Borrowing it
Nothing to install: this file belongs to shenjingnan/home-mcp. 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/shenjingnan/home-mcp/main/.claude/commands/gen-analyze.mdgit clone --depth 1 https://github.com/shenjingnan/home-mcpWrote 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/commands/shenjingnan/home-mcp/gen-analyze)<a href="https://agentmods.dev/commands/shenjingnan/home-mcp/gen-analyze"><img src="https://agentmods.dev/badge/commands/shenjingnan/home-mcp/gen-analyze/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/commands/shenjingnan/home-mcp/gen-analyze"><img src="https://agentmods.dev/badge/commands/shenjingnan/home-mcp/gen-analyze.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 | $0.00002 | $0.01016 |
| Opus 5.5 | $0.00001 | $0.00406 |
| Sonnet 5.5 | $0.00000 | $0.00203 |
| Haiku 4.5 | $0.00000 | $0.00102 |
Grade A, and why
gen-analyze 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.
What it actually says
问题分析
现在我有一个问题,问题描述如下:
$1
分析目标
我希望你能帮我针对这个问题进行全面、深入、客观的分析。请按照以下步骤完成分析工作:
第一步:理解问题和收集信息
-
仔细阅读问题描述:
- 提取核心问题和关键需求
- 识别问题的边界和范围
- 明确问题涉及的技术领域和业务场景
-
收集相关代码和文档:
- 查找与问题相关的源代码文件
- 阅读相关的配置文件和文档
- 了解项目的整体架构和技术栈
- 检查是否有类似问题的历史记录或已有分析
-
了解当前实现:
- 分析现有代码的实现方式
- 理解当前的数据流和业务逻辑
- 识别现有的设计模式和技术选型
第二步:进行深度分析
请从以下维度进行全面分析:
1. 现状分析
- 当前实现的详细描述
- 现有方案的优势和不足
- 存在的问题和痛点
- 性能、可维护性、可扩展性等方面的评估
2. 架构分析
- 当前架构设计概览(使用 Mermaid 图表展示)
- 各模块之间的关系和依赖
- 数据流和控制流分析
- 架构的合理性评估
3. 技术方案对比(如适用)
- 列举可能的解决方案
- 对每个方案进行详细分析(优势、劣势、适用场景)
- 使用表格进行对比
- 从性能、复杂度、兼容性、维护成本等多角度评估
4. 风险评估
- 识别潜在的技术风险
- 评估实施难度和成本
- 考虑兼容性和迁移成本
- 分析对现有系统的影响
5. 最佳实践对照
- 业界相关领域的最佳实践
- 是否符合设计原则(SOLID、DRY 等)
- 代码质量和工程规范
- 可测试性和可维护性考量
第三步:形成分析结论
分析报告要求
-
内容要求:
- 保持中立、客观、冷静的分析态度
- 使用数据和事实支撑观点,避免主观臆断
- 展现专业工程师的技术素养
- 结论要有理有据,逻辑清晰
-
格式要求:
- 使用 Markdown 格式编写
- 需要时使用 Mermaid 绘制架构图、流程图、时序图等
- 使用表格进行方案对比
- 使用代码块展示关键代码片段
- 合理使用标题层级组织内容
-
文件要求:
- 分析报告存放在项目根目录
- 文件名格式:
{主题}-{分析类型}.md(例如:BestMCP-架构分析报告.md) - 文件名要清晰表达分析内容
-
必须包含的章节:
- 概述:问题背景和分析目的
- 当前状态分析:详细描述现状
- 架构分析:技术架构和设计分析
- 问题剖析:深入分析核心问题
- 方案对比(如适用):多种解决方案的详细对比
- 风险评估:潜在风险和注意事项
- 结论与建议:明确的分析结论和后续建议
注意事项
- ✅ 基于项目实际代码和配置进行分析
- ✅ 使用具体的代码示例和数据支撑观点
- ✅ 考虑项目的实际情况和约束条件
- ✅ 分析要全面,但要聚焦核心问题
- ❌ 不要脱离实际代码进行纸上谈兵
- ❌ 不要添加个人偏见和主观判断
- ❌ 不要忽略边界情况和异常场景
完成后
请在完成分析报告后:
- 告知分析报告的完整文件名
- 简要总结核心发现和建议
- 列出需要关注的关键问题
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 · 121 lines · 2 tokens per session scan A 9eb2a6bcddee
gen-analyze is a command published in the GitHub repository shenjingnan/home-mcp (23 stars, last pushed 9mo ago), licensed MIT. It adds 2 tokens to every session and 1,016 once invoked, about $0.0000 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 2026-08-30.
gen-analyze compared with commands from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| gen-analyzeshenjingnan/home-mcp | Command | 23 | 9mo ago | MIT | A | 2 | Claude Code |
| checklistgithub/spec-kit | Command | 148k | yesterday | MIT | A | 13 | Claude Code |
| clarifygithub/spec-kit | Command | 148k | yesterday | MIT | A | 27 | Claude Code |
| specifygithub/spec-kit | Command | 148k | yesterday | MIT | A | 13 | Claude Code |
| analyzegithub/spec-kit | Command | 148k | yesterday | MIT | A | 26 | Claude Code |
| convergegithub/spec-kit | Command | 148k | yesterday | MIT | A | 35 | Claude Code |
| implementgithub/spec-kit | Command | 148k | yesterday | MIT | A | 14 | Claude Code |