docs: make workflow examples beginner-friendly

- Replace raw YAML/JSON with plain language explanations
- Add "What happens" and "You get" for each phase
- More intuitive for newcomers

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
jilinchen
2026-01-07 02:06:03 +08:00
co-authored by Claude Opus 4.5
parent 013cc823b6
commit 38e0350f18
2 changed files with 20 additions and 58 deletions
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@@ -37,50 +37,31 @@ cp agents/web-search-agent.md ~/.claude/agents/
## Workflow & Example ## Workflow & Example
> Example: Researching "AI Agent Demo 2025" > **Example**: Researching "AI Agent Demo 2025"
### Phase 1: Generate Outline ### Phase 1: Generate Outline
``` ```
run /research AI Agent Demo 2025 run /research AI Agent Demo 2025
``` ```
**Output:** `ai-agent-demo/outline.yaml` 💡 **What happens**: Tell it your topic → It creates a research list for you
```yaml
topic: "AI Agent Demo & Review (2025.9-2025.12)" **You get**: A list of 17 AI Agents to research (ChatGPT Agent, Claude Computer Use, Cursor, etc.) + what info to collect for each
items:
- name: "ChatGPT Agent"
category: "Browser Agent"
brief: "OpenAI unified Agent, released July 2025"
- name: "Claude Computer Use"
category: "Desktop Agent"
brief: "Anthropic desktop control Agent"
# ... 15 more items
```
### Phase 2: Deep Research ### Phase 2: Deep Research
``` ```
run /research/deep run /research/deep
``` ```
**Output:** `ai-agent-demo/results/ChatGPT_Agent.json` 💡 **What happens**: AI automatically searches the web for each item, one by one
```json
{ **You get**: Detailed info for each Agent (company, release date, pricing, tech specs, reviews...)
"basic_info": {
"name": "ChatGPT Agent",
"company": "OpenAI",
"release_date": "2025-07-17",
"pricing": "Pro $200/mo, Plus $20/mo"
},
"tech_specs": {
"underlying_model": "GPT-5 series",
"agent_type": "Unified autonomous Agent"
}
}
```
### Phase 3: Generate Report ### Phase 3: Generate Report
``` ```
run /research/report run /research/report
``` ```
**Output:** `ai-agent-demo/report.md` - Markdown report with TOC and all items 💡 **What happens**: All data → One organized report
**You get**: `report.md` - A complete markdown report with table of contents, ready to read or share
## References ## References
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## 工作流 & 示例 ## 工作流 & 示例
> 示例:调研 "AI Agent Demo 2025" > **示例**:调研 "AI Agent Demo 2025"
### 阶段1:生成Outline ### 阶段1:生成Outline
``` ```
run /research AI Agent Demo 2025 run /research AI Agent Demo 2025
``` ```
**输出:** `ai-agent-demo/outline.yaml` 💡 **发生了什么**:告诉它你要研究什么 → 它帮你列出调研清单
```yaml
topic: "AI Agent Demo & 测评 (2025.9-2025.12)" **你会得到**17个待调研的AI Agent清单(ChatGPT Agent、Claude Computer Use、Cursor等)+ 每个要收集哪些信息
items:
- name: "ChatGPT Agent"
category: "浏览器Agent"
brief: "OpenAI统一Agent2025年7月发布"
- name: "Claude Computer Use"
category: "桌面Agent"
brief: "Anthropic桌面操控Agent"
# ... 另外15个items
```
### 阶段2:深度调研 ### 阶段2:深度调研
``` ```
run /research/deep run /research/deep
``` ```
**输出:** `ai-agent-demo/results/ChatGPT_Agent.json` 💡 **发生了什么**:AI自动上网搜索每个item的详细信息,逐个完成
```json
{ **你会得到**:每个Agent的详细资料(公司、发布日期、定价、技术规格、用户评价...)
"basic_info": {
"name": "ChatGPT Agent",
"company": "OpenAI",
"release_date": "2025-07-17",
"pricing": "Pro $200/月, Plus $20/月"
},
"tech_specs": {
"underlying_model": "GPT-5系列",
"agent_type": "统一型自主Agent"
}
}
```
### 阶段3:生成报告 ### 阶段3:生成报告
``` ```
run /research/report run /research/report
``` ```
**输出:** `ai-agent-demo/report.md` - 带目录和所有item的Markdown报告 💡 **发生了什么**:所有数据 → 一份整理好的报告
**你会得到**`report.md` - 带目录的完整Markdown报告,可直接阅读或分享
## 参考文献 ## 参考文献