Database
Database management and queries
api-patterns
by redpanda-data
Connect Query patterns for API calls. Use when working with mutations, queries, or data fetching.
state-management
by redpanda-data
Manage client and server state with Zustand stores and React Query patterns.
ln-113-backend-docs-creator
by levnikolaevich
Creates 2 backend docs (api_spec.md, database_schema.md). L3 Worker invoked CONDITIONALLY when hasBackend or hasDatabase detected.
reference-signal-forms
by angular
Explains the mental model and architecture of the code under packages/forms/signals. You MUST use this skill any time you plan to work with code in packages/forms/signals
prisma-cli
by lukevella
Prisma CLI commands reference covering all available commands, options, and usage patterns. Use when running Prisma CLI commands, setting up projects, generating client, running migrations, or managing databases. Triggers on "prisma init", "prisma generate", "prisma migrate", "prisma db", "prisma studio".
prisma-client-api
by lukevella
Prisma Client API reference covering model queries, filters, operators, and client methods. Use when writing database queries, using CRUD operations, filtering data, or configuring Prisma Client. Triggers on "prisma query", "findMany", "create", "update", "delete", "$transaction".
databricks-spark-structured-streaming
by databricks-solutions
Comprehensive guide to Spark Structured Streaming for production workloads. Use when building streaming pipelines, implementing real-time data processing, handling stateful operations, or optimizing streaming performance.
databricks-unstructured-pdf-generation
by databricks-solutions
"Generate synthetic PDF documents for RAG and unstructured data use cases. Use when creating test PDFs, demo documents, or evaluation datasets for retrieval systems."
databricks-lakebase-provisioned
by databricks-solutions
"Patterns and best practices for using Lakebase Provisioned (Databricks managed PostgreSQL) for OLTP workloads."
databricks-vector-search
by databricks-solutions
"Patterns for Databricks Vector Search: create endpoints and indexes, query with filters, manage embeddings. Use when building RAG applications, semantic search, or similarity matching. Covers both storage-optimized and standard endpoints."
databricks-unity-catalog
by databricks-solutions
"Unity Catalog system tables and volumes. Use when querying system tables (audit, lineage, billing) or working with volume file operations (upload, download, list files in /Volumes/)."
databricks-app-python
by databricks-solutions
"Builds Python-based Databricks applications using Dash, Streamlit, Gradio, Flask, FastAPI, or Reflex. Handles OAuth authorization (app and user auth), app resources, SQL warehouse and Lakebase connectivity, model serving integration, and deployment. Use when building Python web apps, dashboards, ML demos, or REST APIs for Databricks, or when the user mentions Streamlit, Dash, Gradio, Flask, FastAPI, Reflex, or Databricks app."
databricks-metric-views
by databricks-solutions
"Unity Catalog metric views: define, create, query, and manage governed business metrics in YAML. Use when building standardized KPIs, revenue metrics, order analytics, or any reusable business metrics that need consistent definitions across teams and tools."
databricks-synthetic-data-generation
by databricks-solutions
"Generate realistic synthetic data using Faker and Spark, with non-linear distributions, integrity constraints, and save to Databricks. Use when creating test data, demo datasets, or synthetic tables."
databricks-genie
by databricks-solutions
"Create and query Databricks Genie Spaces for natural language SQL exploration. Use when building Genie Spaces or asking questions via the Genie Conversation API."
spark-python-data-source
by databricks-solutions
Use when building custom Spark data source connectors for external systems (databases, APIs, message queues), implementing batch/streaming readers/writers, or creating data source plugins for systems without native Spark support. Triggers - "build Spark data source", "create Spark connector", "implement Spark reader/writer", "connect Spark to [system]", "streaming data source"
databricks-lakebase-autoscale
by databricks-solutions
"Patterns and best practices for using Lakebase Autoscaling (next-gen managed PostgreSQL) with autoscaling, branching, scale-to-zero, and instant restore."
databricks-zerobus-ingest
by databricks-solutions
"Build Zerobus Ingest clients for near real-time data ingestion into Databricks Delta tables via gRPC. Use when creating producers that write directly to Unity Catalog tables without a message bus, working with the Zerobus Ingest SDK in Python/Java/Go/TypeScript/Rust, generating Protobuf schemas from UC tables, or implementing stream-based ingestion with ACK handling and retry logic."
databricks-aibi-dashboards
by databricks-solutions
"Create Databricks AI/BI dashboards. CRITICAL: You MUST test ALL SQL queries via execute_sql BEFORE deploying. Follow guidelines strictly."
databricks-dbsql
by databricks-solutions
Databricks SQL (DBSQL) advanced features and SQL warehouse capabilities. This skill MUST be invoked when the user mentions: "DBSQL", "Databricks SQL", "SQL warehouse", "SQL scripting", "stored procedure", "CALL procedure", "materialized view", "CREATE MATERIALIZED VIEW", "pipe syntax", " >", "geospatial", "H3", "ST_", "spatial SQL", "collation", "COLLATE", "ai_query", "ai_classify", "ai_extract", "ai_gen", "AI function", "http_request", "remote_query", "read_files", "Lakehouse Federation", "recursive CTE", "WITH RECURSIVE", "multi-statement transaction", "temp table", "temporary view", "pipe operator". SHOULD also invoke when the user asks about SQL best practices, data modeling patterns, or advanced SQL features on Databricks.
databricks-spark-declarative-pipelines
by databricks-solutions
"Creates, configures, and updates Databricks Lakeflow Spark Declarative Pipelines (SDP/LDP) using serverless compute. Handles streaming tables, materialized views, CDC, SCD Type 2, and Auto Loader ingestion patterns. Use when building data pipelines, working with Delta Live Tables, ingesting streaming data, implementing change data capture, or when the user mentions SDP, LDP, DLT, Lakeflow pipelines, streaming tables, or bronze/silver/gold medallion architectures."
yaml-development
by apache
Guides YAML SDK development in Apache Beam, including environment setup, testing, and key concepts. Use when working with Beam YAML code in sdks/python/apache_beam/yaml/.
migrate-groovy-to-java
by DataDog
migrate test groovy files to java
postgis-skill
by postgis
PostGIS-focused SQL tips, tricks and gotchas. Use when in need of dealing with geospatial data in Postgres.