zilliztech/milvus-skill
Agent skill that teaches LLMs to operate Milvus vector database using pymilvus — connection, collections, vector CRUD, search, hybrid search, full-text search, indexing, RBAC, and common patterns like RAG
Agent skill that teaches LLMs to operate Milvus vector database using pymilvus — connection, collections, vector CRUD, search, hybrid search, full-text search, indexing, RBAC, and common patterns like RAG
npx skills add zilliztech/milvus-skillAgent skill that teaches LLMs to operate Milvus vector database using pymilvus — connection, collections, vector CRUD, search, hybrid search, full-text search, indexing, RBAC, and common patterns like RAG
Expert-level UX audits and product metric validation for Claude Code — 65+ UX laws, three-layer diagnostics (UX + events + DB), severity-rated HTML reports with evidence and design mockups
Agent skill repository discovered by 10x-chat research.
Content experimentation and A/B testing guidance covering experiment design, hypotheses, metrics, sample size, statistical foundations, CMS-managed variants, and common analysis pitfalls. Use this skill when planning experiments, setting up variants, choosing success metrics, interpreting statistical results, or building experimentation workflows in a CMS or frontend stack.
Enable AI agents to access real-time Danish data for job search, housing, groceries, weather, travel, and health information.
论文倒读法：给一篇论文，递归找出它批判和改进的前序论文（最多5层），再找它之后的最新进展，从源头正向讲述问题演化史。以问题为轴，费曼式讲解每篇论文看到的问题和解法创新。Use when user shares a paper and wants to understand its intellectual lineage, citation chain, problem evolution, or says '倒读', '论文溯源', '论文脉络', 'paper river', 'paper connects', 'trace back', '这篇论文的来龙去脉', '论文演化'. Also trigger when user wants to understand how a research problem evolved across multiple papers.
Minimal AI coding agent team skills for the full engineering workflow.