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 borhen68/SkillEngine --skill code-review-and-qualitygit clone --depth 1 https://github.com/borhen68/SkillEngineWrote 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/borhen68/skillengine/code-review-and-quality)<a href="https://agentmods.dev/skills/borhen68/skillengine/code-review-and-quality"><img src="https://agentmods.dev/badge/skills/borhen68/skillengine/code-review-and-quality/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/borhen68/skillengine/code-review-and-quality"><img src="https://agentmods.dev/badge/skills/borhen68/skillengine/code-review-and-quality.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 | $0.00063 | $0.03478 |
| Opus 5.5 | $0.00025 | $0.01391 |
| Sonnet 5.5 | $0.00013 | $0.00696 |
| Haiku 4.5 | $0.00006 | $0.00348 |
Grade A, and why
code-review-and-quality 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
80% identical to code-review-and-quality — 124 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 — 383 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review and Quality
Overview
Multi-dimensional code review with quality gates. Every change gets reviewed before merge — no exceptions. Review covers five axes: correctness, readability, architecture, security, and performance.
The approval standard: Approve a change when it definitely improves overall code health, even if it isn't perfect. Perfect code doesn't exist — the goal is continuous improvement. Don't block a change because it isn't exactly how you would have written it. If it improves the codebase and follows the project's conventions, approve it.
When to Use
- Before merging any PR or change
- After completing a feature implementation
- When another agent or model produced code you need to evaluate
- When refactoring existing code
- After any bug fix (review both the fix and the regression test)
Iron Rules
These target the review failure modes specific to AI agents. Each is absolute.
- No approval without evidence of review. "LGTM, clean implementation" is a rubber stamp. An approval must state what was checked per axis and what was found — including "checked X, found nothing" — or it didn't happen.
- Review the blast radius, not just the diff. Changed lines are where bugs are born; unchanged callers are where they detonate. For every modified public function, type, or contract, trace at least its direct callers before approving.
- Every finding needs location, severity, and a concrete fix. "Consider improving error handling" is noise.
"
src/api/tasks.ts:42— Critical:deleteTaskswallows the DB error and returns 200; propagate and map to 500" is a review. - Verify claims, don't inherit them. "Tests pass" in a PR description is a claim. Check the CI run or run them yourself. Authors — human or agent — report what they believe, not what is true.
- Sycophancy is a review defect. If the approach has a problem, say so directly with reasoning, even when the author is the user. A polite review that withholds a known issue is worse than no review.
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 · 383 lines · 63 tokens per session scan A e699756f48b7
code-review-and-quality is a skill published in the GitHub repository borhen68/SkillEngine (17 stars, last pushed 4mo ago), licensed MIT. It adds 63 tokens to every session and 3,478 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 80% identical to code-review-and-quality, differing in 124 lines, and is treated as a copy.
Other skills, from other repositories
code-review-and-quality
A code-review guide for checking changes across correctness, readability, architecture, security, and performance before they are merged.
code-simplification
A code-review and refactoring guide for making existing code easier to read while keeping its behavior unchanged. Refactoring means changing how code is organized without changing what it does.
doubt-driven-development
A development practice that puts an independent, fresh-context challenge in front of important coding decisions.
code-review-and-quality
Conducts multi-axis code review. Use before merging any change. Use when reviewing code written by yourself, another agent, or a human. Use when you need to assess code quality across multiple dimensions before it enters the main branch. Use when asked to review a diff or a pull request, even when the diff is pasted…
code-simplification
Simplifies code for clarity. Use when refactoring code for clarity without changing behavior. Use when code works but is harder to read, maintain, or extend than it should be. Use when reviewing code that has accumulated unnecessary complexity.
doubt-driven-development
Subjects every non-trivial decision to a fresh-context adversarial review before it stands. Use when you want every assumption cross-examined before proceeding, when stress-testing a plan for hidden failure modes, when correctness matters more than speed, when working in unfamiliar code, when stakes are high…