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Dagster Expert

Official
dagster-io·vlatest·data·Apache-2.0

The Dagster Expert skill provides in-depth knowledge and troubleshooting assistance for Dagster workflows, accelerating development and resolving complex issues.

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 dagster-io/skills --skill dagster-expert -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

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.

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 failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • Declares what it does: failed

    SKILL.md frontmatter is missing 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 dagster-io/skills at 672f242fe3.

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

Commit
672f242fe3
Manifest
plugins/dagster/skills/dagster-expert/SKILL.md
Scanned
60 files, 2,714 lines
Copies in repo
2 — all of them scanned
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

This skill provides expertise in Dagster, a data orchestrator. It can assist with defining and managing pipelines, understanding concepts like assets and dependencies, and troubleshooting common issues within a Dagster environment. The skill allows users to interact with Dagster definitions and configurations programmatically.

When to use it

  • Pipeline Debugging: Troubleshoot errors or unexpected behavior in existing Dagster data pipelines.
  • Code Generation: Generate basic Dagster pipeline code snippets based on high-level descriptions of required functionality.
  • Concept Explanation: Understand complex Dagster concepts like assets, schedules, and sensors.
  • Configuration Assistance: Help configure Dagster installations or deployments.

Key capabilities

  • Understanding of Dagster pipelines and assets
  • Ability to interpret Dagster definitions (Python code)
  • Knowledge of common Dagster terminology
  • Assistance with troubleshooting Dagster-related issues

Example prompts

  • "Explain the difference between a Dagster asset and a job."
  • "Generate a simple Dagster pipeline that loads data from CSV and saves it to Parquet."
  • “How do I define a schedule in Dagster?”

Tips & gotchas

  • The skill’s effectiveness is dependent on providing clear and specific prompts related to Dagster concepts or code. A basic understanding of Python is helpful for interpreting generated code snippets.