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Found 155 Skills
Spatial indexing and world streaming for Three.js building games with thousands of pieces. Use when optimizing building games, implementing spatial queries, chunk loading, or profiling performance. Includes spatial hash grids, octrees, chunk managers, and benchmarking tools.
Check Meilisearch index status, tasks, health, and settings. Use for debugging search issues, monitoring indexing tasks, and inspecting index configuration. Read-only admin operations.
Vector search indexing and querying workflows using MCP Vector Search, including setup, reindexing, auto-index strategies, and MCP integration.
Knowledge Base RAG implements the complete Retrieval-Augmented Generation pipeline: document ingestion, intelligent chunking, embedding generation, vector store indexing, semantic retrieval, and grounded response generation.
Fetch a single URL and convert its content to Markdown. Use when you need to read a web page, documentation page, or API reference without indexing it. The content is returned as plain Markdown text on stdout.
Language Server Protocol specialist building unified code intelligence systems through LSP client orchestration and semantic indexing
Official Google SEO guide covering search optimization, best practices, Search Console, crawling, indexing, and improving website search visibility based on official Google documentation
Database schema design, indexing, and migration guidance for MongoDB-based applications.
Implement persistence layers with Spring Data JPA. Use when creating repositories, configuring entity relationships, writing queries (derived and @Query), setting up pagination, database auditing, transactions, UUID primary keys, multiple databases, and database indexing. Covers repository interfaces, JPA entities, custom queries, relationships, and performance optimization patterns.
Optimize SQL queries for performance with indexing strategies, query rewriting, and execution plan analysis. Use when queries are slow, optimizing database performance, or analyzing query execution.
Azure SQL Database best practices skill for optimizing T-SQL code, database configuration, indexing strategies, and application patterns. Based on Microsoft SQL Assessment API, SSDT Code Analysis rules, Azure SQL Database performance guidance, and official Microsoft best practices. Use this skill when writing, reviewing, or refactoring code that interacts with Azure SQL Database.
Complete guide for OpenAI's Assistants API v2: stateful conversational AI with built-in tools (Code Interpreter, File Search, Function Calling), vector stores for RAG (up to 10,000 files), thread/run lifecycle management, and streaming patterns. Both Node.js SDK and fetch approaches. ⚠️ DEPRECATION NOTICE: OpenAI plans to sunset Assistants API in H1 2026 in favor of Responses API. This skill remains valuable for existing apps and migration planning. Use when: building stateful chatbots with OpenAI, implementing RAG with vector stores, executing Python code with Code Interpreter, using file search for document Q&A, managing conversation threads, streaming assistant responses, or encountering errors like "thread already has active run", vector store indexing delays, run polling timeouts, or file upload issues. Keywords: openai assistants, assistants api, openai threads, openai runs, code interpreter assistant, file search openai, vector store openai, openai rag, assistant streaming, thread persistence, stateful chatbot, thread already has active run, run status polling, vector store error