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Search Apple Notes by meaning or exact text, discover related notes and unexpected connections, and synthesize ideas with citations. The skill guides local setup and tool selection, with on-device search and optional local or cloud language models for synthesis.
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Search arXiv physics, math, and computer science preprints using natural language queries. Powered by Valyu semantic search.
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Use this skill for setting up vector similarity search with pgvector for AI/ML embeddings, RAG applications, or semantic search. **Trigger when user asks to:** - Store or search vector embeddings in PostgreSQL - Set up semantic search, similarity search, or nearest neighbor search - Create HNSW or IVFFlat indexes for vectors - Implement RAG (Retrieval Augmented Generation) with PostgreSQL - Optimize pgvector performance, recall, or memory usage - Use binary quantization for large vector datasets **Keywords:** pgvector, embeddings, semantic search, vector similarity, HNSW, IVFFlat, halfvec, cosine distance, nearest neighbor, RAG, LLM, AI search Covers: halfvec storage, HNSW index configuration (m, ef_construction, ef_search), quantization strategies, filtered search, bulk loading, and performance tuning.
中文简介正在准备中。当前显示原文说明。
小遥搜索 MCP 工具 - 本地文件智能搜索（语义/全文/图像/语音/混合搜索）
中文简介正在准备中。当前显示原文说明。
Semantic search in the DDC CWICR construction cost database using vector embeddings (BGE-M3, 1024-dim, per-language Qdrant collections). Find similar work items and resources for cost estimation across 8 national bases and 30 markets in 26 languages.
中文简介正在准备中。当前显示原文说明。
Semantic + keyword search and connection-discovery across the user's own Apple Notes via the apple-notes MCP server. Use when the user wants to find, recall, or synthesize something from their notes, or surface non-obvious bridges/related notes. macOS, on-device.
中文简介正在准备中。当前显示原文说明。
Assists with storing, searching, and managing vector embeddings using ChromaDB. Use when building RAG pipelines, semantic search engines, or recommendation systems. Trigger words: chromadb, chroma, vector database, embeddings, semantic search, similarity search, vector store, rag.
中文简介正在准备中。当前显示原文说明。
Serverless vector database at the edge with Cloudflare Vectorize. Use when: building semantic search on Cloudflare Workers, RAG pipelines at the edge, low-latency vector similarity search, or storing and querying embeddings without managing a separate vector database.
中文简介正在准备中。当前显示原文说明。
Semantic code search using Phase 1 vector embeddings and Phase 2 hybrid search.
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Search PubMed biomedical literature with natural language queries powered by Valyu semantic search. Full-text access, integrate into your AI projects.
中文简介正在准备中。当前显示原文说明。
Semantic + keyword search and connection-discovery across the user's own Apple Notes via the apple-notes MCP server. Use when the user wants to find, recall, or synthesize something from their notes, or surface non-obvious bridges/related notes. macOS, on-device.
中文简介正在准备中。当前显示原文说明。
Search arXiv physics, math, and computer science preprints using natural language queries. Powered by Valyu semantic search.
中文简介正在准备中。当前显示原文说明。
Semantic + keyword search and connection-discovery across the user's own Apple Notes via the apple-notes MCP server. Use when the user wants to find, recall, or synthesize something from their notes, or surface non-obvious bridges/related notes. macOS, on-device.
中文简介正在准备中。当前显示原文说明。