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Authoring Dags

skill-kilo-org-kilo-marketplace-authoring-dags · by Kilo-Org

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Install

$ agentstack add skill-kilo-org-kilo-marketplace-authoring-dags

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

DAG Authoring Skill

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.


Running the CLI

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.


Workflow Overview

+-----------------------------------------+
| 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              |
+-----------------------------------------+

Phase 1: Discover

Before writing code, understand the context.

Explore the Codebase

Use file tools to find existing patterns:

  • Glob for **/dags/**/*.py to find existing DAGs
  • Read similar DAGs to understand conventions
  • Check requirements.txt for available packages

Query the Airflow Environment

Use 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:

  • "Is there a Snowflake connection?" -> af config connections
  • "What Airflow version?" -> af config version
  • "Are S3 operators available?" -> af config providers

Phase 2: Plan

Based on discovery, propose:

  1. DAG structure - Tasks, dependencies, schedule
  2. Operators to use - Based on available providers
  3. Connections needed - Existing or to be created
  4. Variables needed - Existing or to be created
  5. Packages needed - Additions to requirements.txt

Get user approval before implementing.


Phase 3: Implement

Write the DAG following best practices (see below). Key steps:

  1. Create DAG file in appropriate location
  2. Update requirements.txt if needed
  3. Save the file

Phase 4: Validate

Use af CLI as a feedback loop to validate your DAG.

Step 1: Check Import Errors

After saving, check for parse errors (Airflow will have already parsed the file):

af dags errors
  • If your file appears -> fix and retry
  • If no errors -> continue

Common causes: missing imports, syntax errors, missing packages.

Step 2: Verify DAG Exists

af dags get 

Check: DAG exists, schedule correct, tags set, paused status.

Step 3: Check Warnings

af dags warnings

Look for deprecation warnings or configuration issues.

Step 4: Explore DAG Structure

af dags explore 

Returns in one call: metadata, tasks, dependencies, source code.

On Astro

If you're running on Astro, you can also validate locally before deploying:

  • Parse check: Run astro dev parse to catch import errors and DAG-level issues without starting a full Airflow environment
  • DAG-only deploy: Once validated, use astro deploy --dags for fast DAG-only deploys that skip the Docker image build — ideal for iterating on DAG code

Phase 5: Test

> See the testing-dags skill for comprehensive testing guidance.

Once validation passes, test the DAG using the workflow in the testing-dags skill:

  1. Get user consent -- Always ask before triggering
  2. Trigger and wait -- af runs trigger-wait --timeout 300
  3. Analyze results -- Check success/failure status
  4. Debug if needed -- af runs diagnose and af tasks logs

Quick Test (Minimal)

# Ask user first, then:
af runs trigger-wait  --timeout 300

For the full test -> debug -> fix -> retest loop, see testing-dags.


Phase 6: Iterate

If issues found:

  1. Fix the code
  2. Check for import errors: af dags errors
  3. Re-validate (Phase 4)
  4. Re-test using the testing-dags skill workflow (Phase 5)

CLI Quick Reference

| 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 | Verify DAG config | | Validate | af dags warnings | Configuration warnings | | Validate | af dags explore | Full DAG inspection |

> Testing commands -- See the testing-dags skill for af runs trigger-wait, af runs diagnose, af tasks logs, etc.


Best Practices & Anti-Patterns

For code patterns and anti-patterns, see [reference/best-practices.md](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.


Related Skills

  • testing-dags: For testing DAGs, debugging failures, and the test -> fix -> retest loop
  • debugging-dags: For troubleshooting failed DAGs
  • deploying-airflow: For deploying DAGs to production (Astro or open-source)
  • migrating-airflow-2-to-3: For migrating DAGs to Airflow 3

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.