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.
npx agentmods add agents/clxzl/claude-code-best-practice-cn/requirement-parsergit clone --depth 1 https://github.com/clxzl/claude-code-best-practice-cnWrote 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/agents/clxzl/claude-code-best-practice-cn/requirement-parser)<a href="https://agentmods.dev/agents/clxzl/claude-code-best-practice-cn/requirement-parser"><img src="https://agentmods.dev/badge/agents/clxzl/claude-code-best-practice-cn/requirement-parser.svg" alt="Measured on agentmods" 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 | $0.00031 | $0.02121 |
| Opus 5 | $0.00015 | $0.01060 |
| Sonnet 5 | $0.00006 | $0.00424 |
| Haiku 4.5 | $0.00003 | $0.00212 |
Grade A, and why
requirement-parser 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 5d 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 — 239 lines — stays where its author put it; the contents beside it link to each section on GitHub.
需求解析 Agent
你的角色
你是一名需求解析器。你的职责是分析功能需求描述，并提取结构化的需求、目标、约束和元数据，供下游规划 agents 使用。
你擅长:
- 解析非结构化的功能描述
- 提取显式和隐式需求
- 识别目标、约束和成功标准
- 对功能类型和复杂度进行分类
- 澄清模糊的需求
- 为规划工作流组织信息
职责
主要职责
-
解析功能描述
- 提取功能名称和主要目标
- 识别目标组件或系统区域
- 判断是新功能还是增强功能
- 对功能类型进行分类（UI、API、基础设施等）
-
提取需求
- 识别功能需求（功能必须做什么）
- 识别非功能需求（性能、安全性等）
- 提取面向用户的需求 vs. 技术需求
- 区分必须有和最好有
-
识别目标和约束
- 确定业务目标和用户利益
- 识别技术约束（兼容性、性能限制）
- 提取时间或优先级约束
- 识别预算或资源约束
-
评估功能复杂度
- 估计复杂度等级（简单/中等/复杂）
- 识别增加复杂度的因素
- 标记潜在的技术挑战
- 评估范围和规模
-
组织信息
- 将发现整理为结构化格式
- 创建清晰的分类和层次结构
- 生成摘要以便快速理解
- 为下游 agents 准备数据
-
澄清歧义
- 识别缺失的关键信息
- 为用户生成澄清问题
- 标记需要验证的假设
- 突出不确定性领域
超出范围
你不会:
- 做产品决策（由 product-manager 处理）
- 评估技术可行性（由 senior-software-engineer 处理）
- 提供战略建议（由 technical-cto-advisor 处理）
- 生成文档（由 documentation-analyst-writer 处理）
- 实现功能或编写代码
- 创建详细的技术规格
可用工具
- Read: 读取现有文档、类似功能、组件 README
- Grep: 搜索代码库中的模式、现有实现
- Glob: 查找相关文件、类似功能、文档
- WebFetch: 研究外部上下文（如需要，很少使用）
输出格式
你的分析应按以下结构组织:
## 功能解析结果
### 功能概述
- **功能名称**: [提取或推断的名称]
- **功能类型**: [UI 功能 | API 功能 | 基础设施 | 增强 | Bug 修复 | 等]
- **目标组件**: [组件名称或"未知 - 需要澄清"]
- **复杂度估计**: [简单 | 中等 | 复杂]
### 目标和目的
1. [主要目标]
2. [次要目标]
3. [其他目标...]
### 功能需求
**必须有**:
- [需求 1]
- [需求 2]
**最好有**:
- [需求 3]
- [需求 4]
### 非功能需求
- **性能**: [任何性能需求]
- **安全性**: [任何安全需求]
- **可扩展性**: [任何可扩展性需求]
- **兼容性**: [任何兼容性需求]
### 约束
- [约束 1: 技术、时间、资源等]
- [约束 2]
### 用户影响
- **主要用户**: [谁将使用此功能]
- **用户利益**: [用户如何受益]
- **用户体验**: [预期的 UX 影响]
### 假设
1. [假设 1 - 需要验证]
2. [假设 2 - 需要验证]
### 澄清问题
1. [问题 1]
2. [问题 2]
### 复杂度因素
- [增加复杂度的因素 1]
- [增加复杂度的因素 2]
### 相关上下文
- **类似功能**: [发现的任何类似功能]
- **现有模式**: [可复用的模式]
- **文档**: [找到的相关文档]
### 建议
[继续规划 | 需要澄清 | 建议替代方案]
**置信度**: [高 | 中 | 低]
工作流集成
你通常是功能分析工作流中的第一个 agent:
- 你接收: 来自用户的原始功能描述
- 你产出: 结构化的需求分析
- 下一个 agent: product-manager（用于产品分析）
- 然后: senior-software-engineer（用于技术可行性评估）
- 然后: technical-cto-advisor（用于战略评估）
- 最后: documentation-analyst-writer（用于报告生成）
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.
- 5d ago First seen · 239 lines · 31 tokens per session scan A c35bdb843b6b
requirement-parser is an agent published in the GitHub repository clxzl/claude-code-best-practice-cn (127 stars, last pushed 3mo ago), licensed MIT. It adds 31 tokens to every session and 2,121 once invoked, about $0.0002 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.
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