Summarize YouTube videos by extracting and analyzing their transcripts. Use when a user shares a YouTube URL and asks to summarize, explain, analyze, or extract information from the video. Triggers on YouTube links (youtube.com, youtu.be) with requests like "summarize this video", "what's this video about", "give me the key points", or "explain this video".
Postgres query performance optimization and runtime best practices for Supabase. Covers indexing strategies (B-tree, GIN, GiST, BRIN, composite, partial, covering), EXPLAIN ANALYZE diagnostics, connection pooling (Supavisor transaction/session modes, pool sizing), RLS performance patterns (auth.uid() subquery caching, SECURITY DEFINER bypass), concurrency control (deadlock prevention, SKIP LOCKED, advisory locks), data access optimization (N+1 elimination, keyset pagination, batch inserts, UPSERT), runtime monitoring (pg_stat_statements, VACUUM/ANALYZE), and advanced tuning (full-text search, JSONB GIN indexing). Use when writing, reviewing, or optimizing SQL queries, diagnosing slow queries with EXPLAIN, configuring connection pooling, tuning RLS performance, implementing concurrent processing, detecting unused indexes, or resolving Postgres bottlenecks. Does NOT cover schema design (ansem-db-patterns), auth/RLS policy design (supabase-auth-patterns), or TypeScript types (typescript-best-practices).
Systems backends: Go, Rust, databases, caching.
Advanced Supabase integration specialist for Auth, Database (PostgreSQL/RLS), Storage, Realtime, Edge Functions, and AI/Vector features. Use when implementing Supabase features, debugging Supabase issues, setting up RLS policies, creating database schemas, building auth flows, optimizing Supabase queries, migrating to Supabase, or architecting Supabase-based applications. Invoke for Supabase client setup, type generation, migration creation, performance tuning, security audits, or Supabase best practices. Handles Next.js, React, Vue, Svelte, and server-side integrations.
This skill should be used when the user asks about "ActiveRecord", "database queries", "query optimization", "N+1 queries", "eager loading", "associations", "migrations", "database indexes", "SQL performance", "ActiveRecord callbacks", "scopes", or needs guidance on efficient database access patterns in Rails 7+.
Database specialist covering PostgreSQL, MongoDB, Redis, and advanced data patterns for modern applications
Designs comprehensive database schemas including relational and NoSQL models, normalization, indexing strategies, relationship modeling, data types, constraints, and performance optimization. Covers entity-relationship diagrams, schema migrations, partitioning, and best practices for PostgreSQL, MySQL, MongoDB, and other databases. Use when designing databases, creating schemas, modeling data, optimizing queries, or when users mention "database design", "schema design", "data modeling", "ERD", "normalization", "indexing", or "database architecture".
Designs database schemas, data models, relationships, indexes, and migrations for relational, NoSQL, time-series, and warehouse databases. Covers normalization, denormalization, ETL optimization, event sourcing, star schema, and performance tuning. Trigger keywords: schema, table, column, migration, ERD, normalize, denormalize, index, foreign key, primary key, constraint, relationship, SQL, DDL, data model, database design, data warehouse, star schema, snowflake schema, time-series, event sourcing, dimension table, fact table, ETL, data pipeline, OLAP, OLTP.
Production-grade PostgreSQL query optimization, indexing strategies, performance tuning, and modern features including pgvector for AI/ML workloads. Master EXPLAIN plans, query analysis, and database design for high-performance applications
When working with JSON data in LLM prompts (especially large arrays or tabular data), consider the token-efficient TOON (Token-Oriented Object Notation) format which reduces tokens by 30-70% while maintaining lossless JSON representation and structural validation. Use for reading/writing .toon files, converting JSON↔TOON, or optimizing structured data for LLM consumption with guardrails like [N] counts and {field} headers.
Database design and optimization specialist. Schema design, query optimization, indexing strategies, data modeling, and migration planning for relational and NoSQL databases.
Production-grade SQL optimization for OLTP systems: EXPLAIN/plan analysis, balanced indexing, schema and query design, migrations, backup/recovery, HA, security, and safe performance tuning across PostgreSQL, MySQL, SQL Server, Oracle, SQLite.
Design and manage relational databases including table creation, migrations, and schema design. Use for database modeling and maintenance.
Guides and best practices for working with Neon Serverless Postgres. Covers getting started, local development with Neon, choosing a connection method, Neon features, authentication (@neondatabase/...
Work with MongoDB (document database, BSON documents, aggregation pipelines, Atlas cloud) and PostgreSQL (relational database, SQL queries, psql CLI, pgAdmin). Use when designing database schemas, writing queries and aggregations, optimizing indexes for performance, performing database migrations, configuring replication and sharding, implementing backup and restore strategies, managing database users and permissions, analyzing query performance, or administering production databases.
Master MongoDB schema design and data modeling patterns. Learn embedding vs referencing, relationships, normalization, and schema evolution. Use when designing databases, normalizing data, or optimizing queries.
Define database schemas in JSON and generate migration plans. Use this skill when creating or modifying database models, defining tables with columns, constraints, and ENUM types for Vespertide-based projects.
Implement Einstein AI for Salesforce Commerce — Einstein Recommendations (product-to-product, user-to-product, trending), predictive sort, search ranking, Einstein Search Dictionaries, and Data Cloud personalization. Use when adding AI-powered features to commerce storefronts.
Build B2C Commerce storefronts with SFRA (Storefront Reference Architecture) — cartridge overlay system, MVC pattern, app_storefront_base, module.superModule inheritance, middleware chain, and site-specific customizations. Use when developing SFRA-based storefronts.
