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/shwilliamson/automatasaurus/code-reviewnpx skills add shwilliamson/automatasaurus --skill code-reviewgit clone --depth 1 https://github.com/shwilliamson/automatasaurusWrote 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/shwilliamson/automatasaurus/code-review)<a href="https://agentmods.dev/skills/shwilliamson/automatasaurus/code-review"><img src="https://agentmods.dev/badge/skills/shwilliamson/automatasaurus/code-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 | $0.00030 | $0.02192 |
| Opus 5 | $0.00015 | $0.01096 |
| Sonnet 5 | $0.00006 | $0.00438 |
| Haiku 4.5 | $0.00003 | $0.00219 |
Grade A, and why
code-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 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.
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.
How it starts
The opening of the file, as written. The whole thing — 330 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review Skill
Guidelines for performing effective code reviews that catch issues, improve code quality, and maintain a positive team dynamic.
Review Mindset
Default to requesting changes. Your job is to protect the codebase. An approval is a statement that you'd stake your reputation on this code — if you have any doubt, request changes. It's always cheaper to do another review round than to ship a bug.
Goals of Code Review
- Catch bugs and design flaws before they reach production
- Prevent security issues — treat every input as hostile
- Enforce quality standards — the codebase should get better with every PR, never worse
- Maintain architectural integrity — reject code that works but is built wrong
The Right Attitude
- You are a gatekeeper. That's not a dirty word — it's your job. The codebase depends on you saying "no" when something isn't ready.
- Be direct and specific. Don't soften feedback with hedging language.
- Approving bad code is worse than blocking good code. When in doubt, request changes.
- A clean diff is not the same as correct code. Read critically, assume there are bugs, and prove yourself wrong.
Review Process
1. Understand the Context First
Before looking at code:
1. Read the PR description
2. Read the linked issue
3. Understand WHAT is being done and WHY
4. Consider: Is this the right approach?
2. First Pass: High-Level Review
Ask yourself:
- Does this solve the problem described in the issue?
- Is the approach reasonable?
- Are there obvious architectural concerns?
- Is anything missing?
3. Second Pass: Detailed Review
Look at each file for:
- Correctness (does it work?)
- Edge cases and error handling
- Security implications
- Performance concerns
- Test coverage
- Code style and readability
4. Summarize Your Review
End with an overall assessment:
**[Architect]** Overall this looks good. Clean implementation of the user registration flow.
A few suggestions:
1. Consider adding rate limiting (security)
2. The validation error messages could be more user-friendly
3. Minor: prefer `const` over `let` where possible
Approving with minor suggestions - none are blocking.
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 First seen · 330 lines · 30 tokens per session scan A 810d7c73d193
code-review is a skill published in the GitHub repository shwilliamson/automatasaurus (5 stars, last pushed 6mo ago), licensed MIT. It adds 30 tokens to every session and 2,192 once invoked, about $0.0002 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 2026-08-31.
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chat-perf
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