search

# Search for Content Search for papers, projects, ecosystem players, or solutions on a specific topic. ## Usage ```text /search <topic> ``` ## Examples ```text /search JEPA /search robot foundation models /search digital twin open source /search Isaac ROS competitors /search Physical AI startups funding 2026 ``` ## Instructions When this command is invoked: 1. **Parse the topic** to understand what to search for 2. **Determine search strategy**: - For papers: Use WebSearch with arXiv and Google Scholar - For projects: Search GitHub via WebSearch - For ecosystem players/solutions: Search vendor blogs, TechCrunch, The Robot Report, Crunchbase - For general content: Multi-source search 3. **Execute searches**: - **arXiv + TechRxiv**: Search with topic keywords + filter last 3-6 months - **Google Scholar**: For applied/engineering papers - **GitHub**: Search repos matching topic with stars>10 - **Research blogs**: Research lab blogs (Meta AI, Google DeepMind, etc.) - **Industry sources**: TechCrunch, The Robot Report, IEEE Spectrum for startups and industry news - **Vendor pages**: Product documentation and developer portals - Use search queries from `research/tools/preferred-sources.md` 4. **Rank and filter results**: - Relevance to Physical AI platform intelligence - Recency (prefer last 6 months for papers) - Quality indicators (citations, stars, author reputation, deployment evidence) - Avoid duplicates already in research documents 5. **Present findings** to user: - Show top 5-10 results - Include: title, source, date, 1-sentence description - Format as numbered list for easy selection - Group by category: Papers, Projects, Ecosystem Players, Solutions 6. **Ask which to add**: "Which of these would you like me to add? (e.g., '1, 3, 5')" 7. **Add selected items** using the `/add` workflow for each ## Search Sources Priority 1. **arXiv + TechRxiv** - Research papers (foundational and applied) 2. **Google Scholar** - Applied/engineering papers, conference proceedings 3. **GitHub** - Open-source projects and implementations 4. **Industry news** - The Robot Report, TechCrunch, IEEE Spectrum for startups and product launches 5. **Company blogs** - Research labs and vendor product announcements 6. **Crunchbase** (via WebSearch) - Startup funding and company profiles 7. **Researcher pages** - Latest work from key people Refer to `research/tools/preferred-sources.md` for specific search queries and sources. ## Output Format ```text Found 10 results for "robot foundation models": Papers: 1. [2026-05] "OpenPI: Open-Source Policy for Robot Manipulation" - Physical Intelligence arXiv:2605.xxxxx - Open VLA model achieving 85% success on 24 tasks 2. [2026-04] "GR00T N1.7: Generalist Robot Policy" - NVIDIA arXiv:2604.xxxxx - Multi-embodiment foundation model Projects: 3. [Active] Physical-Intelligence/openpi - Official OpenPI implementation (2.1k stars) Python/JAX - Open-source VLA with gRPC serving Ecosystem: 4. [Startup] Skild AI - $300M Series A, building general-purpose robot FM Founded 2023, CMU spinout, claims 4x data efficiency Solutions: 5. [Product] NVIDIA Isaac Manipulator - Manipulation pipeline on Isaac ROS GPU-accelerated grasping, integrates with Omniverse Which would you like me to add? (e.g., '1, 3, 5') ``` ## Error Handling - If no results found, suggest related search terms - If too many results (>20), ask user to narrow the search - If search fails, try alternative search methods