migrating-dagster-to-airflow

migrating-dagster-to-airflow is a skill for Claude Code from astronomer/agents. It costs 125 tokens per session (3,401 once invoked), scanned A, original, Apache-2.0.

A guide for moving a Dagster project to Apache Airflow 3 on Astro. Dagster and Airflow are tools for running data workflows, but their concepts and behavior do not always match directly.

In plain words
What is it for?
Inventory a Dagster project, map assets, partitions, schedules, and sensors to Airflow concepts, test representative migrations, and move domains over in stages.
Why use it?
It helps teams find and document differences instead of assuming that every Dagster feature has an exact Airflow equivalent.

Skill for Claude Code

Written for Claude Code: hooks in frontmatter.

Part of the astronomer-data plugin — 35 skills, 3 commands shipped together

Good fit Inventory a Dagster project, map assets, partitions, schedules, and sensors to Airflow concepts, test representative migrations, and move domains over in stages.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/astronomer/agents/migrating-dagster-to-airflow
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add astronomer/agents --skill migrating-dagster-to-airflow
Clone the repo
git clone --depth 1 https://github.com/astronomer/agents

Made for: Claude Code.

Or install astronomer-data, the plugin that ships this one along with the rest of its 35 skills, 3 commands.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for migrating-dagster-to-airflow

README.md
[![agentmods](https://agentmods.dev/badge/skills/astronomer/agents/migrating-dagster-to-airflow/github.svg)](https://agentmods.dev/skills/astronomer/agents/migrating-dagster-to-airflow)
Your own site
<a href="https://agentmods.dev/skills/astronomer/agents/migrating-dagster-to-airflow"><img src="https://agentmods.dev/badge/skills/astronomer/agents/migrating-dagster-to-airflow/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for migrating-dagster-to-airflow

Your own site · 80×15
<a href="https://agentmods.dev/skills/astronomer/agents/migrating-dagster-to-airflow"><img src="https://agentmods.dev/badge/skills/astronomer/agents/migrating-dagster-to-airflow.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 125 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,401 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00125 $0.03401
Opus 5 $0.00063 $0.01700
Sonnet 5 $0.00025 $0.00680
Haiku 4.5 $0.00013 $0.00340

Measured 11d ago against content hash 8c6595689c1f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

migrating-dagster-to-airflow scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

The scan reads SKILL.md. This mod also ships 8 executable files (scripts/inventory.py, scripts/status.py, scripts/tests/conftest.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/migrating-dagster-to-airflow/SKILL.md · 149 lines

How it starts

The opening of the file, as written. The whole thing — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Dagster → Airflow 3 (Astro) migration

Migrate a Dagster project to Airflow 3 on Astro Runtime, honestly. The migration is asset-first (Dagster asset graphs translate to Airflow assets and asset-aware schedules, not flattened DAGs), incremental (domain by domain, Dagster stays authoritative until parity), and honest (every definition gets an explicit disposition; semantic deltas are documented, never papered over).

First time driving this? Read reference/quickstart.md first: hour-one commands, the glossary, and what can and cannot break.

Migration at a glance

  1. Baseline the source project's tests, then inventory it read-only (scripts/inventory.py → manifest).
  2. Review classifications (MECH/JUDG/REDESIGN/NONE per reference/mapping.md); make the go/no-go call (three outcomes; migrate-with-conditions is the common case, stay is the narrow one); plan DAG boundaries, per-edge IO decisions, and Gate 3 expectations into the manifest.
  3. Trial-migrate 2-3 representative units end-to-end through every validation gate.
  4. Migrate domain by domain through the six-gate ladder (reference/validation.md), tracking per-unit state (scripts/status.py); fix failure classes via reference/troubleshooting.md, never stub.
  5. Map the platform layer (secrets, alerts, CI/CD, Deployments) per reference/astro-deployment.md.
  6. Run side by side, then cut over per domain (consumers unpause first; see the checklist), keeping rollback one step away.
  7. Deliver the migration report: every definition dispositioned, an equivalence row per trigger, losses stated plainly.

Version drift

Verified against Airflow 3.3.0 / Astro Runtime 3.3-2 / astronomer-cosmos 1.15 / Dagster 1.13 (2026-07). Version-sensitive rows in the references carry their floor (notably the 3.2-vs-3.3 partition surface). Before relying on a version-gated claim: check the target (airflow version, astro deployment inspect), probe imports for sdk surface (python3 -c "from airflow.sdk import X"), and prefer --help / API spec discovery over assuming verbatim CLI/REST contracts on newer versions. Playbook entries are version-scoped per entry.

Read the full file on GitHub · 149 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 149 lines · 125 tokens per session scan A 8c6595689c1f

Subscribe to this mod's changes

migrating-dagster-to-airflow is a skill published in the GitHub repository astronomer/agents (439 stars, last pushed 5d ago), licensed Apache-2.0. It adds 125 tokens to every session and 3,401 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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