Trigger methods
| User says | Action performed |
|---|---|
| "Start today's topic selection" | Complete process: collect→generate→review→save |
| "Today's AI hotspots" / "See what hotspots there are today" | Collect only: list today's hotspots, do not generate topics |
| "I have a topic" | Single analysis: user input→generate→review |
| "Recommend some good topics" | Quick recommendation: recommend 3-5 based on recent hotspots |
Mode 1: Today's AI hotspots (collect only)
When the user says "Today's AI hotspots", execute the following process:
Collection steps
Use WebSearch to search the following content in parallel:
# 1. AI博主实践分享
"Claude Code" OR "Cursor" tips tricks workflow 2026
# 2. 创业公司/新产品
Product Hunt AI tools launch 2026
# 3. 模型厂商动态
Anthropic Claude OR OpenAI ChatGPT update January 2026
# 4. AI Agent工作流
AI agent automation n8n workflow 2026
# 5. 社区讨论
Reddit ClaudeAI OR LocalLLaMA hot January 2026
# 6. 研究动态
AI research DeepMind OR Meta AI January 2026
Output format
## 今日AI热点 - MMDD
---
### 🧑💻 AI博主实践分享
1. **[内容摘要]**
- 作者：@用户名 / 博主名
- 原文：[文章标题](https://具体URL)
- 要点：一句话总结
---
### 🚀 创业公司/新产品
1. **[产品名]** - 一句话描述
- 原文：[Product Hunt](https://producthunt.com/posts/xxx)
- 热度：⬆️ N upvotes
---
### 🏢 模型厂商动态
1. **[更新内容]**
- 厂商：Anthropic / OpenAI / Google
- 原文：[官方博客](https://具体URL)
- 要点：关键变化
---
### 🔬 AI研究/学术
1. **[论文/博客标题]**
- 来源：DeepMind / Meta AI / arXiv
- 原文：[链接](https://具体URL)
- 要点：核心发现
---
### 💬 社区热议
1. **[讨论标题]**
- 来源：r/ClaudeAI / Hacker News
- 原文：[帖子链接](https://具体URL)
- 热度：⬆️ upvotes | 💬 comments
Key requirements
- Each hotspot must have an original link: not the main domain, but the specific article/post URL
- Organize by 5 categories: blogger sharing, new products, vendor updates, research, community
- Prioritize content with practical value
Mode 2: Complete topic selection process
When the user says "Start today's topic selection":
┌─────────────────────────────────────────────┐
│ 1. 采集热点（同模式一） │
│ 输出今日AI热点列表 │
└─────────────────┬───────────────────────────┘
▼
┌─────────────────────────────────────────────┐
│ 2. 筛选TOP10生成选题方案 │
│ 事件描述 + 核心角度 + 标题 + 写作方式 │
└─────────────────┬───────────────────────────┘
▼
┌─────────────────────────────────────────────┐
│ 3. 审核评分 │
│ 热度 + 独特角度 + 国内关注度 → 总分 │
└─────────────────┬───────────────────────────┘
▼
┌─────────────────────────────────────────────┐
│ 4. 输出结果 │
│ ✅通过：保存到选题库 │
│ ⚠️待优化：给出修改建议 │
│ ❌不通过：说明原因 │
└─────────────────────────────────────────────┘
Mode 3: Single topic analysis
When the user says "I have a topic":
- Ask for the topic content
- Search related hotspots to verify popularity
- Generate a complete topic plan
- Review and score
- Give optimization suggestions
Output location
/Users/ugreen/Documents/obsidian/选题库/每日选题/MMDD-选题名称.md
File naming example:0114-Claude-Code进阶技巧.md
Topic output template
# [选题标题]
**日期**：YYYY-MM-DD
**状态**：待写 / 写作中 / 已发布
**审核分数**：XX/100
## 事件描述
[一段话说清楚发生了什么]
## 核心角度
[为什么值得写，差异化在哪]
## 标题备选
1.
2.
3.
## 写作方式
[干货教程 / 产品体验 / 观点分享 / 新技术突破]
## 大纲
1.
2.
3.
## 素材链接
- [来源1标题](https://具体URL)
- [来源2标题](https://具体URL)
- [来源3标题](https://具体URL)
## 备注
[其他想法]
Quick commands
| Command | Description |
|---|---|
| "Continue" | Continue the process interrupted last time |
| "Skip" | Skip the current topic and look at the next one |
| "Save" | Directly save the current topic to the library |
| "Abandon" | Abandon the current topic |
| "Change angle" | Keep the hotspot and regenerate from a different angle |
| "Expand and write" | Start writing based on the topic |
Review standards
| Dimension | Weight | Scoring standard |
|---|---|---|
| Popularity | 30% | Social media discussion volume, search trends |
| Unique angle | 40% | Whether there is a differentiated perspective, not simple reposting |
| Domestic attention | 30% | Whether domestic users care about this topic |
Passing standard：
- ✅ 80 points or above: pass, save to the topic library
- ⚠️ 60-79 points: needs optimization, give revision suggestions
- ❌ Below 60 points: fail, explain the reason
Daily goals
- Collect: 50+ hotspots (5 categories)
- Generate: 10 topic plans
- Passed: 3-5 qualified topics
- Save: all passed topics are stored in the topic library