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Found 41 Skills
Deep-dive data profiling for a specific table. Use when the user asks to profile a table, wants statistics about a dataset, asks about data quality, or needs to understand a table's structure and content. Requires a table name.
Expert-level PostgreSQL database administration, advanced queries, performance tuning, and production operations
PostgreSQL database helper. Use when writing SQL queries, exploring schema, or working with the database.
Expert in Microsoft SQL Server development and administration. Use when writing T-SQL queries, optimizing database performance, designing schemas, configuring SQL Server, or integrating SQL Server with Node.js using mssql package.
BigQuery Expert Engineer Skill - Comprehensive guide for GoogleSQL queries, data management, performance optimization, and cost management Use when: - Running bq commands (query, load, extract) - Writing GoogleSQL queries (functions, JOINs, CTEs) - Designing partitioned/clustered tables - Using BigQuery ML or external data sources
Expert-level SQL database design, querying, optimization, and administration across PostgreSQL, MySQL, and SQL Server
Build apps on Databricks Apps platform. Use when asked to create dashboards, data apps, analytics tools, or visualizations. Invoke BEFORE starting implementation.
Generate and optimize SQL queries for data retrieval and analysis
Guide for working with SQL queries, in particular for SQLite. Use this skill when writing SQL queries, analyzing database schemas, designing migrations, or working with SQLite-related code.
Guide for using the AI's persistent journal database
Master SQL and database queries across multiple systems. Generate optimized queries, analyze performance, design indexes, and troubleshoot slow queries for PostgreSQL, MySQL, MongoDB, and more.
Query Developer Experience (DX) data via the DX Data MCP server PostgreSQL database. Use this skill when analyzing developer productivity metrics, team performance, PR/code review metrics, deployment frequency, incident data, AI tool adoption, survey responses, DORA metrics, or any engineering analytics. Triggers on questions about DX scores, team comparisons, cycle times, code quality, developer sentiment, AI coding assistant adoption, sprint velocity, or engineering KPIs.