elt-modeling
Comprehensive guide to ELT (Extract, Load, Transform) modeling patterns, dimensional modeling, fact and dimension tables, and data warehouse design
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Comprehensive guide to ELT (Extract, Load, Transform) modeling patterns, dimensional modeling, fact and dimension tables, and data warehouse design
Automated PostgreSQL DB construction and SQL testing for immutable data models. Sets up PostgreSQL container with project-specific schema/data, executes all queries, and generates comprehensive test reports. Use when validating DDL generation results or testing query examples against real database. Triggers include "PostgreSQLで検証", "SQLをテスト", "クエリを実行", "データベースで動作確認", "DDLを検証".
Diff-aware guardrail checker for Fear-of-Falling (FOF) changes; fails closed on raw data edits, Kxx intro/req_cols mismatches, and output discipline risks.
Drizzle ORM for TypeScript - type-safe SQL queries, schema definitions, migrations, and relations. Use when building database layers in Next.js or Node.js applications.
Workflow execution framework with state transitions, bulk operations, rule-based triggers, and authorization. Use when implementing entity workflows with CRUD operations requiring state management and audit trails.
Expert on integrating Shelby Protocol decentralized storage into applications. Helps with use case evaluation, architecture design, migration strategies, cost optimization, performance tuning for video streaming, AI training, data analytics, content delivery, and read-heavy workloads. Triggers on keywords integrate Shelby, decentralized storage integration, video streaming storage, AI training data, data analytics storage, migration to Shelby, storage architecture, content delivery, Shelby use case.
Generate Konveyor analyzer migration rules from migration guides using AI
Generate comprehensive dbt test suites following FF Analytics data quality standards and dbt 1.10+ syntax. This skill should be used when creating tests for new dbt models, adding tests to existing models, standardizing test coverage, or implementing data quality gates. Covers grain uniqueness, FK relationships, enum validation, and freshness tests.
Design and implement Bible reading plans for the KR92 Bible Voice project. Use when: - Creating new reading plans (7-day, 30-day, yearly) - Adding daily readings to existing plans - Generating reading plan SQL migrations - Understanding the reading plan data model - Designing reading sequences (chronological, topical, book-based) - Validating reading reference formats Triggers: "reading plan", "lukusuunnitelma", "daily readings", "create plan", "add readings"
Post-flight validation for Output SDK workflow operations. Systematic verification of step completion, convention compliance, quality validation, and deliverable verification.
Comprehensive guide to Apache Kafka for real-time data streaming including topics, producers, consumers, stream processing, and production best practices
ALWAYS USE when working with Dagster assets, resources, IO managers, schedules, sensors, or dbt integration. CRITICAL for: @asset decorators, @dbt_assets, DbtCliResource, ConfigurableResource, IO managers, partitions. Enforces CATALOG-AS-CONTROL-PLANE architecture - ALL Iceberg writes via catalog (Polaris/Glue). Provides pluggable orchestration patterns abstractable to Airflow/Prefect. Compute abstraction: DuckDB (default), Spark, Snowflake - all via dbt.
AI-powered Telemetry Validator Agent that verifies instrumentation works in sandbox environments. Use when: (1) Validating OTel spans are emitted correctly, (2) Verifying correlation headers in Kafka messages, (3) Confirming OpenLineage events for data pipelines, (4) Generating validation evidence for merge approval. Triggers: "validate telemetry", "verify instrumentation", "check OTel spans", "validate correlation headers".
OpenSolve Pipe component chain data model conventions. Use when creating or modifying components, piping segments, or project structures.
Create dbt models following FF Analytics Kimball patterns and 2×2 stat model. This skill should be used when creating staging models, core facts/dimensions, or analytical marts. Guides through model creation with proper grain, tests, External Parquet configuration, and per-model YAML documentation using dbt 1.10+ syntax.
Use for Supabase schema, RLS policies, API design, and AI integration settings.
MySQL performance optimization guide for Spring Boot/JPA. Use when reviewing database code, discussing index design, query optimization, N+1 problems, JPA/Hibernate tuning, or analyzing EXPLAIN plans. Complements /mysql-performance and /optimize-query commands.
Database seeding toolkit for Supabase projects. Use when: (1) Creating seed data files, (2) Populating lookup/reference tables, (3) Generating test data, (4) Bulk loading data with COPY, (5) Running seed files against database, (6) Managing large seed files with DVC
Follow these patterns when implementing data pipelines, ETL, data ingestion, or data validation in OptAIC. Use for point-in-time (PIT) correctness, Arrow schemas, quality checks, and Prefect orchestration.