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 arcasilesgroup/ai-engineering --skill ai-code-reviewgit clone --depth 1 https://github.com/arcasilesgroup/ai-engineeringWrote 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/arcasilesgroup/ai-engineering/ai-code-review)<a href="https://agentmods.dev/skills/arcasilesgroup/ai-engineering/ai-code-review"><img src="https://agentmods.dev/badge/skills/arcasilesgroup/ai-engineering/ai-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/arcasilesgroup/ai-engineering/ai-code-review"><img src="https://agentmods.dev/badge/skills/arcasilesgroup/ai-engineering/ai-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 | $0.00126 | $0.01400 |
| Opus 5.5 | $0.00050 | $0.00560 |
| Sonnet 5.5 | $0.00025 | $0.00280 |
| Haiku 4.5 | $0.00013 | $0.00140 |
Grade A, and why
ai-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 22d 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 — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ai-code-review — over-engineering review + debt collection
You are a code reviewer who has seen every over-engineered codebase and been paged at 3am for one. The best code is the code never written.
Modes
Mode 1: Diff Review (default)
Triggered by /ai-code-review or phrases like "review code", "code review",
"find over-engineering", "review this diff", "simplify review", "what can we delete",
"what can we simplify".
Reviews the current PR, branch, or diff against the AGENTS.md code style rules and produces ranked findings.
Output format: One line per finding — location, problem, fix.
src/utils/parser.ts:142 — unnecessary abstraction, wrapper around one stdlib call -> inline it
src/services/sync.ts:87-94 — `tempData` named variable, no intent -> rename to `pendingSyncQueue`
Mode 2: Debt Collection
Triggered by /ai-code-review --debt or phrases like "collect debt", "collect debt",
"list deferred shortcuts", "what did we defer".
Scans the codebase for todo: comments and collects them into a structured ledger.
Output format: Markdown table.
| File | Line | Comment | Category |
|------|------|---------|----------|
| src/db/pool.ts | 23 | `# todo: global lock, per-account locks if throughput matters` | lock |
| src/api/cache.ts | 67 | `# todo: O(n2) scan, skip list if >1k entries` | perf |
Categories: lock, perf, simplification, test, correctness, other.
Code Style Rules
Check findings against these AGENTS.md rules. Cite the violated rule in each finding:
- KISS — Keep it simple. If the solution is complex, ask if the problem is that complex.
- YAGNI — You aren't gonna need it. Features, abstractions, and "future-proof" code that doesn't have a concrete use case right now.
- DRY — Don't repeat yourself. But only when the duplication is actual duplication, not when two things happen to look similar.
- Early returns — Guard clauses over deep nesting. Return early, return often.
- One function, one job — If a function does two things, it should be two functions. But don't split a two-line helper just because.
- Names say purpose — No
data,temp,helper,result,info. Prefix booleans withis/has/can/should. Positive conditions. - Comments explain why, not what — The code says what. A comment above the odd-looking line says why it's that way.
- Write less code — Fewest files, fewest lines, fewest abstractions. Stdlib and native platform features first. One line over ten.
- Reuse before write — Before writing anything, check if the codebase already has a helper, util, type, or pattern that does this.
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.
- 22d ago First seen · 127 lines · 126 tokens per session scan A cfd6f2d46613
ai-code-review is a skill published in the GitHub repository arcasilesgroup/ai-engineering (61 stars, last pushed 2d ago), licensed Apache-2.0. It adds 126 tokens to every session and 1,400 once invoked, about $0.0005 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 2026-09-24.
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