Chart Tests
astronomer/airflow-chart
A skill your agent uses when writing, editing, reviewing, or running Helm chart tests for the Astronomer airflow-chart repository.
Workflow and best practices for writing Apache Airflow DAGs.
$ npx skills add astronomer/agents --skill authoring-dags -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install astronomer/agents authoring-dags --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/astronomer/agents.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/authoring-dags .claude/skills/authoring-dags && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "authoring-dags" agent skill from https://github.com/astronomer/agents/tree/main/skills/authoring-dags into .claude/skills/authoring-dags/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "authoring-dags", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/astronomer/agents/tree/main/skills/authoring-dagsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add astronomer/agents --skill authoring-dags -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install astronomer/agents authoring-dags --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/astronomer/agents.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/authoring-dags .agents/skills/authoring-dags && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "authoring-dags" agent skill from https://github.com/astronomer/agents/tree/main/skills/authoring-dags into .agents/skills/authoring-dags/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "authoring-dags", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add astronomer/agents --skill authoring-dags -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install astronomer/agents authoring-dags --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/astronomer/agents.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/authoring-dags .cursor/skills/authoring-dags && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "authoring-dags" agent skill from https://github.com/astronomer/agents/tree/main/skills/authoring-dags into .cursor/skills/authoring-dags/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "authoring-dags", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/astronomer/agents.git --path skills/authoring-dags--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add astronomer/agents --skill authoring-dags -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install astronomer/agents authoring-dags --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/astronomer/agents.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/authoring-dags .gemini/skills/authoring-dags && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "authoring-dags" agent skill from https://github.com/astronomer/agents/tree/main/skills/authoring-dags into .gemini/skills/authoring-dags/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "authoring-dags", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install astronomer/agents authoring-dagsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add astronomer/agents --skill authoring-dags -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/astronomer/agents.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/authoring-dags .github/skills/authoring-dags && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "authoring-dags" agent skill from https://github.com/astronomer/agents/tree/main/skills/authoring-dags into .github/skills/authoring-dags/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "authoring-dags", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add astronomer/agents --skill authoring-dags -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install astronomer/agents authoring-dags --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/astronomer/agents.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/authoring-dags .opencode/skills/authoring-dags && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "authoring-dags" agent skill from https://github.com/astronomer/agents/tree/main/skills/authoring-dags into .opencode/skills/authoring-dags/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "authoring-dags", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
authoring-dagsWorkflow and best practices for writing Apache Airflow DAGs.
Authoring Dags is an agent skill from astronomer/agents. Workflow and best practices for writing Apache Airflow DAGs. Use when creating a new DAG, write pipeline code, handling questions about DAG patterns and conventions or extending an existing DAG with a follow-up/downstream task. ANY request shaped like 'add a DAG named X', 'write a pipeline', 'add a task that runs after Y', or 'extend the DAG'. For testing and debugging DAGs, see the testing-dags skill.
Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `reference/best-practices.md`).
It sits in Data & Analytics, covering Data pipelines and ETL. It works with Apache Airflow and Astro. The repository describes itself as: AI agent tooling for data engineering workflows. The licence is Apache-2.0.
6 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 486ee63. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
uvFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use uv, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Authoring Dags loads about 1.8k tokens when it runs. Until then it costs about 105 tokens; SKILL.md has 665 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from astronomer/agents at commit 486ee63, republished under its Apache-2.0 licence (© astronomer). 665 words, ~1,769 tokens.
.claude/skills/authoring-dags/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.This skill guides you through creating and validating Airflow DAGs using best practices and af CLI commands.
For testing and debugging DAGs, see the testing-dags skill which covers the full test -> debug -> fix -> retest workflow.
These commands assume af is on PATH. Run via astro otto to get it automatically, or install standalone with uv tool install astro-airflow-mcp.
+-----------------------------------------+
| 1. DISCOVER |
| Understand codebase & environment |
+-----------------------------------------+
|
+-----------------------------------------+
| 2. PLAN |
| Propose structure, get approval |
+-----------------------------------------+
|
+-----------------------------------------+
| 3. IMPLEMENT |
| Write DAG following patterns |
+-----------------------------------------+
|
+-----------------------------------------+
| 4. VALIDATE |
| Check import errors, warnings |
+-----------------------------------------+
|
+-----------------------------------------+
| 5. TEST (with user consent) |
| Trigger, monitor, check logs |
+-----------------------------------------+
|
+-----------------------------------------+
| 6. ITERATE |
| Fix issues, re-validate |
+-----------------------------------------+Before writing code, understand the context.
Use file tools to find existing patterns:
Glob for **/dags/**/*.py to find existing DAGsRead similar DAGs to understand conventionsrequirements.txt for available packagesUse af CLI commands to understand what's available:
| Command | Purpose |
|---|---|
af config connections | What external systems are configured |
af config variables | What configuration values exist |
af config providers | What operator packages are installed |
af config version | Version constraints and features |
af dags list | Existing DAGs and naming conventions |
af config pools | Resource pools for concurrency |
Example discovery questions:
af config connectionsaf config versionaf config providersBased on discovery, propose:
Get user approval before implementing.
Write the DAG following best practices (see below). Key steps:
requirements.txt if neededUse af CLI as a feedback loop to validate your DAG.
After saving, check for parse errors (Airflow will have already parsed the file):
af dags errorsCommon causes: missing imports, syntax errors, missing packages.
af dags get <dag_id>Check: DAG exists, schedule correct, tags set, paused status.
af dags warningsLook for deprecation warnings or configuration issues.
af dags explore <dag_id>Returns in one call: metadata, tasks, dependencies, source code.
If you're running on Astro, you can also validate locally before deploying:
astro dev parse to catch import errors and DAG-level issues without starting a full Airflow environmentastro deploy --dags for fast DAG-only deploys that skip the Docker image build — ideal for iterating on DAG codeSee the testing-dags skill for comprehensive testing guidance.
Once validation passes, test the DAG using the workflow in the testing-dags skill:
af runs trigger-wait <dag_id> --timeout 300af runs diagnose <dag_id> <run_id> and af tasks logs <dag_id> <run_id> <task_id># Ask user first, then:
af runs trigger-wait <dag_id> --timeout 300For the full test -> debug -> fix -> retest loop, see testing-dags.
If issues found:
af dags errors| Phase | Command | Purpose |
|---|---|---|
| Discover | af config connections | Available connections |
| Discover | af config variables | Configuration values |
| Discover | af config providers | Installed operators |
| Discover | af config version | Version info |
| Validate | af dags errors | Parse errors (check first!) |
| Validate | af dags get <dag_id> | Verify DAG config |
| Validate | af dags warnings | Configuration warnings |
| Validate | af dags explore <dag_id> | Full DAG inspection |
Testing commands -- See the testing-dags skill for
af runs trigger-wait,af runs diagnose,af tasks logs, etc.
For code patterns and anti-patterns, see reference/best-practices.md.
Read this reference when writing new DAGs or reviewing existing ones. It covers what patterns are correct (including Airflow 3-specific behavior) and what to avoid.
© astronomer, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file in skills/authoring-dags of astronomer/agents.
Open the folder on GitHubat commit 486ee63
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in astronomer/agents, which our catalogue first saw on October 7, 2026.
Authoring Dags next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Authoring Dags this skillastronomer/agents | 451 | 1 repos | ~1.8k | Automated safety check: Pass | Apache-2.0 | |
| Chart Testsastronomer/airflow-chart | 297 | — | ~2.8k | Automated safety check: Pass | Custom licence | |
| Functional Testsastronomer/airflow-chart | 297 | — | ~2.2k | Automated safety check: Pass | Custom licence | |
| Helm Chartastronomer/airflow-chart | 297 | — | ~6.4k | Automated safety check: Pass | Custom licence | |
| Upgrading Mwaa Environmentsaws/agent-toolkit-for-aws | 2.8k | — | ~7.3k | Automated safety check: Pass | Apache-2.0 | |
| Paidf Orchestration Write DagNVIDIA/skills | 3.5k | — | ~8.2k | Automated safety check: Pass | Apache-2.0 |
astronomer/airflow-chart
A skill your agent uses when writing, editing, reviewing, or running Helm chart tests for the Astronomer airflow-chart repository.
astronomer/airflow-chart
A skill your agent uses when writing, editing, reviewing, or running functional (end-to-end) tests for the Astronomer airflow-chart repository.
astronomer/airflow-chart
A skill your agent uses for Helm chart work - creating charts, modifying existing charts, values design, testing.
aws/agent-toolkit-for-aws
Upgrades an MWAA environment to a newer Airflow version — within 2.x, within 3.x, or across the 2.x-to-3.x boundary.
NVIDIA/skills
A skill your agent uses when a user describes a custom PAIDF Orchestration pipeline — a specific ordered combination of stages such as augmentation only, auto-labeling only, detection+captioning…
aws/agent-toolkit-for-aws
Authors and deploys MWAA workflow artifacts: Python Airflow DAGs for provisioned environments or YAML workflow files for Serverless.
astronomer/agents
Queries the data warehouse with SQL and answers business questions about data.
astronomer/agents
Queries, manages, and troubleshoots Apache Airflow using the af CLI.
astronomer/agents
Guide for migrating Dagster projects to Apache Airflow 3 on Astro.
astronomer/agents
Deploys Airflow DAGs and projects. An agent skill from astronomer/agents.
astronomer/agents
Builds human-in-the-loop (HITL) Airflow workflows - approval gates, form input, and human-driven branching.
astronomer/agents
Annotate Airflow tasks with data lineage using inlets and outlets.
Works with
Categories
Workflow and best practices for writing Apache Airflow DAGs. Authoring Dags is an agent skill from astronomer/agents. Workflow and best practices for writing Apache Airflow DAGs.
Authoring Dags fits situations like: creating a new DAG; write pipeline code; handling questions about DAG patterns and conventions; extending an existing DAG with a follow-up/downstream task.
Run `npx skills add astronomer/agents --skill authoring-dags -a claude-code`. Or copy the skill folder (skills/authoring-dags in astronomer/agents) into .claude/skills/authoring-dags in your project. Claude Code loads it when a task matches its description.
Run `npx skills add astronomer/agents --skill authoring-dags -a codex`. Or copy the skill folder (skills/authoring-dags in astronomer/agents) into .agents/skills/authoring-dags in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add astronomer/agents --skill authoring-dags -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/authoring-dags, .gemini/skills/authoring-dags, .github/skills/authoring-dags and .opencode/skills/authoring-dags in your project.
Going by SKILL.md and its folder, Authoring Dags needs the command-line tools its instructions call (uv). Our summary lists: Docker.
SKILL.md contains no URLs. Its commands use uv, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Authoring Dags is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.8k tokens (SKILL.md is roughly 7.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Authoring Dags: Chart Tests (astronomer/airflow-chart, 297 stars), Functional Tests (astronomer/airflow-chart, 297 stars), Helm Chart (astronomer/airflow-chart, 297 stars) and Upgrading Mwaa Environments (aws/agent-toolkit-for-aws, 2.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
astronomer (a GitHub organization) maintains it in astronomer/agents, which has 451 GitHub stars. The repository holds 34 skills in this directory. The repository was last updated on October 7, 2026.
Source: astronomer/agents on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.