embodied-ai-news
聚合来自精选来源（机器人媒体、arXiv、公司博客）的公开可用的 Embodied AI 和机器人新闻。提供有关人形机器人、基础模型、硬件、部署和资金的结构化简报，并提供原始文章的直接链接。
安装 / 下载方式
TotalClaw CLI推荐
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curl -fsSL https://skills.taituai.com/api/skills/totalclaw%3Atotalclaw~hexavi8-embodied-ai-news/file -o hexavi8-embodied-ai-news.md# Embodied AI News Briefing
> Aggregates the latest Embodied AI & Robotics news from curated sources and delivers concise summaries with direct links. Covers the full stack: algorithms, hardware, simulation, deployment, funding, policy, and the China ecosystem.
## When to Use This Skill
Activate this skill when the user:
- Asks for embodied AI news, robot news, or humanoid robot updates
- Requests a daily/weekly/monthly robotics briefing
- Mentions wanting to know what's happening in embodied AI / robotics
- Asks about specific companies: Tesla Optimus, Figure, Unitree, AGIBOT, Boston Dynamics, etc.
- Asks about specific technologies: VLA models, diffusion policy, sim-to-real, dexterous manipulation
- Wants a summary of recent robotics research papers
- Asks about robotics funding, deployments, or supply chain
- Asks about simulation platforms, benchmarks, or datasets
- Asks about robotics policy, safety standards, or export controls
- Requests a monthly trend report or competitive analysis
- Says: "给我今天的具身智能资讯" (Give me today's embodied AI news)
- Says: "机器人行业有什么新动态" (What's new in the robot industry)
- Says: "最近有什么人形机器人的消息" (Any recent humanoid robot news)
- Says: "这个月的具身智能趋势报告" (This month's embodied AI trend report)
- Says: "embodied AI updates", "robot learning news", "humanoid robot news"
### Trigger Keywords
**English**: `embodied AI`, `humanoid robot`, `robot news`, `robotics update`, `robot learning`, `VLA model`, `diffusion policy`, `dexterous manipulation`, `sim-to-real`, `robot deployment`, `robotics funding`, `Figure AI`, `Tesla Optimus`, `Unitree`, `AGIBOT`, `Boston Dynamics`, `1X`, `Physical Intelligence`, `Skild AI`, `robot hand`, `quadruped robot`, `Isaac Sim`, `world model robot`, `robot benchmark`, `robot safety`, `robot regulation`, `monthly robot report`
**Chinese**: `具身智能`, `人形机器人`, `机器人资讯`, `灵巧操作`, `仿真到真实`, `机器人部署`, `宇树`, `智元`, `优必选`, `银河通用`, `傅利叶`, `机器人融资`, `灵巧手`, `四足机器人`, `机器人大模型`, `机器人月报`, `机器人安全`, `机器人政策`
---
## Reference Files
This skill relies on 5 companion reference files. Always consult them during execution:
```
📁 references/
├── 📰 news_sources.md — WHERE to find information (tiered source list)
├── 🔍 search_queries.md — HOW to search (query templates & recipes)
├── 📝 output_templates.md — WHAT format to output (6+ template variants)
├── 📊 taxonomy.md — SHARED LANGUAGE (categories, keywords, company list)
└── 🧭 workflow.md — WHEN and in what ORDER to execute (SOP for daily/weekly/monthly)
```
| File | When to Consult |
| --------------------- | --------------------------------------------------------------------------------------- |
| `news_sources.md` | Phase 1 — choosing which sites to fetch; selecting tier-appropriate sources |
| `search_queries.md` | Phase 1 — building search queries; selecting recipe by briefing type |
| `taxonomy.md` | Phase 3 — classifying stories; Phase 1 — looking up company aliases & tech terms |
| `output_templates.md` | Phase 5 — rendering final output; selecting template by user request |
| `workflow.md` | All Phases — orchestrating the end-to-end workflow; time budgeting; monthly maintenance |
### File Interconnection Map
```
┌─────────────────┐ ┌────────────────────┐ ┌───────────────┐ ┌──────────────────┐
│ search_queries │────▶ │ news_sources │────▶│ Classify & │────▶│ output_templates │
│ (discover) │ │ (browse & verify) │ │ Prioritize │ │ (generate) │
└─────────────────┘ └────────────────────┘ └───────────────┘ └──────────────────┘
▲ ▲
│ │
└────── taxonomy.md ─────┘
(shared vocabulary)
```
---
## Execution Workflow
### Phase 0: Determine Briefing Type & Time Scope
**Before any tool calls**, ask the user (if not already clear):
1. **Briefing Type**: Daily / Weekly / Monthly / Custom Topic?
2. **Time Scope**: Last 24 hours / Last 7 days / Last 30 days / Custom date range?
3. **Output Format**: Standard / Brief / Thread / Markdown Report / Presentation / Custom?
4. **Focus Area** (optional): All categories / Specific category (e.g., only hardware, only China ecosystem)?
**Default if user doesn't specify**:
- Type: Daily
- Scope: Last 24 hours
- Format: Standard
- Focus: All categories
**Map to workflow.md**:
- Daily → `workflow.md` Section "Daily Workflow"
- Weekly → `workflow.md` Section "Weekly Workflow"
- Monthly → `workflow.md` Section "Monthly Workflow"
---
### Phase 1: Information Gathering
Consult `workflow.md` for the appropriate recipe, then execute the corresponding steps from `search_queries.md` and `news_sources.md`.
#### Step 1.1: Execute Search Queries
**Tool**: `WebSearch` (or equivalent web search tool)
**Source**: `search_queries.md` → Select the appropriate recipe:
- Daily Briefing → Recipe A (5 queries)
- Weekly Roundup → Recipe B (8 queries)
- Monthly Deep Dive → Recipe C (12 queries)
- Custom Topic → Recipe D + user-specified filters
**Parameters**:
- `return_format`: markdown
- `with_images_summary`: false
- `timeout`: 20 seconds per source
- Fetch only from publicly accessible sources listed in `news_sources.md`
**Output**: A list of 20–50 URLs with headlines and snippets.
---
#### Step 1.2: Fetch Tier 1 Sources Directly
**Tool**: `mcp__web_reader__webReader`
**Source**: `news_sources.md` → Tier 1 section
Directly fetch the homepage or RSS feed of:
- The Robot Report
- IEEE Spectrum — Robotics
- TechCrunch — Robotics
- Robotics Business Review
- (Add others based on briefing type)
**Parameters**:
- `url`: [homepage URL from news_sources.md]
- `return_format`: markdown
- `with_images_summary`: false
- Process only URLs from verified sources in `news_sources.md`
**Output**: Recent headlines (last 24h / 7d / 30d based on scope).
---
#### Step 1.3: Fetch arXiv Papers
**Tool**: `mcp__arxiv__readURL` (if available) or `WebSearch` with arXiv-specific queries
**Source**: `search_queries.md` → Section "6. Academic Research (arXiv)"
Execute 2–3 arXiv queries:
```
cat:cs.RO AND ("embodied AI" OR "robot learning" OR "VLA") submittedDate:[today - 7d TO today]
```
**Output**: 5–10 recent papers with abstracts.
---
#### Step 1.4: Fetch Company Blogs & Official Announcements
**Tool**: `mcp__web_reader__webReader`
**Source**: `news_sources.md` → Tier 2 (Company Blogs) + Tier 4 (China Ecosystem)
Fetch from:
- Figure AI Blog
- Physical Intelligence Blog
- Tesla AI Blog
- Unitree Blog (Chinese + English)
- AGIBOT WeChat Official Account (if accessible)
- (Add others based on focus area)
**Fetch constraints**:
- Only process URLs from search results and sources listed in `news_sources.md`
- Skip content requiring authentication
- Timeout: 15 seconds per URL
**Output**: Recent announcements (last 7d / 30d based on scope).
---
### Phase 2: Content Extraction & Deduplication
For each fetched URL:
1. **Extract**:
- Headline
- Publication date
- Source name
- Summary (first 2–3 paragraphs or abstract)
- Key entities: companies, models, hardware platforms (use `taxonomy.md` for reference)
2. **Deduplicate**:
- If multiple sources cover the same story, keep the one with the most detail
- Merge information if they provide complementary details
3. **Discard**:
- Stories older than the time scope
- Irrelevant content (use `search_queries.md` Section 1.4 "Noise Exclusion Filter")
- Duplicate announcements
**Output**: A deduplicated list of 15–30 stories with extracted metadata.
---
### Phase 3: Classification & Prioritization
Consult `taxonomy.md` to classify each story.
#### Step 3.1: Assign Primary Category
Use `taxonomy.md` → Section "