Expert in vector databases, embedding strategies, and semantic search implementation. Masters Pinecone, Weaviate, Qdrant, Milvus, and pgvector for RAG applications, recom — from…
Expert in vector databases, embedding strategies, and semantic search implementation. Masters Pinecone, Weaviate, Qdrant, Milvus, and pgvector for RAG applications, recom — from…
Comprehensive guide for managing vector databases including Pinecone, Weaviate, and Chroma for semantic search, RAG systems, and similarity-based applications
Deploy, manage, and optimize vector databases for AI applications. Covers Qdrant, Weaviate, pgvector, and Pinecone — collection management, indexing strategies, backup, and…
Vector database selection, embedding storage, approximate nearest neighbor (ANN) algorithms, and vector search optimization.
Architect, deploy, and optimize production-grade vector search engines using Qdrant, Milvus, and Pinecone.
Create your RAG skill in one prompt, then learn to improve it throughout the chapter — from majiayu000/claude-skill-registry
Vector database expert for embeddings, similarity search, RAG patterns, and indexing strategies
Handles vector databases for efficient storage and querying of high-dimensional vectors in AI/ML applications.
Audit Vector DB coverage -- compares the live filesystem manifest against the ChromaDB index to identify coverage gaps.
Removes stale and orphaned chunks from the ChromaDB vector store for files that have been deleted or renamed.
Ingests repository files into the ChromaDB vector store. Builds or updates the vector index from a manifest or directory scan using ingest.py.
Interactively initializes the Vector DB plugin. Guided discovery asks which folders to index, confirms the manifest, then scaffolds vector_profiles.json for high-performance…
Vector database operations — Pinecone, Weaviate, Qdrant, ChromaDB. Indexing, querying, filtering, and managing
Embedding strategies, ANN algorithms, hybrid search, RAG chunking strategies, and reranking for semantic search and retrieval.
Semantic search skill for retrieving code and documentation from the ChromaDB vector store. Use when you need concept-based search across the repository (Phase 2 of the 3-phase…
Vector similarity and distance algorithms for agent memory ranking. Cosine similarity, Euclidean distance, Manhattan distance, Jaccard, Hamming, and when to use each metric for…
Optimize vector index performance for latency, recall, and memory. Use when tuning HNSW parameters, selecting quantization strategies, or scaling vector search infrastruc — from…
Optimize vector index performance for latency, recall, and memory. Use when tuning HNSW parameters, selecting quantization strategies, or scaling vector search infrastruc — from…
Optimize vector index performance for latency, recall, and memory. Use when tuning HNSW parameters, selecting quantization strategies, or scaling vector search infrastruc — from…
Optimize vector index performance for latency, recall, and memory. Use when tuning HNSW parameters, selecting quantization strategies, or scaling vector search infrastruc — from…
Optimize vector index performance for latency, recall, and memory. Use when tuning HNSW parameters, selecting quantization strategies, or scaling vector search infrastruc — from…
Optimize vector index performance for latency, recall, and memory. Use when tuning HNSW parameters, selecting quantization strategies, or scaling vector search infrastruc — from…
Optimize vector index performance for latency, recall, and memory. Use when tuning HNSW parameters, selecting quantization strategies, or scaling vector search infrastruc — from…
Optimize vector index performance for latency, recall, and memory. Use when tuning HNSW parameters, selecting quantization strategies, or scaling vector search infrastruc — from…
Optimize vector index performance for latency, recall, and memory. Use when tuning HNSW parameters, selecting quantization strategies, or scaling vector search infrastruc — from…
Optimize vector index performance for latency, recall, and memory. Use when tuning HNSW parameters, selecting quantization strategies, or scaling vector search infrastruc — from…
Optimize vector index performance for latency, recall, and memory. Use when tuning HNSW parameters, selecting quantization strategies, or scaling vector search infrastruc — from…
Canonical vector DB / knowledge-graph tooling for code and embeddings: RuVector CLI, RVF format, and GitNexus-style knowledge graphs.
HNSW vector search for pattern similarity retrieval and knowledge graph maintenance with PageRank scoring, community detection, and 3-tier memory management.
HNSW vector search for pattern similarity retrieval and knowledge graph maintenance with PageRank scoring, community detection, and 3-tier memory management.
Persistent vector memory for Claude Code via LanceDB. Use when: remembering across sessions, storing lessons, recalling past decisions, maintaining context continuity.
Full memory stack for OpenClaw on Windows. Includes LanceDB semantic memory, git-notes decision memory, and memory hygiene workflow.
Control Anki Vector robot via wire-pod. Speak through Vector, see through its camera, move head/lift/wheels, change eye colors, trigger animations.
HNSW vector search with RuVector embeddings for 150x-12500x faster semantic retrieval
Implement semantic vector search for construction data. Build AI-powered search using embeddings and vector databases (Qdrant, ChromaDB) for intelligent querying of…
Implement vector search for knowledge retrieval. Use when adding RAG, semantic search, knowledge base features, or context building for the agent.
Problem-solving strategies for vector spaces in linear algebra. Trigger phrases: "problem-solving strategies for vector spaces in linear algebra".
Embedding and vector retrieval expert for semantic searchUse when "vector search, embeddings, semantic search, qdrant, pgvector, similarity search, reranking, hybrid retrieval,…
Run a vector index in production, covering dimensions, filtering, updates, and reindexing when the embedding model changes.
Fix garbled text in PDF/SVG vector graphics caused by font encoding issues, making files editable in AI tools. Supports batch processing and JSON export for manual correction.
Manage codebase and database vectorization for semantic search. Use when initializing, refreshing, or querying the vector index.
Vectorized.io integration. Manage data, records, and automate workflows. Use when the user wants to interact with Vectorized.io data.
Turn a raster logo image into a clean, editable, exactly-symmetric SVG using the vectormark CLI. Use when the user wants to vectorize, idealize, clean up, trace, or convert a…
Standard для агентов VEDA (Ася, Зам, HR, Лекс), которые создают Google Docs и Google Sheets через инструменты create_gdoc / create_gsheet.
Создание и обновление документов (статей базы знаний) в Veda Base (base.myveda.ru). Использовать когда юзер просит "создать документ в Base", "залить в Документы", "сделать гайд…
Создание задач (VHO-*) в Veda Base (base.myveda.ru) программно — через psql или API, с привязкой knowledge-документа («Документ из базы»).
CTO-инфра + операционка VEDA Platform. Техзащита, инцидент-менеджмент, операционная гигиена, аудит класса.
Деплой проектов Veda на сервер 109.73.194.217. rsync, PM2, env-переменные, build. Используй при любом деплое, переносе кода на сервер или перезапуске сервисов.
Продукт VEDA: 7Н/5S, тарифы, модули, опции, НейроАстролог, value stack, маппинг сфер на модули. Используй при создании оффера, лендинга, сравнении тарифов, формировании пакетов,…
Мета-навык для создания новых навыков Veda. Шаблон SKILL.md, структура папок, правила именования, чеклист качества. Используй когда нужно упаковать новое знание в навык.
Generate UGC-style promotional videos with AI lip-sync. Takes an image (person with product from Morpheus/Ad-Ready) and a brief, generates a script, and creates a video of the…
Kontrolli ausalt, mida tead ja mida ei tea enne jätkamist. Kasuta igal hetkel kindluse hindamiseks, lünkade nähtavale toomiseks ja otsustamiseks, kas jätkata või uurida edasi.
Veeva Vault common errors for REST API and clinical operations. Use when working with Veeva Vault document management and CRM. Trigger: "veeva common errors".
Veeva Vault core workflow a for REST API and clinical operations. Use when working with Veeva Vault document management and CRM. Trigger: "veeva core workflow a".
Veeva Vault core workflow b for REST API and clinical operations. Use when working with Veeva Vault document management and CRM. Trigger: "veeva core workflow b".
Veeva Vault cost tuning for REST API and clinical operations. Use when working with Veeva Vault document management and CRM. Trigger: "veeva cost tuning".
Veeva Vault data handling for enterprise operations. Use when implementing advanced Veeva Vault patterns. Trigger: "veeva data handling".
Veeva Vault enterprise rbac for enterprise operations. Use when implementing advanced Veeva Vault patterns. Trigger: "veeva enterprise rbac".
Veeva Vault hello world with REST API and VQL. Use when integrating with Veeva Vault for life sciences document management. Trigger: "veeva hello world".