Explore AI agent skills related to vector search. Browse installable Claude Code and automation skills on Mentalok Skills Hub.
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11 skills found
High-performance vector search engine for AI agents featuring sub-millisecond retrieval, HNSW indexing, and quantization for efficient RAG, similarity matching, and knowledge base management.
Anthropic Claude integration patterns: streaming, RAG with pgvector, tool use, model selection (Haiku/Sonnet/Opus), prompt caching, and cost management for AI-powered engineering.
Intelligent RAG-based gateway that routes coding tasks to specialized Swift/iOS expertise without context window bloat. Uses MCP to retrieve precise patterns from 100+ indexed skills.
A local RAG semantic memory system using Qdrant and Ollama. Ideal for recalling workspace files, notes, project decisions, and user preferences with high-relevance vector search.
Essential guide to llmemory for document storage and search: installation, database setup with pgvector, document ingestion, hybrid/semantic retrieval, and building RAG systems with multi-tenant support.
Local hybrid search engine for markdown notes, documentation, and codebase knowledge bases to reduce token consumption and improve retrieval efficiency.
Fetch, index, and search developer documentation from GitHub and websites to provide AI agents with accurate, grounded, and version-specific code context.
Upstash Vector DB setup, semantic search, namespaces, and embedding models. Ideal for building high-performance vector search features in Next.js 16/Vercel projects.
A toolkit for writing high-quality agent skills (SKILL.md files) for ClawdHub/MoltHub, covering structure, frontmatter schemas, content patterns, and agent-consumable documentation best practices.
Implement ReasoningBank adaptive learning with AgentDB's ultra-fast vector backend. Features trajectory tracking, verdict judgment, memory distillation, and pattern recognition for self-learning autonomous agents.
Implement adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement in AI agents.