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Found 119 Skills
Analyze whether ClickHouse indexes (PRIMARY KEY, ORDER BY, skipping indexes, projections) are being used effectively for actual query patterns. Use when investigating index effectiveness, ORDER BY key design, query-to-index alignment, or when queries scan more data than expected.
Diagnose ClickHouse RAM usage, OOM errors, memory pressure, and allocation patterns. Use for memory-related issues and out-of-memory errors.
Vitess best practices, query optimization, and connection troubleshooting for PlanetScale Vitess databases. Load when working with PlanetScale Vitess databases, sharding, VSchema configuration, keyspace management, or MySQL-compatible scaling issues.
Help with MongoDB query optimization and indexing. Use only when the user asks for optimization or performance: "How do I optimize this query?", "How do I index this?", "Why is this query slow?", "Can you fix my slow queries?", "What are the slow queries on my cluster?", etc. Do not invoke for general MongoDB query writing unless user asks for performance or index help. Prefer indexing as optimization strategy. Use MongoDB MCP when available.
PostgreSQL 数据库管理
Tips and best practices for effective GrepAI searches. Use this skill to improve search result quality.
Search and fetch Microsoft Learn documentation
Analyzes and optimizes SQL/NoSQL queries for performance. Use when reviewing query performance, optimizing slow queries, analyzing EXPLAIN output, suggesting indexes, identifying N+1 problems, recommending query rewrites, or improving database access patterns. Supports PostgreSQL, MySQL, SQLite, MongoDB, Redis, DynamoDB, and Elasticsearch.
Use this skill when querying Tarkov game data via MCP tools. Provides optimal query patterns, data relationships, and best practices for the tarkov-dev and eft-wiki MCP servers.
Generate complete solutions for specific Dataverse SDK use cases with architecture recommendations
Formulate effective web search queries, analyze search results, and synthesize findings. Optimize search strategies for different types of information needs.
Guides MongoDB users through implementing and optimizing Atlas Search (full-text), Vector Search (semantic), and Hybrid Search solutions. Use this skill when users need to build search functionality for text-based queries (autocomplete, fuzzy matching, faceted search), semantic similarity (embeddings, RAG applications), or combined approaches. Also use when users need text containment, substring matching ('contains', 'includes', 'appears in'), case-insensitive or multi-field text search, or filtering across many fields with variable combinations. Provides workflows for selecting the right search type, creating indexes, constructing queries, and optimizing performance using the MongoDB MCP server.