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Found 416 Skills
Creates a complete Amazon Aurora database cluster with instances, handling cluster creation, instance provisioning, and Secrets Manager password management in the proper sequence. Use when setting up new Aurora MySQL or PostgreSQL clusters with production-ready configuration.
Workload-aware architecture design for Apache Doris. MUST USE when designing data architectures, choosing between data models, planning ingestion strategies, sizing clusters, or translating business requirements into Apache Doris system designs. Complements doris-best-practices with decision frameworks and sizing-first workflow. Use when user describes a workload involving: IoT, sensor data, telemetry, real-time analytics, dashboard, log analysis, log search, CDC sync, time-series, device monitoring, point query service, ad-hoc analytics, lakehouse federation, ETL/ELT pipeline, report analytics, clickstream, user behavior, observability, metrics, fleet tracking, or any OLAP workload requiring table design from scratch. Also triggers on prompts like: "design a table for...", "how should I store...", "build an architecture for...", "we have X devices sending data every Y seconds", "recommend a cluster size for...", "what data model should I use for...", "we need to ingest X GB/day", "migrate from MySQL/PostgreSQL to Apache Doris". Also use for legacy analytics/search/serving stack consolidation prompts even when Apache Doris is not named explicitly, including replacing or migrating from Impala, Kudu, Elasticsearch/ES, Greenplum, Presto, HBase, Hive, Hadoop, Redis, or Lambda-style multi-engine data platforms.
This skill should be used when the user wants to add a database (Postgres, Redis, MySQL, MongoDB), says "add postgres", "add redis", "add database", "connect to database", or "wire up the database". For other templates (Ghost, Strapi, n8n, etc.), use the templates skill.
Automatically discover database skills when working with SQL, PostgreSQL, MongoDB, Redis, database schema design, query optimization, migrations, connection pooling, ORMs, or database selection. Activates for database design, optimization, and implementation tasks.
Database operations including querying, schema exploration, and data analysis. Activates for tasks involving PostgreSQL, MySQL, MariaDB, SQLite, MongoDB, Redis, Elasticsearch, or ClickHouse databases.
Use when "evaluating technology", "choosing frameworks", "stack comparison", "technology decisions", or asking about "React vs Vue", "PostgreSQL vs MySQL", "AWS vs GCP", "build vs buy"
Drizzle ORM documentation covering queries, CRUD operations, schema definitions, migrations, caching (50 topics), custom types, and database connections. Includes integrations for PostgreSQL (Neon, Vercel, Supabase, AWS Data API, PlanetScale, Prisma), MySQL (AWS Data API, PlanetScale, TiDB), and SQLite (Bun, Cloudflare D1/Durable Objects, Expo, Turso, OP SQLite). Use when working with Drizzle queries, database schemas, migrations, type-safe SQL, ORM patterns, or connecting to supported databases.
Connect Spice to data sources and query across them with federated SQL. Use when connecting to databases (Postgres, MySQL, DynamoDB), data lakes (S3, Delta Lake, Iceberg), warehouses (Snowflake, Databricks), files, APIs, or catalogs; configuring datasets; creating views; writing data; or setting up cross-source queries.
Drizzle ORM — type-safe, lightweight TypeScript ORM for SQL databases. Schema declaration, CRUD queries, joins, relations, migrations with Drizzle Kit, and database seeding. Use when defining database schemas, writing queries (select/insert/update/delete), setting up migrations, configuring drizzle.config.ts, establishing database connections, validating data with drizzle-zod/valibot, or working with PostgreSQL, MySQL, SQLite, Turso, Bun SQL, Neon, Supabase, PGlite, Expo SQLite, Cloudflare D1, PlanetScale, SingleStore, MSSQL, CockroachDB.
Best practices, coding conventions, and patterns for backend projects using TypeScript. Use when writing code, tests, or new features in TypeScript backends with src/, Express, PostgreSQL/MongoDB, and Mocha+tsx.
Cal.com self-hosted deployment to GCP Cloud Run with Supabase PostgreSQL. Docker Compose for local dev. TRIGGERS - deploy calcom, cloud run, self-hosted, docker compose, supabase, gcp deploy, infrastructure, cal.com hosting.
Pipeline state management for Goldsky Turbo — pause, resume, restart, and delete commands with their rules and safety behavior. Use this skill when the user asks: will deleting my pipeline lose the data already in my postgres/clickhouse table, how do I pause a pipeline while doing database maintenance, how do I restart from block zero to reprocess all historical data, can I update a running streaming pipeline in place or do I have to delete and redeploy, will resuming a paused pipeline pick up from where it left off (checkpoint), how do I re-run a completed job pipeline from the beginning, can I pause or restart a job-mode pipeline. Also covers what happens to checkpoint state on delete, and job auto-deletion 1 hour after termination. For actively diagnosing why a pipeline is broken or erroring, use /turbo-doctor instead.