Curated agent skills for 向量搜索 — compare tools, clone hosted repos, and install with Skill Manager.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
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.
Optimize AgentDB performance using quantization, HNSW indexing, caching, and batch operations to improve speed, memory, and scalability.
AI-assisted version control for code agents. Track prompts, context, and diffs automatically with MemoV to ensure full traceability without polluting your git history.
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.
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.
Orchestrates multi-agent iterative refinement for high-quality OpenClaw skill development, ensuring rigorous testing and lifecycle management.
Implement adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement in AI agents.