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Found 914 Skills
End-to-end data engineering pipeline for Harvard Art Museums API with ETL, SQL analytics, and Streamlit visualization
Generate reproducible analysis artifacts — SQL queries, Python visualizations, and summary tables — as you work through a BigQuery data analysis. Use when asked to conduct a deep dive, exploratory analysis, or investigation that goes beyond a simple data lookup.
Optimizes Snowflake SQL query performance from provided query text. Use when optimizing Snowflake SQL for: (1) User provides or pastes a SQL query and asks to optimize, tune, or improve it (2) Task mentions "slow query", "make faster", "improve performance", "optimize SQL", or "query tuning" (3) Reviewing SQL for performance anti-patterns (function on filter column, implicit joins, etc.) (4) User asks why a query is slow or how to speed it up
Use when you need to generate, validate, or deploy stored procedures for PostgreSQL, MySQL, or SQL Server. Creates database functions, triggers, and procedures with proper error handling and transaction management. Trigger with phrases like "generate stored procedure", "create database function", "write SQL procedure", "add trigger to table", or "create CRUD procedures".
Prevent SQL injection attacks using prepared statements, parameterized queries, and input validation. Use when building database-driven applications securely.
Auto-activate for sqlspec, SQLSpec, SQLFileLoader, drivers, query builders, named SQL, filters, pagination, Arrow, framework extensions, ADK stores, data dictionary, or observers. Not for ORM repositories.
This skill should be used when the user asks to "use SQLModel", "define SQLModel models", "connect SQLModel with FastAPI", "set up a database with SQLModel", or needs guidance on SQLModel best practices, relationships, or session management.
Creates dbt models following project conventions. Use when working with dbt models for: (1) Creating new models (any layer - discovers project's naming conventions first) (2) Task mentions "create", "build", "add", "write", "new", or "implement" with model, table, or SQL (3) Modifying existing model logic, columns, joins, or transformations (4) Implementing a model from schema.yml specs or expected output requirements Discovers project conventions before writing. Runs dbt build (not just compile) to verify.
Alibaba Cloud AnalyticDB for MySQL O&M diagnosis assistant. It supports cluster information query, performance monitoring, slow query diagnosis, running SQL analysis, table-level optimization suggestions, etc. Triggers: "ADB MySQL", "AnalyticDB", "cluster list", "slow query", "BadSQL", "data skew", "idle index", "SQL Pattern", "space diagnosis", "table diagnosis", "performance monitoring".
This file generates or explains Cloud SQL resources. Use this file when the user asks to create a Cloud SQL instance or database for MySQL, PostgreSQL, or SQL Server. Cloud SQL manages third-party MySQL, PostgreSQL, and SQL Server instances as resources in Cloud SQL. For example, when Cloud SQL creates an open-source MySQL instance, the resulting resource is a Cloud SQL for MySQL instance that Google Cloud manages. Cloud SQL handles backups, high availability, and secure connectivity for relational database workloads.
SQL analysis skill for Ascend PyTorch Profiler / msprof DB (e.g., ascend_pytorch_profiler*.db, msprof_*.db). Convert natural language questions (operator latency, communication, dispatch, scheduling, schema/table queries) into safe and executable SQL, and extract table structure details from official documents as needed.
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