| name | deep-research |
| description | Structured deep research workflow with human-in-the-loop control. Use /research to generate research outline, /research-deep for parallel web search across items, /research-report to compile markdown reports. Supports academic research, benchmark research, technology selection, market analysis, and due diligence. Triggers: 'deep research', 'research topic', 'benchmark comparison', 'technology survey', 'market analysis'. Requires: WebSearch capability. |
| description_zh | 结构化深度调研工作流，支持大纲生成、并行搜索、报告输出 |
| description_en | Structured deep research workflow: outline, parallel search, report generation |
| version | 1.0.0 |
| homepage | https://github.com/Weizhena/Deep-Research-skills |
| license | MIT |
| allowed-tools | Read, Write, Glob, WebSearch, Task, AskUserQuestion |
Deep Research — 结构化深度调研工作流
基于 Deep-Research-skills 项目，提供人机协作的结构化调研能力。
核心命令
| 命令 | 说明 |
|---|
/research <topic> | 初步调研，生成 outline.yaml + fields.yaml |
/research-deep | 并行深度搜索，逐项收集数据 |
/research-report | 汇总生成 Markdown 报告 |
/research-add-items | 追加调研条目 |
/research-add-fields | 追加调研字段 |
工作流程
/research "AI Agent 2025"
↓ 生成大纲（items + fields）
↓ 用户确认/修改
/research-deep
↓ 并行 web-search-agent 逐项搜索
↓ 结果写入 results/
/research-report
↓ 汇总为 report.md
适用场景
- 学术调研：论文综述、Benchmark 对比
- 技术选型：框架评估、工具对比
- 市场调研：竞品分析、行业趋势
- 尽职调查：公司研究、投资分析
目录结构
deep-research/
├── research/SKILL.md # /research 命令（中文版）
├── research-deep/SKILL.md # /research-deep 命令
├── research-report/SKILL.md # /research-report 命令
├── research-add-items/SKILL.md
├── research-add-fields/SKILL.md
├── research-en/ # 英文版本
│ ├── research/SKILL.md
│ ├── research-deep/SKILL.md
│ ├── research-report/SKILL.md
│ ├── research-add-items/SKILL.md
│ └── research-add-fields/SKILL.md
└── agents/ # 搜索代理
├── web-search-agent.md
└── web-search-modules/ # 搜索策略模块
输出示例
{topic_slug}/
├── outline.yaml # 调研条目 + 执行配置
├── fields.yaml # 字段定义
├── results/ # 逐项搜索结果
│ ├── item_1.yaml
│ ├── item_2.yaml
│ └── ...
└── report.md # 最终报告
致谢
- 作者：Weizhena
- 灵感：RhinoInsight — Improving Deep Research through Control Mechanisms for Model Behavior and Context
