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Found 1,160 Skills
Grafana Cloud Database Observability — query-level performance insights for MySQL and PostgreSQL. Covers setup with Grafana Alloy, query samples, visual explain plans, RED metrics, pg_stat_statements and Performance Schema integration, and correlation with application traces. Use when monitoring database performance, diagnosing slow queries, setting up database observability for MySQL or PostgreSQL (self-managed, RDS, Aurora, Azure, Cloud SQL), or correlating DB metrics with APM data.
Manages datasets, tables, and jobs in BigQuery, and integrates with BigQuery ML and Gemini for advanced data analytics and AI-driven insights. Use when you need to interact with BigQuery, run SQL queries, manage BigQuery resources, or leverage BigQuery's built-in ML capabilities. Also use when performing data analysis, ingesting data into BigQuery, or developing AI applications on BigQuery.
Azure Cosmos DB performance optimization and best practices guidelines for NoSQL, partitioning, queries, and SDK usage. Use when writing, reviewing, or refactoring code that interacts with Azure Cosmos DB, designing data models, optimizing queries, or implementing high-performance database operations.
Production incident response procedures for Python/React applications. Use when responding to production outages, investigating error spikes, diagnosing performance degradation, or conducting post-mortems. Covers severity classification (SEV1-SEV4), incident commander role, communication templates, diagnostic commands for FastAPI/ PostgreSQL/Redis, rollback procedures, and blameless post-mortem process. Does NOT cover monitoring setup (use monitoring-setup) or deployment procedures (use deployment-pipeline).
Generate a Wren MDL project by exploring a database with available tools (SQLAlchemy, database drivers, MCP connectors, or raw SQL). Guides agents through schema discovery, type normalization, and MDL YAML generation using the wren CLI. Use when: user wants to create or set up a new MDL, onboard a new data source, or scaffold a project from an existing database.
End-to-end retail ETL pipeline using PySpark, SQL Server, and Medallion Architecture (Bronze/Silver/Gold layers) for data warehousing
Safegres is Constructive's security protocol for expressing authorization as Authz* policy nodes (types + JSON configs). This skill defines each Authz* type, its config shape, semantics, and when to use it. No SQL and no SDK/grant/RLS steps.
Creates structured bug reports for defects found during Oracle-to-PostgreSQL migration. Use when documenting behavioral differences between Oracle and PostgreSQL as actionable bug reports with severity, root cause, and remediation steps.
Identifies Oracle-to-PostgreSQL migration risks by cross-referencing code against known behavioral differences (empty strings, refcursors, type coercion, sorting, timestamps, concurrent transactions, etc.). Use when planning a database migration, reviewing migration artifacts, or validating that integration tests cover Oracle/PostgreSQL differences.
Use when building Apache Spark applications, distributed data processing pipelines, or optimizing big data workloads. Invoke for DataFrame API, Spark SQL, RDD operations, performance tuning, streaming analytics.
Complete guide for using drift database library in Dart applications (CLI, server-side, non-Flutter). Use when building Dart apps that need local SQLite database storage or PostgreSQL connection with type-safe queries, reactive streams, migrations, and efficient CRUD operations. Includes setup with sqlite3 package, PostgreSQL support with drift_postgres, connection pooling, and server-side patterns.
Optimizes Snowflake query performance using query ID from history. Use when optimizing Snowflake queries for: (1) User provides a Snowflake query_id (UUID format) to analyze or optimize (2) Task mentions "slow query", "optimize", "query history", or "query profile" with a query ID (3) Analyzing query performance metrics - bytes scanned, spillage, partition pruning (4) User references a previously run query that needs optimization Fetches query profile, identifies bottlenecks, returns optimized SQL with expected improvements.