Set up CI that reports what CHANGED between the base branch and the PR — new vs resolved type errors, lint issues, formatter drift, bundle size, and test failures — in one PR…
Use when deciding whether a project fits Critical Inquiry (CI) and which format to target. CI is the leading interdisciplinary journal of criticism and theory in the arts and…
Conception de pipelines CI/CD pour tout type de plateforme. Se déclenche avec "CI/CD", "pipeline", "GitHub Actions", "Azure DevOps", "GitLab CI", "déploiement automatique — from…
MUST USE when designing ClickHouse architectures, selecting between ingestion or modeling patterns, or translating best practices into workload-specific system designs.
Use when syncing data FROM relational databases (PostgreSQL, MySQL, MongoDB) TO ClickHouse. Covers change data capture using Debezium, Airbyte, or custom triggers.
Run ClickHouse integration tests in CI with GitHub Actions and Docker containers. Use when setting up automated testing against a real ClickHouse instance, configuring CI…
Diagnose and fix the top 15 ClickHouse errors — query failures, insert problems, memory limits, and merge issues.
Collect ClickHouse diagnostic data — system tables, query logs, merge status, and server metrics for support tickets and troubleshooting.
Create your first ClickHouse table, insert data, and run analytical queries. Use when starting a new ClickHouse project, learning MergeTree basics, or testing your ClickHouse…
Run ClickHouse locally with Docker, configure test fixtures, and iterate fast. Use when setting up a local ClickHouse dev environment, writing integration tests, or running…
MUST USE when investigating performance issues on a ClickHouse-managed Postgres instance. Provides an evidence-based RCA workflow that scrapes the Prometheus endpoint for system…
Configure ClickHouse across dev, staging, and production with environment-specific settings, secrets management, and infrastructure-as-code patterns.
Monitor ClickHouse with Prometheus metrics, Grafana dashboards, system table queries, and alerting for query performance, merge health, and resource usage.
Production readiness checklist for ClickHouse — server tuning, backup, monitoring, and deployment verification.
Configure ClickHouse query concurrency, memory quotas, and connection limits. Use when hitting "too many simultaneous queries", managing concurrent users, or tuning server-side…
Production reference architecture for ClickHouse-backed applications — project layout, data flow, multi-tenant patterns, and operational topology.
Use when ingesting continuous data streams from Kafka, RabbitMQ, or Kinesis into ClickHouse. Covers backpressure handling, exactly-once semantics, stream processing patterns, and…
D1、Vectorize、Queues、Workers をまたぐデータパイプラインの整合性と失敗処理を設計・レビューする。複数サービスの結合部に使う。単一 API の使い方には使わない。「Queue再処理」「D1とVectorizeの不整合」を正のトリガーとし、単一Workerのdeploy安全性には cloudflare-worker-cd を使う。
Real-time structural Code Health via CodeScene MCP — review before edits, verify score deltas after changes, gate commits and PRs.
Lets an agent run dbt parity checks, relation diffs, and row or value comparisons so refactors and source swaps can be verified before rollout.
Kafka Connect integration expert. Covers source and sink connectors, JDBC, Elasticsearch, S3, Debezium CDC, SMT (Single Message Transforms), connector configuration, and data…
Decide whether and when a SaaS should build its own app/connector marketplace, versus joining others' marketplaces or buying embedded iPaaS, and design its operating model -…
Scaffold a working GitHub Pages website from a vetted template and wire it to deploy automatically. Use when the user wants to create, scaffold, or publish a site on GitHub Pages…
Use when writing Spark jobs, debugging performance issues, or configuring cluster settings for Apache Spark applications, distributed data processing pipelines, or big da — from…
Synthesize Reflector insights into structured delta proposals for playbook updates, following ACE paper's Curator architecture
Manages MongoDB Atlas Stream Processing (ASP) workflows. Handles workspace provisioning, data source/sink connections, processor lifecycle operations, debugging diagnosti — from…
Debugs why session recordings aren't appearing in the local dev environment. Use when a developer reports that local replay ingestion isn't working, recordings aren't showing up…
Guide the user through connecting a new data warehouse source — Postgres, MySQL, Stripe, Hubspot, MongoDB, Salesforce, BigQuery, Snowflake, and so on.
Deploys the current project to a live HTTPS URL via Cybrix. Activates on any request to make the current project public, get a URL for it, deploy it, ship it, host it, publish it,…
Expert guidance for Dagster data orchestration including assets, resources, automation, testing,
Orchestrate data pipelines using Dagster, the cloud-native data orchestration platform. Define data assets as Python functions with automatic lineage tracking, scheduling, and…
Expert guidance for Dagster data orchestration including assets, resources, schedules, sensors, partitions, testing, and ETL patterns.
Interact with Dagster data orchestration platform running locally or on Kubernetes. Use when Claude needs to monitor Dagster runs, get run logs, list assets/jobs, materialize…
ALWAYS USE when working with Dagster assets, resources, IO managers, schedules, sensors, or dbt integration.
Anleitung zur Analyse der DailyQuest Supabase-Datenbank mit der Supabase CLI. Enthält den kompletten Workflow: CLI installieren, authentifizieren, Projekt verknüpfen, Schema…
Create data pipeline and analytics architecture diagrams using PlantUML syntax with database/analytics stencil icons.
Build scalable data pipelines, modern data warehouses, and real-time streaming architectures. Implements Apache Spark, dbt, Airflow, and cloud-native data platforms.
Use when user needs scalable data pipeline development, ETL/ELT implementation, or data infrastructure design.
Data engineering patterns for ETL pipelines, data warehousing, Apache Spark, and data quality validation
You are a data pipeline architecture expert specializing in scalable, reliable, and cost-effective data pipelines for batch and streaming data processing.
Build data ingestion pipelines for batch and streaming data from multiple sources. Covers extraction strategies, format normalization, deduplication, validation gates, and staging…
Patterns Apache Kafka — topics, partitions, consumer groups, exactly-once semantics et Kafka Streams.
Provides architectural guidance for data lake design including partitioning strategies, storage layout, schema design, and lakehouse patterns.
Data Lake architecture and management including medallion architecture (bronze/silver/gold zones), data catalog with AWS Glue, partitioning strategies, schema evolution, data…
Data Mesh architecture patterns — domain ownership, data products with SLOs, self-serve platform design, Delta Lake vs Iceberg, federated Trino queries, data contracts,…
Use when planning, reviewing, or troubleshooting a Salesforce data migration — covering tool selection (Data Loader, Bulk API 2.0, MuleSoft, Informatica, Jitterbit), migration…
Designs and builds ETL/ELT data pipelines. Takes data sources, destination, transformation requirements.
트리거: "데이터 파이프라인", "celery task", "kafka consumer", "파이프라인 만들어줘", "비동기 작업", "airflow dag", "airflow 만들어줘", "배치 파이프라인", "rabbitmq", "메시지 큐", "etl 파이프라인", "데이터 처리", "스케줄러 만들어줘" 수행:…
Review or design a data pipeline architecture. Assesses ingestion pattern, transformation design, orchestration, idempotency, freshness SLAs, data contracts at boundaries, dbt…
Testing data pipelines including ETL validation, data quality checks, pipeline orchestration testing, and data lineage verification.
Write correct, performant SQL across all major data warehouse dialects (Snowflake, BigQuery, Databricks, PostgreSQL, etc.).
Syncing Rails Postgres to a data warehouse (Snowflake, BigQuery, Redshift) — Fivetran / Airbyte / Hightouch / Stitch / Census / CDC via Debezium, when ELT beats ETL, dbt for…
Snowflake, BigQuery, Redshift, dimensional modeling, and modern data warehouse architecture
Route a database/data task to the right skill among the data-layer specialists — PostgreSQL, MySQL/MariaDB, the Prisma ORM, Redis, ClickHouse analytics, cross-engine migrations,…
Modern deployment with Databricks Asset Bundles (DAB), supporting multi-environment configurations and CI/CD integration.
Fix the deploy-time foot-guns of Databricks Asset Bundles (DAB) and the infrastructure operations around them: the bundle-bind gap for UC catalogs and external locations, the…
Configure Databricks CI/CD integration with GitHub Actions and Asset Bundles. Use when setting up automated testing, configuring CI pipelines, or integrating Databricks…
Diagnose and fix Databricks common errors and exceptions. Use when encountering Databricks errors, debugging failed jobs, or troubleshooting cluster and notebook issues.
Execute Databricks primary workflow: Delta Lake ETL pipelines. Use when building data ingestion pipelines, implementing medallion architecture, or creating Delta Lake…
Execute Databricks secondary workflow: MLflow model training and deployment. Use when building ML pipelines, training models, or deploying to production.