addyosmani/agent-skills is a collection of reusable workflows, quality checks, commands, and other instructions that guide AI coding agents through software development. It is for developers who want agents to follow consistent engineering practices, and the catalogue entries are its packaged skills, commands, agents, plugins, instructions, and hooks.
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 addyosmani/agent-skills --skill code-review-and-qualitygit clone --depth 1 https://github.com/addyosmani/agent-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/addyosmani/agent-skills/code-review-and-quality)<a href="https://agentmods.dev/skills/addyosmani/agent-skills/code-review-and-quality"><img src="https://agentmods.dev/badge/skills/addyosmani/agent-skills/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/addyosmani/agent-skills/code-review-and-quality"><img src="https://agentmods.dev/badge/skills/addyosmani/agent-skills/code-review-and-quality.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
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 | $0.00051 | $0.04357 |
| Opus 5 | $0.00026 | $0.02178 |
| Sonnet 5 | $0.00010 | $0.00871 |
| Haiku 4.5 | $0.00005 | $0.00436 |
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 10d 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.
Copies of this mod
8 near-identical copies found in the catalogue:
- code-review-and-quality — 100% identical, 9 lines differ
- code-review-and-quality — 100% identical, 4 lines differ
- code-review-and-quality — 100% identical, 4 lines differ
- code-review-and-quality — 100% identical, 4 lines differ
- code-review-and-quality — 100% identical, 4 lines differ
- code-review-and-quality — 98% identical, 18 lines differ
- code-review-and-quality — 98% identical, 0 lines differ
- code-review-and-quality — 97% identical, 1 lines differ
How it starts
The opening of the file, as written. The whole thing — 397 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)
The Five-Axis Review
Every review evaluates code across these dimensions:
1. Correctness
Does the code do what it claims to do?
- Does it match the spec or task requirements?
- Are edge cases handled (null, empty, boundary values)?
- Are error paths handled (not just the happy path)?
- Does it pass all tests? Are the tests actually testing the right things?
- Are there off-by-one errors, race conditions, or state inconsistencies?
2. Readability & Simplicity
Can another engineer (or agent) understand this code without the author explaining it?
- Are names descriptive and consistent with project conventions? (No
temp,data,resultwithout context) - Is the control flow straightforward (avoid nested ternaries, deep callbacks)?
- Is the code organized logically (related code grouped, clear module boundaries)?
- Are there any "clever" tricks that should be simplified?
- Could this be done in fewer lines? (1000 lines where 100 suffice is a failure)
- Are abstractions earning their complexity? (Don't generalize until the third use case)
- Would comments help clarify non-obvious intent? (But don't comment obvious code.)
- Are there dead code artifacts: no-op variables (
_unused), backwards-compat shims, or// removedcomments? - Is a new conditional bolted onto an unrelated flow? That's a design smell, not a nit — push the logic into its own helper, state, or policy instead of tangling an existing path.
- Do repeated conditionals on the same shape appear? They signal a missing model or dispatcher. A "temporary" branch is usually permanent debt.
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.
- 10d ago First seen · 397 lines · 51 tokens per session scan A 8f3cabca581b
code-review-and-quality is a skill published in the GitHub repository addyosmani/agent-skills (93,102 stars, last pushed yesterday), licensed MIT. It adds 51 tokens to every session and 4,357 once invoked, about $0.0003 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 2026-08-30.
Other skills, from other repositories
doubt-driven-development
A development practice that puts an independent, fresh-context challenge in front of important coding decisions.
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.
code-review
Structured code review focusing on correctness, security, and maintainability. Correctness before style. Every reviewer comment must be actionable.
code-review-and-quality
Conducts multi-axis code review with hard rules against rubber-stamping and diff-only tunnel vision. Use before merging any change, whether written by yourself, another agent, or a human. Triggers on "review this", "is this ready to merge", or any completed implementation awaiting approval.
doubt-driven-development
Subjects every non-trivial decision to a fresh-context adversarial review before it stands. Use when correctness matters more than speed, when working in unfamiliar code, when stakes are high (production, security-sensitive logic, irreversible operations), or any time a confident output would be cheaper to verify now…