports database disk image is malformed, run gitcrawl doctor --json once to let the portable cache repair before retrying review; do not bypass the shim unless repair fails and freshness requires live GitHub.
  • If Gitcrawl reports a portable manifest mismatch, source/runtime DB health error, or stale portable-store checkout, run gitcrawl doctor --json and inspect source_db_health, runtime_db_health, and portable_store_status before falling back to live GitHub.
  • Do not push just to review. Push only when the user requested push/ship/PR update.

Read the full file on GitHub · 428 lines

Changes

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.

  1. 4d ago First seen · 428 lines · 22 tokens per session scan A 43e683f99228

Subscribe to this mod's changes

autoreview is a skill published in the GitHub repository openclaw/crabbox (1,362 stars, last pushed today), licensed MIT. It adds 22 tokens to every session and 8,085 once invoked, about $0.0001 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 2026-08-30.

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