code-quality-check

A rule set for reviewing code quality across multiple programming languages and common configuration formats.

In plain words
What is it for?
Use it to run quality checks, limit them by language or severity, generate reports, establish a baseline, or apply fixes where supported.
Why use it?
It checks changed code for maintainability, security risks, performance issues, coding practices, and test quality before review or commit.

Cursor rule

Install

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.

agentmods
npx agentmods add rules/mr-chen-05/rules-2.1-optimized/code-quality-check
Clone the repo
git clone --depth 1 https://github.com/Mr-chen-05/rules-2.1-optimized
Per session 5,010 This file is loaded in full into every session.
When invoked 5,010 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.05010 $0.05010
Opus 5 $0.02505 $0.02505
Sonnet 5 $0.01002 $0.01002
Haiku 4.5 $0.00501 $0.00501

Measured 2d ago against content hash 2df12ffb8620, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

code-quality-check 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 2d 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.

project-rules/code-quality-check.mdc · 689 lines

How it starts

The opening of the file, as written. The whole thing — 689 lines — stays where its author put it; the contents beside it link to each section on GitHub.

🔍 Code Quality Check - 智能代码质量检查

AI驱动的跨语言代码质量检查系统,集成智能分析引擎、MCP工具自动化和超级大脑系统推荐。

🧠 AI Intelligence Core - AI智能核心

智能激活条件

自动激活场景:
  - 检测到代码文件变更需要质量检查
  - 用户执行 "/quality-check" 命令
  - commit工作流提交前自动触发(/commit 或 /commit --fast;支持 /commit-fast 别名)
  - 超级大脑系统推荐质量检查
  - 项目进入代码审查阶段

智能分析维度:
  - 代码复杂度和可维护性 (30%)
  - 安全漏洞和潜在风险 (25%)
  - 性能问题和优化机会 (20%)
  - 代码规范和最佳实践 (15%)
  - 测试覆盖率和质量 (10%)

🚀 Commands - 智能命令

  • /quality-check - AI智能质量检查(推荐)
  • /quality-check --language <lang> - 指定语言检查
  • /quality-check --severity <level> - 指定严重级别 (critical/high/medium/low)
  • /quality-check --fix - 自动修复可修复的问题
  • /quality-check --report - 生成详细质量报告
  • /quality-check --baseline - 建立质量基线

✨ AI-Powered Features - AI驱动功能

🤖 智能代码分析引擎

多语言支持:
  前端语言:
    - JavaScript/TypeScript (ES6+, React, Vue, Angular)
    - HTML5/CSS3 (响应式设计, 可访问性)
    - SCSS/SASS/Less (预处理器优化)

  后端语言:
    - Python (Django, Flask, FastAPI)
    - Node.js (Express, Koa, NestJS)
    - Java (Spring Boot, Maven, Gradle)
    - C# (.NET Core, ASP.NET)
    - Go (Gin, Echo, 微服务)

  数据库和配置:
    - SQL (MySQL, PostgreSQL, SQLite)
    - NoSQL (MongoDB, Redis)
    - YAML/JSON/XML 配置文件
    - Docker/Kubernetes 配置

智能分析能力:
  - 语法和语义分析
  - 代码复杂度计算
  - 安全漏洞扫描
  - 性能瓶颈识别
  - 代码异味检测
  - 依赖关系分析

🔧 MCP工具智能编排

工具链集成:
  代码分析工具:
    - ESLint/Prettier (JavaScript/TypeScript)
    - Pylint/Black (Python)
    - SonarQube (多语言静态分析)
    - CodeQL (安全分析)
    - Bandit (Python安全扫描)

  性能分析工具:
    - Lighthouse (前端性能)
    - Profiler (后端性能)
    - Memory Analyzer (内存分析)
    - Load Testing (负载测试)

  自动化修复:
    - 代码格式化自动修复
    - 简单语法错误修复
    - 导入语句优化
    - 代码风格统一

📋 Quality Check Categories - 质量检查分类

🔴 Critical Issues - 致命问题

安全漏洞:
  - SQL注入风险
  - XSS跨站脚本攻击
  - CSRF跨站请求伪造
  - 敏感信息泄露
  - 不安全的加密实现

架构问题:
  - 循环依赖
  - 紧耦合设计
  - 单点故障
  - 资源泄露
  - 死锁风险

🟠 High Priority - 高优先级

性能问题:
  - 内存泄露
  - 无限循环
  - 低效算法
  - 数据库N+1查询
  - 大文件处理问题

可维护性:
  - 代码重复率过高
  - 函数复杂度过高
  - 类职责不清
  - 命名不规范
  - 缺少文档注释

Read the full file on GitHub · 689 lines

Changes

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.

  1. 2d ago First seen · 689 lines · 5,010 tokens per session scan A 2df12ffb8620

Subscribe to this mod's changes

code-quality-check is a cursor rule published in the GitHub repository Mr-chen-05/rules-2.1-optimized (172 stars, last pushed 9mo ago), licensed MIT. It adds 5,010 tokens to every session, about $0.0250 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.