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 mamahoos/dot-files --skill code-review-and-qualitygit clone --depth 1 https://github.com/mamahoos/dot-filesWrote 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/mamahoos/dot-files/code-review-and-quality)<a href="https://agentmods.dev/skills/mamahoos/dot-files/code-review-and-quality"><img src="https://agentmods.dev/badge/skills/mamahoos/dot-files/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/mamahoos/dot-files/code-review-and-quality"><img src="https://agentmods.dev/badge/skills/mamahoos/dot-files/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 | $0.00071 | $0.04460 |
| Opus 5.5 | $0.00028 | $0.01784 |
| Sonnet 5.5 | $0.00014 | $0.00892 |
| Haiku 4.5 | $0.00007 | $0.00446 |
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 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.
This is a copy
97% identical to code-review-and-quality — 1 line 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 — 400 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.
- 22d ago Changed · +2 lines ee1e4914aab5
- 28d ago Changed · +20 tokens per session bb31ef41cafa
- 1mo ago First seen · 398 lines · 51 tokens per session scan A cdd241bc1bd7
code-review-and-quality is a skill published in the GitHub repository mamahoos/dot-files (5 stars, last pushed 4d ago), licensed MIT. It adds 71 tokens to every session and 4,460 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 97% identical to code-review-and-quality, differing in 1 line, and is treated as a copy.
Other skills, from other repositories
codebase-audit
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pr-style
This skill should be used when creating or editing a GitHub pull request title or description, regardless of tool (gh CLI, GitHub MCP tools, API). Defines PR title format and body format with Why/What/Notes sections.
gh-pr
This skill should be used when creating a GitHub pull request via gh pr create. Covers the gh CLI mechanics; PR title and body conventions come from the pr-style skill.
self-review
Deliberate end-to-end review pass over a completed change, applying the laziness ladder. Invoke when the user asks for a review, or when orchestrating one. Not a routine step after every edit.
pr-grooming
Use when the user wants to groom, triage, or clean up the open pull requests of a repo: "groom the PRs", "review the open PRs", "which drafts are stale", "close old draft PRs", "rebase the dependabot PRs", "are the open PRs still mergeable", "refresh that old bugfix PR", or a periodic PR review — even when they do not…
explain-changes
Explain how the code on the current branch works, as an HTML page opened in the browser, written so someone can understand the change and review it. Use when asked to explain a branch, explain these changes, walk me through this code, help me review this, or explain what an agent just did. Most useful when someone…