stream
De la autor
Designing ETL/ELT pipelines, visualizing data flows, selecting batch/streaming approaches, and architecting Kafka/Airflow/dbt systems. Use when building data pipelines or managing data quality.
Instalare
npx skills add simota/agent-skills --skill stream -a claude-code
Se instalează în .claude/skills/stream/ · Fiecare comandă descarcă skill-ul direct de pe GitHub cu utilitarul open source skills.
Identic octet cu octet cu commit-ul scanat, cu licența depozitului și un fișier SOURCE.txt.
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Verificări de siguranță pe SKILL.md
- Conține text ascuns (caractere invizibile, comentarii lungi sau blocuri codificate)Mediu
De ce 75
aiqbench calculează scorul de încredere din semnale publice. Nu este un audit de securitate, așa că citește un skill înainte să-l instalezi.
Skill-uri similare
Cele mai apropiate de acesta prin ce fac și când sunt folosite.
- senior-data-engineerborghei/Claude-SkillsData engineering for batch and streaming pipelines with Airflow, dbt, Spark, and Kafka. Use when designing data architectures, building pipelines, adding data-quality checks, optimizing ETL/ELT, or troubleshooting pipeline failures.Date★ 978
- data-engineeringcbrock84/headcountBuilds and operates data pipelines — ingestion, transformation, orchestration, quality testing, and reliability of data delivery. Use this to design or debug a pipeline, decide batch versus streaming, add data quality checks, handle late or duplicate data, or work out why a dashboard's numbers changed without anyone changing the dashboard.Date★ 2.1K
- engineering-data-pipelinestelagod/code-abyssData engineering knowledge reference covering Airflow, Dagster, Kafka Streams, Flink, dbt, and data quality patterns. Use when building data pipelines, ETL workflows, stream processing, or data quality checks.Date★ 243
- tool.data_engineering.134100a5a52f2e93AI45Lab/OpenARTData engineering practice patterns for data pipelines, ETL/ELT, orchestration, data quality, and infrastructure. Covers Airflow, Dagster, Prefect, Spark, dbt, data lakes, lakehouses, Iceberg, Delta Lake, warehouses (Snowflake, BigQuery, Databricks), streaming (Kafka, Kinesis, Flink), CDC, data contracts, data governance, data mesh, and batch processing. Use when reviewing or building data pipelines, ingestion systems, stream processing, data infrastructure, or data platform architecture. Do not use for SQL modeling or dbt projects (use analytics-engineering), business dashboards (use analytics), or ML model training (use data-science).Date★ 254
- tool.data_engineering.55c8f35d7b3cac72AI45Lab/OpenARTData engineering practice patterns for data pipelines, ETL/ELT, orchestration, data quality, and infrastructure. Covers Airflow, Dagster, Prefect, Spark, dbt, data lakes, lakehouses, Iceberg, Delta Lake, warehouses (Snowflake, BigQuery, Databricks), streaming (Kafka, Kinesis, Flink), CDC, data contracts, data governance, data mesh, and batch processing. Use when reviewing or building data pipelines, ingestion systems, stream processing, data infrastructure, or data platform architecture. Do not use for SQL modeling or dbt projects (use analytics-engineering), business dashboards (use analytics), or ML model training (use data-science).Date★ 254
- data-pipeline-patternsvibeeval/vibecosystemETL/ELT patterns, batch vs streaming, idempotency, data quality framework, and pipeline orchestrationDate★ 540
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