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 darrencroton/ai-agent-coder --skill code-reviewgit clone --depth 1 https://github.com/darrencroton/ai-agent-coderWrote 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/darrencroton/ai-agent-coder/code-review)<a href="https://agentmods.dev/skills/darrencroton/ai-agent-coder/code-review"><img src="https://agentmods.dev/badge/skills/darrencroton/ai-agent-coder/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/darrencroton/ai-agent-coder/code-review"><img src="https://agentmods.dev/badge/skills/darrencroton/ai-agent-coder/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 | $0.00054 | $0.02395 |
| Opus 5.5 | $0.00022 | $0.00958 |
| Sonnet 5.5 | $0.00011 | $0.00479 |
| Haiku 4.5 | $0.00005 | $0.00239 |
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.
How it starts
The opening of the file, as written. The whole thing — 169 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Professional Code Review
Produce a senior-level review that is evidence-based, risk-driven, and difficult to fake with a superficial skim.
Load Order
- Always read this file.
- Read references/review-matrix.md for the required review dimensions.
- Read references/scientific-and-language-priorities.md whenever the change touches C, C++, Python, numerical code, simulations, data pipelines, benchmarks, or scientific tests.
Inputs To Identify
From the user message and local context, identify:
- Review target: diff, commit, branch, files, directory, or completed task
- Requirement source: drift-audit result, plan, spec, ticket, issue, paper, docs, or explicit user criteria
- Project rules:
AGENTS.md,CLAUDE.md,CONTRIBUTING, test/build conventions - Evidence available: git diff, tests, benchmarks, logs, docs, configs, generated outputs
Resolve the target from local context when possible. Ask the user only if multiple plausible review scopes remain.
Minimum Investigation Standard
Every review must do all of the following:
- Inspect the actual change set, not just a summary.
- Read the most relevant surrounding code, not only the modified lines.
- Follow changed interfaces one hop outward:
- caller and callee
- data producer and consumer
- public API and the primary tests
- If algorithms, numerics, memory ownership, concurrency, or file formats changed, inspect related tests and invariants before concluding.
- Review all changed files. Do not stop after the first few files or after style comments.
Workflow
1. Establish scope
- Prefer
git diff,git show, or a user-supplied patch. - If there is no usable git context, review the supplied files directly and say so.
- Identify high-risk files first: core algorithms, public APIs, memory management, concurrency, I/O, configs, tests, and build files.
- Never browse
.pm/,.orchestrator/,archive/(bookkeeping/log/archive, not content) — reading a specific path already named there is fine.
What ships with it
2 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.
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 Changed · +1 lines 148ba78987c8
- 2mo ago Changed ad064cf50402
- 2mo ago First seen · 168 lines · 54 tokens per session scan A 7af7787e71f9
code-review is a skill published in the GitHub repository darrencroton/ai-agent-coder (2 stars, last pushed 7d ago), licensed MIT. It adds 54 tokens to every session and 2,395 once invoked, about $0.0002 per session on Opus 5.5. 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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