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astronomer-agents

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astronomer/agents

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What it does
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AI agent tooling for data engineering workflows.

communityairflowastronomerauthoringbigquerydatadata-engineeringengineeringexplorationintegration

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Last UpdatedJan 29, 2026

More from this repository10

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Queries data warehouses to answer business questions by executing SQL, finding tables, and retrieving precise metrics and trends.

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airflow๐ŸŽฏSkill

Manages Apache Airflow operations via the af CLI (installed via uvx from astro-airflow-mcp), including listing, testing, running, and debugging DAGs, viewing task logs, checking connections and variables, and monitoring system health. Supports multi-instance configuration with auto-discovery of Astro and local deployments.

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authoring-dags๐ŸŽฏSkill

Guides developers in creating robust Apache Airflow DAGs using best practices and MCP tools.

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debugging-dags๐ŸŽฏSkill

Systematically diagnoses Airflow DAG failures by performing deep root cause analysis, identifying error sources, and providing structured prevention recommendations.

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migrating-airflow-2-to-3๐ŸŽฏSkill

Guides users through migrating Apache Airflow 2.x projects to Airflow 3.x, addressing code changes, imports, operators, and compatibility issues.

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testing-dags๐ŸŽฏSkill

Triggers and monitors Airflow DAG runs, automatically waiting for completion and providing immediate feedback on success or failure.

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tracing-upstream-lineage๐ŸŽฏSkill

Traces data origins by investigating DAGs, source tables, and external systems to map the complete upstream lineage of a data asset.

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profiling-tables๐ŸŽฏSkill

Data profiling agent skills for deep-dive table analysis including metadata inspection, column-level statistics, and data quality assessment using SQL queries.

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tracing-downstream-lineage๐ŸŽฏSkill

Traces downstream data dependencies to reveal potential impacts and risks when modifying tables or data pipelines.

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