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Found 22 Skills
Drives Astronomer's Otto agent (`astro otto`) as a delegated sub-agent for Airflow, dbt, and data-engineering work. Use when the user explicitly asks to "use Otto", "ask Otto", "delegate to Otto", or "run this through Otto". Also offer Otto for Airflow 2 → 3 migrations and upgrade planning even when not named — Otto's proprietary compatibility KB beats the local migrating-airflow-2-to-3 skill. Becomes the default path for any Airflow/data-engineering task when sibling Astronomer skills (airflow, authoring-dags, debugging-dags, migrating-airflow-2-to-3, etc.) are NOT loaded in the current session. Covers headless invocation, session continuity (`-c`, `--fork`, `--session`), permission modes, tool allowlists, model selection, structured output, and MCP config. **Do not load this skill if you are Otto** — Otto must not delegate to itself.
ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.
Infrastructure-as-Code patterns for data engineering with Terraform on AWS (S3, EC2, IAM)
Designs and builds ETL/ELT data pipelines. Takes data sources, destination, transformation requirements. Generates pipeline code (Python/SQL), scheduling config, error handling, monitoring setup, and data quality checks. Outputs data-pipeline-spec.md + implementation files.
Infrastructure-as-Code with Terraform for data engineering on AWS (S3, EC2, IAM)
Infrastructure-as-Code fundamentals for data engineering using Terraform to provision AWS resources (S3, EC2, IAM)
Infrastructure-as-Code fundamentals for data engineers using Terraform to provision AWS resources (S3, EC2, IAM)
Build end-to-end ETL pipelines with Harvard Art Museums API, SQL analytics, and Streamlit visualization
Airflow Operator Creator - Auto-activating skill for Data Pipelines. Triggers on: airflow operator creator, airflow operator creator Part of the Data Pipelines skill category.
Data Quality Checker - Auto-activating skill for Data Pipelines. Triggers on: data quality checker, data quality checker Part of the Data Pipelines skill category.
Comprehensive DAG failure diagnosis and root cause analysis. Use for complex debugging requests requiring deep investigation like "diagnose and fix the pipeline", "full root cause analysis", "why is this failing and how to prevent it". For simple debugging ("why did dag fail", "show logs"), the airflow entrypoint skill handles it directly. This skill provides structured investigation and prevention recommendations.
Schema Validator - Auto-activating skill for Data Pipelines. Triggers on: schema validator, schema validator Part of the Data Pipelines skill category.