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Found 23 Skills
Analyzes and optimizes SQL queries using EXPLAIN plans, index recommendations, query rewrites, and performance benchmarking. Use for "query optimization", "slow queries", "database performance", or "EXPLAIN analysis".
Generate and optimize SQL queries for data retrieval and analysis
Generate, optimize, and explain SQL queries with best practices. Use when writing database queries or optimizing SQL performance.
Analyze and optimize SQL queries for performance. Use when improving slow queries, reducing execution time, or analyzing query performance in PostgreSQL and MySQL.
Postgres performance optimization and best practices from Supabase. Use this skill when writing, reviewing, or optimizing Postgres queries, schema designs, or database configurations.
Use this skill when the user uploads Excel (.xlsx/.xls) or CSV files and wants to perform data analysis, generate statistics, create summaries, pivot tables, SQL queries, or any form of structured data exploration. Supports multi-sheet Excel workbooks, aggregation, filtering, joins, and exporting results to CSV/JSON/Markdown.
For writing and executing SQL queries - from simple single-table queries to complex multi-table JOINs and aggregations
Expert SQL query writing, optimization, and database schema design with support for PostgreSQL, MySQL, SQLite, and SQL Server. Use when working with databases for: (1) Writing complex SQL queries with joins, subqueries, and window functions, (2) Optimizing slow queries and analyzing execution plans, (3) Designing database schemas with proper normalization, (4) Creating indexes and improving query performance, (5) Writing migrations and handling schema changes, (6) Debugging SQL errors and query issues
Database operations including querying, schema exploration, and data analysis. Activates for tasks involving PostgreSQL, MySQL, MariaDB, SQLite, MongoDB, Redis, Elasticsearch, or ClickHouse databases.
Generate SQL queries from natural language descriptions. Supports BigQuery, PostgreSQL, MySQL, and other dialects. Reads database schemas from uploaded diagrams or documentation. Use when writing SQL, building data reports, exploring databases, or translating business questions into queries.
MySQL relational database. Covers queries, indexes, and optimization. Use when working with MySQL databases. USE WHEN: user mentions "mysql", "mariadb", asks about "AUTO_INCREMENT", "ON DUPLICATE KEY UPDATE", "GROUP_CONCAT", "mysql specific syntax" DO NOT USE FOR: PostgreSQL - use `postgresql` instead, MongoDB - use `mongodb` instead, Oracle - use `oracle` instead, SQL Server - use `sqlserver` instead
PostgreSQL relational database. Covers SQL queries, indexes, constraints, and performance. Use when working with PostgreSQL. USE WHEN: user mentions "postgres", "postgresql", "pg_", asks about "JSONB queries", "window functions", "recursive CTE", "row level security", "full text search", "partitioning", "pgBouncer", "replication" DO NOT USE FOR: MySQL syntax - use `mysql` instead, MongoDB - use `mongodb` instead, Oracle PL/SQL - use `plsql` instead, SQL Server T-SQL - use `tsql` instead