airflow

Queries, manages, and troubleshoots Apache Airflow using the `af` CLI. Use when working with anything related to Airflow - a DAG, a DAG run, a task log, an import or parse error, a broken DAG, or any Airflow operation. Covers listing and triggering DAGs, retrying runs, reading task logs, diagnosing failures, debugging import and parse errors, checking connections, variables and pools, exploring the REST API, and monitoring health (for example "trigger a pipeline", "retry a run", "list connections", "check Airflow health", "why did my DAG fail"). This is the entrypoint that routes to sibling skills for authoring, testing, deploying, and migrating Airflow 2 to 3. Not for warehouse/SQL analytics on Airflow metadata tables (use analyzing-data); for deep root-cause reports use debugging-dags or airflow-investigation.

v1.0.1New

#astronomer

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Signed by: skills-hub.ai distributor
Method: Distributor-signed by skills-hub.aiCryptographically signed by the skills-hub.ai distributor key at publish time.
Signed: Jul 16, 2026, 8:19 PM

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npx @skills-hub-ai/cli install astronomer-airflow

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~/.claude/skills/<skill>/SKILL.md

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npx @skills-hub-ai/cli install astronomer-airflow --target claude-code

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blueprintDefine reusable Airflow task group templates with Pydantic validation and compose DAGs from YAML. Use when creating blueprint templates, composing DAGs from YAML, validating configurations, or enabling no-code DAG authoring for non-engineers.0 installs authoring-java-sdk-tasksWrites Airflow task logic in Java, Kotlin, or any JVM language using the Airflow Java SDK. Use when the user wants to implement Airflow tasks in Java/JVM, asks about `@Builder.Dag`/`@Builder.Task`/`@Builder.XCom`, the `Task`/`BundleBuilder` interfaces, reading connections/variables/XComs from Java, the JSON-to-Java type mapping, or logging from Java tasks. This skill covers the Java-specific native API; the shared Python-stub pattern and conceptual model live in authoring-language-sdk-tasks. For building/shipping the bundle see deploying-java-sdk-bundles; for coordinator config see configuring-airflow-language-sdks.0 installs setting-up-astro-projectInitialize and configure Astro/Airflow projects. Use when the user wants to create a new project, set up dependencies, configure connections/variables, or understand project structure. For running the local environment, see managing-astro-local-env.0 installs airflow-hitlBuilds human-in-the-loop (HITL) Airflow workflows - approval gates, form input, and human-driven branching. Use when a DAG needs a human in the loop - an approval or reject step, sign-off before a task runs, a decision or approval UI, branching on a human choice, or collecting form input mid-run; also on mentions of ApprovalOperator, HITLOperator, HITLBranchOperator, HITLEntryOperator, or HITLTrigger. Requires Airflow 3.1+. Not for AI/LLM task calls (see migrating-ai-sdk-to-common-ai).0 installs deploying-airflowDeploy Airflow DAGs and projects. Use when the user wants to deploy code, push DAGs, set up CI/CD, deploy to production, or asks about deployment strategies for Airflow.0 installs deploying-go-sdk-bundlesBuilds, packs, and deploys compiled Airflow Go SDK bundles so the ExecutableCoordinator can run them. Use when the user wants to compile a Go task bundle, asks about `go build`, `go tool airflow-go-pack`, the AFBNDL01 self-contained executable bundle, packing or inspecting a bundle, placing it under `executables_root`, cross-compiling a bundle for workers, `go-sdk` module versioning/tags/pseudo-versions, or getting the bundle onto an Airflow worker (Docker, Kubernetes, or Astro). For the task code see authoring-go-sdk-tasks; for the shared coordinator settings see configuring-airflow-language-sdks.0 installs

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deploying-java-sdk-bundlesBuilds and deploys compiled Airflow Java SDK bundles so workers can run them. Use when the user wants to package a JVM task bundle into a JAR, asks about the `org.apache.airflow.sdk` Gradle plugin, `./gradlew bundle`, the Maven shade/BOM setup, fat vs thin JARs, the logging integration artifacts (JPL, SLF4J, Log4j 2, JUL), preview/snapshot builds, or getting the JAR onto an Airflow worker (Docker, Kubernetes, or Astro). For the task code see authoring-java-sdk-tasks; for the Airflow coordinator settings see configuring-airflow-language-sdks.0 installs managing-astro-deploymentsManage Astronomer production deployments with Astro CLI. Use when the user wants to authenticate, switch workspaces, create/update/delete deployments, or deploy code to production.0 installs cosmos-dbt-fusionUse when running a dbt Fusion project with Astronomer Cosmos. Covers Cosmos 1.11+ configuration for Fusion on Snowflake/Databricks with ExecutionMode.LOCAL. Before implementing, verify dbt engine is Fusion (not Core), warehouse is supported, and local execution is acceptable. Does not cover dbt Core.0 installs checking-freshnessQuick data freshness check. Use when the user asks if data is up to date, when a table was last updated, if data is stale, or needs to verify data currency before using it.0 installs analyzing-dataQueries data warehouse and answers business questions about data. Handles questions requiring database/warehouse queries including "who uses X", "how many Y", "show me Z", "find customers", "what is the count", data lookups, metrics, trends, or SQL analysis.0 installs authoring-language-sdk-tasksThe language-neutral foundation for Airflow language SDKs — implement task logic in a non-Python language while the DAG stays in Python. Use when the user wants to run an Airflow task in another language (Java, Kotlin, Go, or other JVM/native languages), asks how the Python `@task.stub` pairs with native task code, how task/DAG IDs must match across the two sides, how data passes via XCom as JSON, or which language SDKs exist. This skill owns the shared Python-stub pattern and conceptual model; for a specific language's native API, build, and runtime, use that language's skill (e.g. authoring-java-sdk-tasks, authoring-go-sdk-tasks).0 installs

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Frequently asked questions about airflow

What does the airflow skill do?

How do I install the airflow skill?

Run `npx @skills-hub-ai/cli install astronomer-airflow` from your terminal. The CLI writes the SKILL.md to the correct location for your AI tool (e.g. ~/.claude/skills/astronomer-airflow/ for Claude Code or ~/.cursor/skills/ for Cursor with --target cursor) and adds it to your project's .skills.json lockfile.

Which AI tools does airflow work with?

airflow runs in Claude Code. It follows the open Agent Skills standard (SKILL.md), so the same skill works in every supported tool without modification.

Is the airflow skill free?

Yes. Every skill on skills-hub.ai is free and open-source. There are no premium tiers, paywalls, or usage limits. You only pay for whatever AI assistant you're already using.

How do I use airflow after installing it?

In Claude Code, type `/astronomer-airflow` (or whatever slash command the skill registers) and the AI follows the skill's instructions immediately. You can also reference it by name in natural language, your AI loads the skill into context when relevant.

Can I share the airflow skill with my team?

Yes. Commit your project's .skills.json lockfile and teammates run `npx @skills-hub-ai/cli install` (no args) to install every skill at the exact version you pinned. Organization-scoped installs work via skills-hub.ai organizations.