By name: ai-products description: Curate AI product launches from Product Hunt, Hacker News, GitHub, and Techmeme. Use when user invokes /ai-products or when /start-my-day needs product launches.
AI Product Discovery
Fetch, deduplicate, and rank AI product launches from multiple sources.
Sources
| Source | URL | Notes |
|---|---|---|
| Product Hunt | https://www.producthunt.com/feed |
Filter for AI-related |
| Hacker News | https://hn.algolia.com/api/v1/search?tags=show_hn&numericFilters=created_at_i>TIMESTAMP |
Show HN posts, 24h window |
| GitHub Trending | https://mshibanami.github.io/GitHubTrendingRSS/daily/python.xml |
Python repos |
| Techmeme | https://techmeme.com/river |
Product announcements |
Workflow
Check cache: Look for
50_资源/产品发布/YYYY-MM/YYYY-MM-DD-摘要.md. If exists with today's date, return cached.Fetch sources: Use WebFetch on each. Extract product name, URL, description, and engagement metrics (votes/points/stars).
Filter: Keep only AI-related products (keywords: AI, ML, LLM, GPT, Claude, automation, agent, model).
Deduplicate: Same product across sources = merge. Keep best description, combine metrics, track all sources.
Rank by:
- AI relevance
- Engagement (normalize: PH votes/500, HN points/100, GH stars/1000)
- Content potential (tutorial-friendly, review-worthy, open source bonus)
- Recency and novelty
Generate digest: See TEMPLATE.md. Sections:
- 精选推荐 (3-5) with content angles
- LLM与AI模型
- 开发者工具
- 生产力与自动化
- 开源亮点
Save files:
50_资源/产品发布/YYYY-MM/YYYY-MM-DD-摘要.md50_资源/产品发布/YYYY-MM/原始数据/YYYY-MM-DD_ProductHunt-Raw.md50_资源/产品发布/YYYY-MM/原始数据/YYYY-MM-DD_HackerNews-Raw.md50_资源/产品发布/YYYY-MM/原始数据/YYYY-MM-DD_GitHub-Raw.md
Output Format
Manual invocation: Full digest with all sections.
From /start-my-day: Condensed list:
**产品发布机会 (5):**
- [产品名] - [内容角度] - [关键指标]
...
完整摘要: [[YYYY-MM-DD-摘要]]
Error Handling
- Source down: Continue with others, note in digest
- <2 sources available: Fall back to yesterday's archive
- Empty results: Create minimal digest noting "今日无新AI产品"
Content Angle Logic
- High engagement + tutorial-friendly: "教程机会"
- Novel + early stage: "抢先报道优势"
- Open source + complex: "深度分析"
- SaaS + practical: "工具评测"
- Similar to existing: "对比 vs [竞品]"