Borrowing it
Nothing to install: this file belongs to zhangloveyan/backend-skill. 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/zhangloveyan/backend-skill/main/.claude/skills/proj-analyze-req/SKILL.mdgit clone --depth 1 https://github.com/zhangloveyan/backend-skillWrote 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/zhangloveyan/backend-skill/proj-analyze-req)<a href="https://agentmods.dev/skills/zhangloveyan/backend-skill/proj-analyze-req"><img src="https://agentmods.dev/badge/skills/zhangloveyan/backend-skill/proj-analyze-req/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/zhangloveyan/backend-skill/proj-analyze-req"><img src="https://agentmods.dev/badge/skills/zhangloveyan/backend-skill/proj-analyze-req.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 | $0.00036 | $0.02049 |
| Opus 5.5 | $0.00014 | $0.00820 |
| Sonnet 5.5 | $0.00007 | $0.00410 |
| Haiku 4.5 | $0.00004 | $0.00205 |
Grade A, and why
proj-analyze-req 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 — 227 lines — stays where its author put it; the contents beside it link to each section on GitHub.
需求分析(阶段一)
目标:理解用户真实需求,明确功能边界和业务逻辑,生成需求分析文档。 产出:需求分析文档(用户确认后进入阶段二)
执行流程
Step 0: 初始化任务文档 → Step 1: 需求理解 → Step 2: 规模判断 → Step 3: 需求澄清(与用户交互) → Step 4: 输出需求文档 → Step 5: 用户确认
Step 0: 初始化任务文档
在用户输入需求后,必须创建全流程任务文档骨架:
- 文件位置:
docs/task/{YYYYMMDD}_{中文模块名}_任务.md - 内容要求:仅记录流程状态、产物清单、上下文快照、下一步指令
- 禁止写细节:不写技术实现与字段设计
Step 1: 需求理解
从用户描述中初步提取:
| 维度 | 提取内容 |
|---|---|
| 功能目标 | 要实现什么功能 |
| 使用角色 | 谁来使用 |
| 涉及端 | Web后台/小程序/App/开放接口 |
| 涉及模块 | 影响哪些现有模块 |
| 关键操作 | 核心功能点 |
注意:此步骤仅做初步理解,禁止假设任何细节。
Step 2: 规模判断
| 规模 | 特征 | 后续流程 |
|---|---|---|
| 简单 | 改字段、加接口、改配置 | 可简化澄清,但仍需确认 |
| 中等 | 新模块、独立功能 | 标准流程 |
| 复杂 | 跨模块、架构调整、核心流程 | 完整流程,详细文档 |
判断依据:
- 涉及 1 个文件 → 简单
- 涉及 1 个模块(多文件) → 中等
- 涉及多个模块 → 复杂
Step 3: 需求澄清(必须执行)
3.1 必问问题清单
AI 必须向用户询问以下问题,根据需求复杂度选择性提问:
| 维度 | 问题 | 说明 |
|---|---|---|
| 功能范围 | 这个功能给谁用?Web端?移动端?都需要? | 明确端类型 |
| 用户角色 | 涉及哪些角色?各角色能做什么操作? | 明确权限边界 |
| 功能清单 | 具体需要哪些功能点? | 列表/详情/创建/编辑/删除/导出/审批... |
| 业务流程 | 主要业务流程是怎样的?有哪些状态流转? | 明确流程节点 |
| 业务规则 | 有哪些业务限制或校验规则? | 明确约束条件 |
| 数据要求 | 需要记录哪些信息/字段? | 明确数据结构 |
| 关联关系 | 与现有哪些模块有关联? | 明确依赖关系 |
| 参考资料 | 有没有参考产品或原型图? | 获取更多上下文 |
3.2 提问原则
- 先思考再提问 - 根据需求类型,预判可能涉及的细节点(如:是否多端、是否有状态流转、是否需要关联用户等)
- 一次性列出 - 将所有待确认问题整理后一次性提出,减少交互轮次
- 不要假设答案 - 不确定的必须问
- 追问细节 - 用户回答模糊时继续追问
- 确认理解 - 复述用户的回答确保理解正确
3.3 提问示例
我来帮您分析这个需求。为了准确理解,请回答以下问题:
**1. 功能范围**
- 这个功能给谁用?Web后台管理端?小程序端?还是都需要?
**2. 用户角色**
- 涉及哪些角色?各角色分别能做什么操作?
**3. 功能清单**
- 需要哪些具体功能?(如:列表查询、详情查看、新增、编辑、删除、导出...)
**4. 业务流程**
- 主要的业务流程是怎样的?
- 是否有状态流转?(如:待处理→处理中→已完成)
**5. 数据要求**
- 需要记录哪些信息/字段?
- 哪些是必填项?
请逐一回答,我会根据您的回答进一步澄清。
Step 4: 输出需求文档
在充分澄清后,使用模板输出需求分析文档。
模板文件:需求文档模板
保存位置:docs/req/{YYYYMMDD}_{中文模块名}_需求.md
同步更新任务文档:
- 将“需求分析”状态标记为进行中/已完成
- 在产物清单中记录需求文档路径
- 更新上下文快照与下一步指令
Step 5: 用户确认
5.1 确认话术
输出需求文档后,必须使用以下话术请求确认:
以上是我对需求的理解,请确认:
1. 功能范围是否完整?
2. 业务流程是否正确?
3. 是否有遗漏的功能点或业务规则?
确认后我将进入技术方案设计阶段(/proj-analyze-design)。
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 227 lines · 36 tokens per session scan A d04f2e122bce
proj-analyze-req is a skill published in the GitHub repository zhangloveyan/backend-skill (103 stars, last pushed 23d ago), licensed MIT. It adds 36 tokens to every session and 2,049 once invoked, about $0.0001 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.
proj-analyze-req compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| proj-analyze-reqzhangloveyan/backend-skill | Skill | 103 | 23d ago | MIT | A | 36 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |