OpenClaw Agent Skills is a shared repository of reusable workflows for coding agents working on OpenClaw projects. It provides skills for activities such as code-review closeout, behavior validation, session handoff, remote testing, transcript provenance, and viewing agent sessions. The catalogue entries are the project’s distributed skills and instruction.
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 agentmods add skills/openclaw/agent-skills/autoreviewnpx skills add openclaw/agent-skills --skill autoreviewgit clone --depth 1 https://github.com/openclaw/agent-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/openclaw/agent-skills/autoreview)<a href="https://agentmods.dev/skills/openclaw/agent-skills/autoreview"><img src="https://agentmods.dev/badge/skills/openclaw/agent-skills/autoreview.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 | $0.00022 | $0.01575 |
| Opus 5 | $0.00011 | $0.00788 |
| Sonnet 5 | $0.00004 | $0.00315 |
| Haiku 4.5 | $0.00002 | $0.00158 |
Grade A, and why
autoreview scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to autoreview — 477 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Auto Review
Run an independent review when the user or an owning workflow asks for one. This is code review, not Guardian approval routing. Let the reviewer choose how to analyze the change; provide the target, relevant context, and desired severity. Findings are advice to verify, not instructions to apply blindly.
Run
Use scripts/autoreview beside this skill. Keep its custom codex exec path:
native codex review cannot combine explicit Git target flags with custom instructions.
The helper combines those with evidence, severity filtering, and validated JSON;
it leaves review judgment to Codex. For an OpenClaw checkout:
AUTOREVIEW=".agents/skills/autoreview/scripts/autoreview"
"$AUTOREVIEW" --mode local
In the canonical agent-skills repo, the path is
skills/autoreview/scripts/autoreview. On Windows, invoke the helper with Python.
Use --help for the complete flags and environment overrides.
Choose the Git target explicitly when the default is ambiguous:
| Target | Arguments | Scope |
|---|---|---|
| Local work | --mode local |
HEAD → index → working tree, plus untracked files |
| Local candidate against a base | --mode local --base <ref> |
Pinned base → index → working tree, plus untracked files |
| Committed branch/PR | --mode branch --base <ref> |
Merge-base → HEAD; excludes dirty work |
| One commit | --mode commit --commit <ref> |
Raw parent → commit; a root compares against the empty tree |
--mode auto selects local work when dirty, otherwise a branch review using the
PR base or origin/main. Clean main has no implicit review target.
--mode uncommitted is an alias for local. The helper does not fetch refs.
What ships with it
13 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.
- AGENTS.md 437 B
- CLAUDE.md 9 B
- scripts/autoreview 251 KB
- scripts/autoreview_test.py 70 KB runs code
- scripts/test-review-harness 367 B
- scripts/test-review-harness.ps1 1023 B runs code
- scripts/test-review-harness.py 6.5 KB runs code
- tests/fixtures/swift-benign-status-literals.swift 1.2 KB
- tests/fixtures/typescript-benign-config-path-references.ts 1.1 KB runs code
- tests/fixtures/typescript-benign-references.ts 2.0 KB runs code
- tests/fixtures/typescript-sensitive-literals.ts 714 B runs code
- tests/test_autoreview_hardening.py 300 KB runs code
- tests/test_codex_sandbox.py 4.5 KB runs code
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.
- today Changed · -285 lines cd5e563704e8
- 5d ago First seen · 428 lines · 22 tokens per session scan A 43e683f99228
autoreview is a skill published in the GitHub repository openclaw/agent-skills (1,078 stars, last pushed yesterday), licensed MIT. It adds 22 tokens to every session and 1,575 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to autoreview, differing in 477 lines, and is treated as a copy.
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