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 curiositech/windags-skills --skill code-review-checklistgit clone --depth 1 https://github.com/curiositech/windags-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/curiositech/windags-skills/code-review-checklist)<a href="https://agentmods.dev/skills/curiositech/windags-skills/code-review-checklist"><img src="https://agentmods.dev/badge/skills/curiositech/windags-skills/code-review-checklist/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/curiositech/windags-skills/code-review-checklist"><img src="https://agentmods.dev/badge/skills/curiositech/windags-skills/code-review-checklist.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 | $0.00043 | $0.01786 |
| Opus 5 | $0.00022 | $0.00893 |
| Sonnet 5 | $0.00009 | $0.00357 |
| Haiku 4.5 | $0.00004 | $0.00179 |
Grade A, and why
code-review-checklist 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 5d 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.
The source is not reproduced here
A licence we could not identify
The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.
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.
- 5d ago First seen · 168 lines · 43 tokens per session scan A 173533880525
code-review-checklist is a skill published in the GitHub repository curiositech/windags-skills (10 stars, last pushed 1mo ago), with no licence file. It adds 43 tokens to every session and 1,786 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 2026-09-03.
Other skills, from other repositories
code-review-quality
Conduct context-driven code reviews focusing on quality, testability, and maintainability. Use when reviewing code, providing feedback, or establishing review practices.
code-review
Use to judge a concrete diff, branch, or GitHub PR on its own merits with no rsc-SDD spec/plan chain to key off — the spec-less giving pass behind /code-review: only findings you can defend, one verdict, read-only unless --comment or --fix. NOT the SDD gate keyed to 02-DOCS/wiki/sdd/ that also processes incoming…
code-review-expert
Expert-level code review focusing on quality, security, performance, and maintainability. Use this skill for conducting thorough code reviews, identifying issues, and providing constructive feedback.
code-review
Performs thorough code reviews with focus on best practices, security, performance, and maintainability. Use this skill when reviewing pull requests, auditing code quality, or getting feedback on implementations.
code-review-checklist
Guide an AI agent through a structured code review — correctness, security, performance, readability, and test coverage — producing a summary with actionable, prioritized feedback. Triggers on pull-request review, diff review, or "review this code" requests.
Code Review Checklist
Runs a systematic checklist review on any code diff or file, covering correctness, security, performance, and readability.