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Found 204 Skills
Expert-level MongoDB database design, aggregation pipelines, indexing, replication, and production operations
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.
MongoDB - NoSQL document database with flexible schema design, aggregation pipelines, indexing strategies, and Spring Data integration
Expert blueprint for GDSkills skill discovery and indexing system. Enables AI agents to find relevant skills by topic/keyword. Use when building skill libraries OR implementing search functionality. Keywords skill discovery, indexing, search, metadata, skill registry.
Optimizes Magento 2 indexing for search performance and database efficiency. Use when optimizing search performance, configuring Elasticsearch, designing database indexes, or improving reindexing strategies. Masters indexer optimization, Elasticsearch configuration, and database indexing.
Use this skill when working on technical SEO infrastructure - crawlability, indexing, XML sitemaps, canonical URLs, robots.txt, redirect chains, rendering strategies (SSR/SSG/ISR/CSR), crawl budget optimization, and search engine rendering. Triggers on fixing indexing issues, configuring crawl directives, choosing rendering strategies for SEO, debugging Google Search Console errors, or auditing site architecture for search engines.
Improve database query performance through indexing, query optimization, and execution plan analysis. Reduce response times and database load.
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.
Use when designing databases for data-heavy applications, making schema decisions for performance, choosing between normalization and denormalization, selecting storage/indexing strategies, planning for scale, or evaluating OLTP vs OLAP trade-offs. Also use when encountering N+1 queries, ORM issues, or concurrency problems.
PostgreSQL database optimization workflow for query tuning, indexing strategies, performance analysis, and production database management.
Vector embeddings with HNSW indexing, sql.js persistence, and hyperbolic support. 75x faster with agentic-flow integration. Use when: semantic search, pattern matching, similarity queries, knowledge retrieval. Skip when: exact text matching, simple lookups, no semantic understanding needed.
Optimize SQL query performance using EXPLAIN analysis, indexing strategies, and common anti-pattern fixes. Use this skill when the user needs to speed up slow queries, design indexes, fix N+1 problems, or optimize database performance — even if they say 'this query is slow', 'optimize our database', 'which indexes do we need', or 'our dashboard takes 30 seconds to load'.