Borrowing it
Nothing to install: this file belongs to RookieCol/caudal. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/RookieCol/caudal/main/.agents/skills/code-review/SKILL.mdgit clone --depth 1 https://github.com/RookieCol/caudalWrote 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/rookiecol/caudal/code-review)<a href="https://agentmods.dev/skills/rookiecol/caudal/code-review"><img src="https://agentmods.dev/badge/skills/rookiecol/caudal/code-review/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/rookiecol/caudal/code-review"><img src="https://agentmods.dev/badge/skills/rookiecol/caudal/code-review.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 | $0.00096 | $0.01536 |
| Opus 5.5 | $0.00038 | $0.00614 |
| Sonnet 5.5 | $0.00019 | $0.00307 |
| Haiku 4.5 | $0.00010 | $0.00154 |
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 1mo 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.
This is a copy
88% identical to code-review — 60 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Two-axis review of the diff between HEAD and a fixed point the user supplies:
- Standards — does the code conform to this repo's documented coding standards?
- Spec — does the code faithfully implement the originating issue / PRD / spec?
Both axes run as parallel sub-agents so they don't pollute each other's context, then this skill aggregates their findings.
The issue tracker should have been provided to you — run /setup-matt-pocock-skills if docs/agents/issue-tracker.md is missing.
Process
1. Pin the fixed point
Whatever the user said is the fixed point — a commit SHA, branch name, tag, main, HEAD~5, etc. If they didn't specify one, ask for it.
Capture the diff command once: git diff <fixed-point>...HEAD (three-dot, so the comparison is against the merge-base). Also note the list of commits via git log <fixed-point>..HEAD --oneline.
Before going further, confirm the fixed point resolves (git rev-parse <fixed-point>) and the diff is non-empty. A bad ref or empty diff should fail here — not inside two parallel sub-agents.
2. Identify the spec source
Look for the originating spec, in this order:
- Issue references in the commit messages (
#123,Closes #45, GitLab!67, etc.) — fetch via the workflow indocs/agents/issue-tracker.md. - A path the user passed as an argument.
- A PRD/spec file under
docs/,specs/, or.scratch/matching the branch name or feature. - If nothing is found, ask the user where the spec is. If they say there isn't one, the Spec sub-agent will skip and report "no spec available".
3. Identify the standards sources
Anything in the repo that documents how code should be written, such as CODING_STANDARDS.md or CONTRIBUTING.md.
On top of whatever the repo documents, the Standards axis always carries the smell baseline below — a fixed set of Fowler code smells (Refactoring, ch.3) that applies even when a repo documents nothing. Two rules bind it:
- The repo overrides. A documented repo standard always wins; where it endorses something the baseline would flag, suppress the smell.
- Always a judgement call. Each smell is a labelled heuristic ("possible Feature Envy"), never a hard violation — and, like any standard here, skip anything tooling already enforces.
What ships with it
1 file 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.
- 1mo ago First seen · 90 lines · 96 tokens per session scan A 6a65cc61114f
code-review is a skill published in the GitHub repository RookieCol/caudal (0 stars, last pushed 3mo ago), licensed MIT. It adds 96 tokens to every session and 1,536 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 88% identical to code-review, differing in 60 lines, and is treated as a copy.
Other skills, from other repositories
address-review
Read PR review comments from GitHub, evaluate, address, and reply.
product-review-report
A product-review workflow that researches a product and writes a Markdown report for deciding whether it is worth buying and using. It compares products from both the decision-maker's and everyday user's viewpoints.
sublime-detection-engineering
Load when the prompt's first line is Sublime detection proposal . Turns one confirmed malicious email into a tested Sublime MQL detection rule proposal: read what made the message malicious, check what already catches it, author MQL, validate the syntax, prove it matches the source message, backtest it over history…
code-review
Two-mode skill: (1) adversarial review — spec compliance + code quality + security, confidence-scored findings with file:line evidence; (2) receiving review — verify-before- agreeing discipline for acting on external/human review feedback.
review-pr
Reviews a pull request for production-readiness. Use when reviewing PRs, checking code changes before merge, or when asked to evaluate a PR.
codebase-hygiene
Two-mode skill: (1) find semantic duplicates — functions doing the same thing under different names, invisible to copy-paste detectors; (2) deepen shallow modules — thin wrappers and pass-through layers that spread complexity. Advisory and read-only; changes route through BUILD with full gates.