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Dignified Python

Official
dagster-io·vlatest·backend

Executes Dagster Python code within a controlled environment, ensuring reproducibility and adhering to best practices.

Repository

Install on your platform

This skill no longer installs under the name dignified-python. dagster-io/erk is deleted or private, so it cannot be installed from.

We check each listing against its upstream repository with the rules the skills CLI uses, last on 2026-10-22. We don't show a command we know will fail.

Repository install instructions

What we know about this skill

Publisher

dagster-io

Matched to the vendor's own GitHub organisation.

Install target

Live repository

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

Nobody has reviewed this code. TrustedSkills indexes and links skills; it does not audit, run or scan them. A skill runs with whatever access you give your agent — read the source before you install it.

Automated safety checks

scanned

We could not read this skill's source, so none of the checks below were run.

Not scanned. repository not found or private Source recorded as dagster-io/erk.
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.
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About this skill

What it does

The dagster-io-dignified-python skill allows AI agents to execute Python code within a Dagster pipeline context. This enables the agent to interact with and manipulate data defined in Dagster pipelines, leveraging existing infrastructure for data processing and orchestration. It provides a secure and controlled environment for running arbitrary Python code as part of a larger workflow.

When to use it

  • Data Transformation: An AI agent needs to perform complex calculations or transformations on data managed by a Dagster pipeline.
  • Pipeline Configuration: The agent requires modifying pipeline configurations based on external factors or dynamic inputs.
  • Automated Testing: The skill can be used for automated testing of data quality and pipeline logic within a defined environment.
  • Custom Logic Integration: Integrate custom Python code to extend the functionality of existing Dagster pipelines.

Key capabilities

  • Execution of arbitrary Python code
  • Integration with Dagster pipelines
  • Secure execution environment
  • Access to data defined in Dagster pipelines

Example prompts

  • "Run this Python script to calculate the average value of a column in my dataset."
  • "Update the schedule for my pipeline based on today's date."
  • "Execute this code and check if the result matches the expected output."

Tips & gotchas

The agent needs appropriate permissions within the Dagster environment to execute code and access data. Be mindful of potential security implications when running arbitrary Python code; ensure the code is trusted and validated before execution.