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Found 28 Skills
MUST USE when reviewing ClickHouse schemas, queries, or configurations. Contains 28 rules that MUST be checked before providing recommendations. Always read relevant rule files and cite specific rules in responses.
MUST USE when designing ClickHouse architectures, selecting between ingestion or modeling patterns, or translating best practices into workload-specific system designs. Complements clickhouse-best-practices with decision frameworks and explicit provenance labels.
Design an end-to-end MotherDuck pipeline. Use when choosing raw, staging, and analytics boundaries, bulk ingestion paths, transformation sequencing, publication targets, or whether DuckLake is actually required.
Use when reading from or writing to Neo4j with Apache Spark or Databricks using the Neo4j Connector for Apache Spark (org.neo4j:neo4j-connector-apache-spark). Covers SparkSession setup, DataFrame reads via labels/Cypher/relationship scan, DataFrame writes with SaveMode, node.keys for MERGE, relationship write mapping, partition and batch tuning, PySpark and Scala examples, Databricks cluster config, Databricks secrets for credentials, Delta Lake to Neo4j pipelines. Does NOT handle Cypher authoring — use neo4j-cypher-skill. Does NOT handle the Python bolt driver — use neo4j-driver-python-skill. Does NOT handle GDS algorithms — use neo4j-gds-skill.
Materialize documentation for SQL syntax, data ingestion, concepts, and best practices. Use when users ask about Materialize queries, sources, sinks, views, or clusters.
Use bigquery CLI (instead of `bq`) for all Google BigQuery and GCP data warehouse operations including SQL query execution, data ingestion (streaming insert, bulk load, JSONL/CSV/Parquet), data extraction/export, dataset/table/view management, external tables, schema operations, query templates, cost estimation with dry-run, authentication with gcloud, data pipelines, ETL workflows, and MCP/LSP server integration for AI-assisted querying and editor support. Modern Rust-based replacement for the Python `bq` CLI with faster startup, better cost awareness, and streaming support. Handles both small-scale streaming inserts (<1000 rows) and large-scale bulk loading (>10MB files), with support for Cloud Storage integration.
Tinybird TypeScript SDK for defining datasources, pipes, and queries with full type inference. Use when working with @tinybirdco/sdk, TypeScript Tinybird projects, or type-safe data ingestion and queries.
Creates and maintains dlt (data load tool) pipelines from APIs, databases, and other sources. Use when the user wants to build or debug pipelines; use verified sources (e.g. Salesforce, GitHub, Stripe) or declarative REST API or custom Python; configure destinations (e.g. DuckDB, BigQuery, Snowflake); implement incremental loading; or edit .dlt config and secrets. Use when the user mentions data ingestion, dlt pipeline, dlt init, rest_api_source, incremental load, or pipeline dashboard.
Guide for creating GreptimeDB Pipeline, by which user can add a process layer to GreptimeDB between ingestion and storage, to transform data.
Input template configuration for Elastic integrations. Covers agent stream templates (agent/stream/*.yml.hbs) for all non-CEL input types: HTTPJSON, AWS S3, CloudWatch, Azure Blob, Azure EventHub, GCS, GCP Pub/Sub, TCP, UDP, HTTP Endpoint, Filestream, Logfile, Journald, Winlog, and WebSocket. For CEL input programs, use the cel-programs skill instead.
Analyzes clinical trial protocols and generates CDISC-compliant (SDTM/ADaM) data schemas. Use when designing data ingestion pipelines for clinical research or preparing regulatory submissions.
Goldsky Turbo pipeline YAML reference — the authoritative source for field names, required vs optional fields, and valid values. Use whenever the user asks about specific YAML fields: what does `start_at: earliest` vs `latest` do, what fields does a postgres/clickhouse/kafka sink require, what is the `from:` field in a sink, how does `checkpoint` work, what's the syntax for `batch_size` or `primary_key`. Also use for validation errors like 'unknown field' or 'missing required field'. For interactive pipeline building end-to-end, use /turbo-builder instead.