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Airflow Hitl

Checked
astronomer·vlatest·data·Apache-2.0

Airflow Hitl streamlines data workflows by automating complex DAGs, boosting efficiency and reducing manual intervention for smoother data pipelines.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add astronomer/agents --skill airflow-hitl -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

astronomer

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned astronomer/agents at cbe1141f54.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
cbe1141f54
Manifest
skills/airflow-hitl/SKILL.md
Scanned
1 file, 171 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

The airflow-hitl skill enables AI agents to interact with Apache Airflow in a human-in-the-loop (HITL) workflow. It allows for dynamic task execution, monitoring, and manual intervention during pipeline runs, ensuring greater control and flexibility over data workflows.

When to use it

  • When you need to pause or modify an Airflow DAG mid-execution based on real-time decisions.
  • During debugging of complex pipelines where manual oversight is required at specific steps.
  • To implement conditional logic that requires human approval before proceeding with downstream tasks.
  • For scenarios involving sensitive data processing, where human validation is necessary.

Key capabilities

  • Integration with Apache Airflow for task execution and monitoring
  • Support for pausing, resuming, or modifying DAG runs on the fly
  • Human-in-the-loop decision points during pipeline execution
  • Real-time feedback loop between AI agent and workflow operators

Example prompts

  • "Pause the 'data-ingestion' DAG at the validation step and wait for manual approval."
  • "Trigger a re-run of task 'transform_data' after fixing an upstream error."
  • "Notify the operator when the 'quality-check' task fails and request intervention."

Tips & gotchas

  • Ensure that your Airflow environment is properly configured to accept external HITL commands.
  • Use this skill judiciously, as over-reliance on manual intervention can slow down automated workflows.