analyze-issue

A set of rules and commands for analyzing GitHub issues and turning them into implementation specifications. GitHub issues are tracked bug reports, feature requests, and other development tasks.

In plain words
What is it for?
Use it to classify issues, review requirements and constraints, identify affected modules, define interfaces and data structures, plan testing, and assess risks and effort.
Why use it?
It gives developers a structured way to understand an issue, inspect the relevant code, plan a fix, choose tests, and estimate the work.

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/analyze-issue
Clone the repo
git clone --depth 1 https://github.com/Mr-chen-05/rules-2.1-optimized
Per session 0 Nothing until a file matches its globs; then the whole rule loads.
When invoked 1,444 The whole file, excluding the scripts and references it only reads on demand.
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 $0.00000 $0.01444
Opus 5 $0.00000 $0.00722
Sonnet 5 $0.00000 $0.00289
Haiku 4.5 $0.00000 $0.00144

Measured 3d ago against content hash f23c34b6e6ce, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

analyze-issue 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 3d 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/analyze-issue.mdc · 185 lines

How it starts

The opening of the file, as written. The whole thing — 185 lines — stays where its author put it; the contents beside it link to each section on GitHub.

🔍 Issue Analysis - 问题分析

分析GitHub问题并创建详细的实现规范。

🚀 Commands - 命令

  • /analyze-issue - 分析GitHub问题
  • /issue-spec - 创建实现规范
  • /estimate - 评估工作量

🧠 前置步骤:Context7 知识预载(修复/新项目前置)

  • 触发时机:开始 /analyze-issue 前,问题类型为 Bug/错误/异常 或 新功能/新项目分析
  • 执行:
    • 使用 Context7 在 src、docs、tests、config、README.*、architecture、api 目录检索相关材料(错误堆栈、模块、接口、约束、历史决策)
    • 质量阈值:至少 5 个高相关片段或覆盖 3 类关键材料;评分 ≥ 0.65;超时 60s
    • 回退:Context7 → 代码检索(search_codebase/search_by_regex)→ 文件系统读取
    • 记录与确认:将“知识预载摘要”写入 project.context.md 的 Pinned,并通过增强反馈机制确认后继续
  • 跳过条件:纯文档/注释、打印文案微调、单文件小范围变量改名等轻量变更

📋 Process - 分析流程

1. 🔍 问题理解 (Issue Understanding)

  • 仔细阅读问题描述和评论
  • 识别核心需求和约束条件
  • 理解用户期望和使用场景
  • 转换条件:问题理解清晰,需求明确

2. 📊 技术分析 (Technical Analysis)

  • 分析现有代码库结构
  • 识别相关模块和依赖
  • 评估技术可行性
  • 转换条件:技术方案可行,风险可控

3. 📝 实现规范 (Implementation Spec)

  • 创建详细的实现计划
  • 定义接口和数据结构
  • 规划测试策略
  • 转换条件:规范完整,可执行性强

4. ⏱️ 工作量评估 (Effort Estimation)

  • 评估开发时间
  • 识别潜在风险
  • 制定里程碑计划
  • 转换条件:评估合理,计划可行

🛠️ Analysis Framework - 分析框架

Issue Classification - 问题分类

  • Bug 🐛 - 功能缺陷
  • Feature ✨ - 新功能需求
  • Enhancement ⚡ - 功能改进
  • Documentation 📝 - 文档相关
  • Performance 🚀 - 性能优化
  • Security 🔒 - 安全问题

Priority Assessment - 优先级评估

  • Critical 🔴 - 阻塞性问题
  • High 🟠 - 重要功能
  • Medium 🟡 - 一般需求
  • Low 🟢 - 优化建议

Complexity Analysis - 复杂度分析

  • Simple - 1-2天
  • Medium - 3-5天
  • Complex - 1-2周
  • Epic - 2周以上

📋 Implementation Template - 实现模板

问题分析报告

## 问题分析

### 核心需求
- [ ] 需求1:描述
- [ ] 需求2:描述

### 技术要求
- [ ] 技术要求1
- [ ] 技术要求2

### 约束条件
- [ ] 约束1
- [ ] 约束2

## 实现方案

### 架构设计
- 模块结构
- 数据流设计
- 接口定义

### 实现步骤
1. [ ] 步骤1
2. [ ] 步骤2
3. [ ] 步骤3

### 测试策略
- [ ] 单元测试
- [ ] 集成测试
- [ ] 用户验收测试

## 工作量评估

- **预估时间**:X天
- **风险等级**:低/中/高
- **依赖项**:列出依赖

✅ Best Practices - 最佳实践

分析原则

  • 全面性 - 考虑所有相关因素
  • 准确性 - 基于事实和数据
  • 可行性 - 方案切实可行
  • 可测试性 - 结果可验证

沟通策略

  • 及时反馈 - 定期更新进展
  • 主动澄清 - 遇到歧义及时确认
  • 文档记录 - 重要决策要记录
  • 风险预警 - 提前识别和沟通风险

🔧 Tools Integration - 工具集成

Read the full file on GitHub · 185 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. 3d ago First seen · 185 lines · 0 tokens per session scan A f23c34b6e6ce

Subscribe to this mod's changes

analyze-issue 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 costs nothing until one of its globs matches a file; then it loads 1,444 tokens. 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.