Borrowing it
Nothing to install: this file belongs to jmxt3/gitscape.ai. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/jmxt3/gitscape.ai/main/.agents/skills/code-review-and-quality/SKILL.mdgit clone --depth 1 https://github.com/jmxt3/gitscape.aiWrote 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/jmxt3/gitscape.ai/code-review-and-quality)<a href="https://agentmods.dev/skills/jmxt3/gitscape.ai/code-review-and-quality"><img src="https://agentmods.dev/badge/skills/jmxt3/gitscape.ai/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/jmxt3/gitscape.ai/code-review-and-quality"><img src="https://agentmods.dev/badge/skills/jmxt3/gitscape.ai/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 | $0.00051 | $0.03040 |
| Opus 5 | $0.00026 | $0.01520 |
| Sonnet 5 | $0.00010 | $0.00608 |
| Haiku 4.5 | $0.00005 | $0.00304 |
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 9d 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
83% identical to code-review-and-quality — 57 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 — 348 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?
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.
- 9d ago First seen · 348 lines · 51 tokens per session scan A 7587de5eff9e
code-review-and-quality is a skill published in the GitHub repository jmxt3/gitscape.ai (33 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 51 tokens to every session and 3,040 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 83% identical to code-review-and-quality, differing in 57 lines, and is treated as a copy.
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Use when reviewing an incoming GitHub pull request — runs the multi-level (L1-L5) audit against the PR's real diff range, posts findings as one batched review (inline, summary, or local-only), offers the standard fix chain on NEEDSFIX, and optionally merges. The maintainer-side counterpart to /hyperflow:issue. Trigger…
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MindOS: local knowledge assistant & shared KB. Keeps decisions, notes, SOPs, debugging lessons, research findings, preferences across sessions/agents. Core: save notes, search KB, organize files, run workflows, review, append CSV, hand off context, distill lessons. NOT for app source or paths outside KB. Triggers…