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search-first

Research-before-coding workflow: systematically search existing solutions before custom implementation. Use when introducing new libraries, tools, or solving unfamiliar problems.

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研究优先工作流

编码前系统化搜索现有方案,做出 Adopt/Extend/Compose/Build 决策。

核心原则:不重复造轮子,但也不盲目引入依赖。

触发条件 | Trigger Conditions

  • /cc-best:lead 技术方案设计阶段
  • 需要引入新库/工具/框架时
  • 遇到"需要 X 功能"的需求时
  • 解决不熟悉的技术问题时

搜索流程 | Search Process

1. 并行搜索(限时 5-10 分钟)
   ├─ 包管理器(npm/PyPI/Maven 等,根据项目技术栈)
   ├─ MCP 服务器(如适用)
   ├─ GitHub/社区方案
   └─ 官方文档/API 参考

2. 方案评估
   ├─ 功能匹配度
   ├─ 维护活跃度(最近提交、issue 响应)
   ├─ 许可证兼容性
   └─ 依赖复杂度

3. 决策 + 记录
   ├─ 输出 Adopt/Extend/Compose/Build 决策
   ├─ 记录到 progress.md 决策表
   └─ 标注置信度

评估矩阵 | Decision Matrix

条件决策行动
精确匹配 + 活跃维护 + 兼容许可采用 (Adopt)直接安装使用
部分匹配 + 良好基础扩展 (Extend)安装 + 薄包装器适配
多个弱匹配组合 (Compose)组合 2-3 个小包
无合适方案构建 (Build)自研,但带着搜索知识

评估检查清单

- [ ] 功能是否满足核心需求(≥80%)
- [ ] 最近 6 个月内有提交
- [ ] 许可证与项目兼容(MIT/Apache/ISC 优先)
- [ ] 依赖数量合理(<20 direct deps)
- [ ] 有测试覆盖和文档
- [ ] 无已知安全漏洞

与角色工作流的集成 | Pipeline Integration

在 /cc-best:lead 工作流中,技术栈选型前自动触发:

PM(需求) → Lead(search-first → 方案设计) → Dev(实现)

集成方式

  1. Lead 角色:技术方案设计时,对每个新依赖执行 search-first
  2. Dev 角色:遇到"需要引入新工具"时,暂停编码执行 search-first
  3. Architect agent:架构决策中自动引用 search-first 结果

搜索策略 | Search Strategy

按场景选择搜索深度

场景搜索深度时间上限
已知成熟方案浅搜索2 分钟
常见功能需求标准搜索5 分钟
创新/罕见需求深度搜索10 分钟

搜索来源优先级

  1. 项目已有依赖(检查 package.json/go.mod 等)
  2. 项目技术栈生态的官方推荐
  3. 包管理器搜索(npm search / pip search 等)
  4. GitHub trending + awesome-xxx 列表
  5. WebSearch 通用搜索

决策记录模板 | Decision Template

### 搜索决策: [功能描述]

**搜索范围**: [npm/GitHub/WebSearch]
**候选方案**:

1. [方案A] - [优劣概述]
2. [方案B] - [优劣概述]

**决策**: [Adopt/Extend/Compose/Build] [方案名]
**理由**: [1-2 句]
**置信度**: [高/中/低]

最佳实践 | Best Practices

  1. 搜索有时间上限 — 超时用 MVP 方案,标记 TBD
  2. 不是每个工具都要搜索 — 区分"已知成熟方案"和"新需求"
  3. 检查维护状态 — star 多但 3 年未更新的比新库风险更高
  4. 考虑退出成本 — 深度耦合的依赖要慎重选择
  5. 记录搜索过程 — 即使决定 Build,也记录为什么不 Adopt

记住: 搜索不是目的,做出有依据的决策才是目的。5 分钟的搜索可以避免 5 天的重复造轮子。

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