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.
git clone --depth 1 https://github.com/bestcarly/opc-coding-guideWrote 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/rules/bestcarly/opc-coding-guide/multi-model-review)<a href="https://agentmods.dev/rules/bestcarly/opc-coding-guide/multi-model-review"><img src="https://agentmods.dev/badge/rules/bestcarly/opc-coding-guide/multi-model-review/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/rules/bestcarly/opc-coding-guide/multi-model-review"><img src="https://agentmods.dev/badge/rules/bestcarly/opc-coding-guide/multi-model-review.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 | $0.01858 | $0.01858 |
| Opus 5.5 | $0.00743 | $0.00743 |
| Sonnet 5.5 | $0.00372 | $0.00372 |
| Haiku 4.5 | $0.00186 | $0.00186 |
Grade A, and why
multi-model-review 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 2mo 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.
How it starts
The opening of the file, as written. The whole thing — 275 lines — stays where its author put it; the contents beside it link to each section on GitHub.
多模型审查规则（2026 年版）
补充人：墨铃 (Mori)
补充日期：2026-02-28
参考章节：第十一章 11.2 节
适用范围
以下代码必须进行多模型审查：
- 核心业务逻辑：支付、订单、用户管理
- 安全敏感代码：认证、授权、加密、数据处理
- 公共库和框架：被多处引用的模块
- 性能关键代码：高频调用、大数据处理
审查流程
1. 开发者完成代码并自测
↓
2. 运行模型 A 审查（Claude Opus 4.5）
↓
3. 运行模型 B 审查（GPT-5.3-Codex）
↓
4. 运行安全扫描（Claude Code Security）
↓
5. 对比分析，生成综合报告
↓
6. 人工审查 Critical/High 问题
↓
7. 修复问题
↓
8. 重新验证
↓
9. 合并代码
模型分工
| 模型 | 角色 | 特长 | 超时配置 |
|---|---|---|---|
| Claude Opus 4.5 | 深度审查 | 架构分析、边界条件、可维护性 | 300s |
| GPT-5.3-Codex | 快速扫描 | 代码规范、性能、测试覆盖 | 180s |
| Claude Code Security | 安全扫描 | 漏洞检测、合规检查 | 240s |
审查维度
代码质量
- 命名规范
- 函数长度（< 50 行）
- 圈复杂度（< 10）
- 重复代码检测
- 注释完整性
功能正确
- 需求覆盖
- 边界条件
- 异常处理
- 错误恢复
性能
- 时间复杂度
- 空间复杂度
- 数据库查询优化
- 缓存策略
安全
- 输入验证
- 认证授权
- 数据加密
- 敏感信息泄露
可维护性
- 模块化
- 依赖管理
- 测试覆盖
- 文档完整
质量门槛
代码必须满足以下条件才能合并：
| 指标 | 门槛 | 说明 |
|---|---|---|
| 总体评分 | ≥ 8/10 | 综合评估 |
| Critical 问题 | 0 个 | 必须全部修复 |
| High 问题 | ≤ 2 个 | 修复或记录风险 |
| 测试覆盖率 | ≥ 80% | 核心模块 ≥ 90% |
| 安全扫描 | 通过 | 无 Critical/High |
提示词模板
模型 A（Claude）审查提示词
# Role: 资深代码审查专家
## Profile
- 15 年后端开发经验
- 精通 TypeScript/Node.js/Python
- 专长：架构设计、边界条件、可维护性
## Goals
对代码进行深度审查，发现潜在问题
## Workflow
1. 理解代码意图和上下文
2. 检查架构和设计模式
3. 分析边界条件和异常处理
4. 评估可维护性和扩展性
5. 提出改进建议
## Input
- 代码：[文件路径或代码块]
- 上下文：[相关文档/需求]
- 重点：[安全/性能/可维护性]
## Output Format
### 审查报告
#### 概览
- 文件：[文件名]
- 评分：[X/10]
- 总结：[一句话总结]
#### 问题列表
| 序号 | 类型 | 位置 | 严重程度 | 描述 | 建议 |
|------|------|------|----------|------|------|
| 1 | 边界条件 | auth.ts:45 | Medium | 未处理空值 | 添加空值检查 |
#### 优点
- [列出代码优点]
#### 改进建议
- [列出改进建议]
模型 B（Codex）审查提示词
# Role: 代码质量工程师
## Profile
- 10 年全栈开发经验
- 精通代码规范和最佳实践
- 专长：性能优化、测试覆盖、代码规范
## Goals
快速扫描代码质量问题
## Workflow
1. 检查代码规范
2. 分析性能瓶颈
3. 评估测试覆盖
4. 检测重复代码
5. 提出优化建议
## Input
- 代码：[文件路径或代码块]
- 规范：[编码规范文档]
## Output Format
### 快速扫描报告
#### 评分
- 代码规范：[X/10]
- 性能：[X/10]
- 测试覆盖：[X/10]
- 总体：[X/10]
#### 问题列表
| 序号 | 类型 | 位置 | 严重程度 | 描述 |
|------|------|------|----------|------|
| 1 | 性能 | user.ts:120 | High | N+1 查询问题 |
#### 建议修复
[修复代码示例]
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.
- 2mo ago First seen · 275 lines · 1,858 tokens per session scan A f16956b7ad15
multi-model-review is a cursor rule published in the GitHub repository bestcarly/opc-coding-guide (7 stars, last pushed 7mo ago), licensed MIT. It adds 1,858 tokens to every session, about $0.0074 per session on Opus 5.5. 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 2026-08-31.
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