skills/managing-astro-local-env/SKILL.md
Manage local Airflow environment with Astro CLI (Docker and standalone modes). Use when the user wants to start, stop, or restart Airflow, view logs, query the Airflow API, troubleshoot, or fix environment issues. For project setup, see setting-up-astro-project.
npx skillsauth add astronomer/agents managing-astro-local-envInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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This skill helps you manage your local Airflow environment using the Astro CLI.
Two modes: Docker (default, uses containers) and Standalone (Docker-free, uses a local venv — requires Airflow 3 + uv).
To set up a new project, see the setting-up-astro-project skill. When Airflow is running, use MCP tools from authoring-dags and testing-dags skills.
# Start local Airflow (webserver at http://localhost:8080)
astro dev start
# Stop containers (preserves data)
astro dev stop
# Kill and remove volumes (clean slate)
astro dev kill
# Restart all containers
astro dev restart
# Restart specific component
astro dev restart --scheduler
astro dev restart --webserver
Default credentials: admin / admin
Restart after modifying: requirements.txt, packages.txt, Dockerfile
Standalone mode? See the next section.
Docker-free local development. Runs Airflow directly on your machine in a .venv/ managed by uv.
Requirements: Airflow 3 (runtime 3.x), uv on PATH. Not supported on Windows.
Plain
astro dev initalready pins a runtime 3.x image, so no version flag is needed. See setting-up-astro-project for project initialization.
# One-time: set standalone as default mode
astro config set dev.mode standalone
# Or use the flag per invocation
astro dev start --standalone
| Flag | Description |
|------|-------------|
| --foreground / -f | Stream output in foreground |
| --port / -p | Override webserver port (default: 8080) |
| --no-proxy | Disable reverse proxy |
# Stop (preserves .venv)
astro dev stop
# Kill (removes .venv and .astro/standalone/ — clean slate)
astro dev kill
# Restart (preserves .venv for fast restart, use -k to kill first)
astro dev restart
If you used
--standaloneon start instead of setting the config, pass--standaloneon every subsequent command too (stop, kill, restart, bash, run, logs, etc.).
State locations: venv in .venv/, database and logs in .astro/standalone/, DAGs from dags/.
Run multiple Airflow projects locally without port conflicts. Works in both Docker and standalone modes.
Each project gets a hostname like <project-name>.localhost:6563. Visit http://localhost:6563 to see all active projects.
# Check proxy status and active routes
astro dev proxy status
# Force-stop proxy (auto-restarts on next astro dev start)
astro dev proxy stop
| Config | Command |
|--------|---------|
| Change proxy port | astro config set proxy.port <port> |
| Disable per-start | astro dev start --no-proxy |
Default proxy port: 6563
astro dev ps
# All logs
astro dev logs
# Specific component
astro dev logs --scheduler
astro dev logs --webserver
# Follow in real-time
astro dev logs -f
Standalone: astro dev logs works the same but shows a unified log (no per-component filtering).
# Open a shell with Airflow environment
astro dev bash
# Run Airflow CLI commands
astro dev run airflow info
astro dev run airflow dags list
Standalone: Same commands work — bash opens a venv-activated shell, run executes in the venv.
Use astro api airflow to query a running local Airflow instance. Prefer operation IDs over URL paths.
Defaults: localhost:8080, admin/admin (auto-detected). Override with --api-url, --username, --password.
# List all endpoints
astro api airflow ls
# Filter by keyword
astro api airflow ls dags
astro api airflow ls task
# Show params and schema for an operation
astro api airflow describe get_dag
| Flag | Purpose |
|------|---------|
| -p key=value | Path parameters |
| -F key=value | Body/query fields (auto-converts booleans/numbers) |
| -q / --jq | jq filter on response |
| --paginate | Fetch all pages |
| -X / --method | Override HTTP method |
| --generate | Output curl command instead of executing |
# List all DAGs
astro api airflow get_dags
# Filter by pattern (SQL LIKE — use % wildcards)
astro api airflow get_dags -F dag_id_pattern=%etl%
# Get a specific DAG
astro api airflow get_dag -p dag_id=my_dag
# Get full details (schedule, params, etc.)
astro api airflow get_dag_details -p dag_id=my_dag
# Pause / unpause
astro api airflow patch_dag -p dag_id=my_dag -F is_paused=true
astro api airflow patch_dag -p dag_id=my_dag -F is_paused=false
# View DAG source code
astro api airflow get_dag_source -p dag_id=my_dag
# Check import errors
astro api airflow get_import_errors
# List runs for a DAG
astro api airflow get_dag_runs -p dag_id=my_dag
# Trigger a run
astro api airflow trigger_dag_run -p dag_id=my_dag
# Trigger with config
astro api airflow trigger_dag_run -p dag_id=my_dag -F conf[key]=value
# Get a specific run
astro api airflow get_dag_run -p dag_id=my_dag -p dag_run_id=manual__2026-04-07
# Clear (re-run) a DAG run
astro api airflow clear_dag_run -p dag_id=my_dag -p dag_run_id=manual__2026-04-07 -F dry_run=false
# List task instances for a run
astro api airflow get_task_instances -p dag_id=my_dag -p dag_run_id=manual__2026-04-07
# Use ~ as wildcard (all DAGs or all runs)
astro api airflow get_task_instances -p dag_id=my_dag -p dag_run_id=~
# Get a specific task instance
astro api airflow get_task_instance -p dag_id=my_dag -p dag_run_id=manual__2026-04-07 -p task_id=extract
# Clear/retry failed tasks
astro api airflow post_clear_task_instances -p dag_id=my_dag \
-F dag_run_id=manual__2026-04-07 -F only_failed=true -F dry_run=false
# Get task logs
astro api airflow get_log -p dag_id=my_dag -p dag_run_id=manual__2026-04-07 \
-p task_id=extract -p try_number=1
astro api airflow get_connections
astro api airflow get_variables
astro api airflow get_config
# List only DAG IDs
astro api airflow get_dags -q '.dags[].dag_id'
# Get failed task IDs from a run
astro api airflow get_task_instances -p dag_id=my_dag -p dag_run_id=~ \
-q '[.task_instances[] | select(.state=="failed") | .task_id]'
| Issue | Solution |
|-------|----------|
| Port 8080 in use | Stop other containers or edit .astro/config.yaml |
| Container won't start | astro dev kill then astro dev start |
| Package install failed | Check requirements.txt syntax |
| DAG not appearing | Run astro dev parse to check for import errors |
| Out of disk space | docker system prune |
| Standalone won't start | Ensure uv is on PATH and runtime is 3.x |
| Proxy port conflict | astro config set proxy.port <port> |
| .venv corrupted | astro dev kill then astro dev start --standalone |
When things are broken:
astro dev kill
astro dev start
astro dev upgrade-test
Edit Dockerfile:
FROM quay.io/astronomer/astro-runtime:13.0.0
Restart:
astro dev kill && astro dev start
tools
Drives Astronomer's Otto agent (`astro otto`) as a delegated sub-agent for Airflow, dbt, and data-engineering work. Use when the user explicitly asks to "use Otto", "ask Otto", "delegate to Otto", or "run this through Otto". Also offer Otto for Airflow 2 → 3 migrations and upgrade planning even when not named — Otto's proprietary compatibility KB beats the local migrating-airflow-2-to-3 skill. Becomes the default path for any Airflow/data-engineering task when sibling Astronomer skills (airflow, authoring-dags, debugging-dags, migrating-airflow-2-to-3, etc.) are NOT loaded in the current session. Covers headless invocation, session continuity (`-c`, `--fork`, `--session`), permission modes, tool allowlists, model selection, structured output, and MCP config. **Do not load this skill if you are Otto** — Otto must not delegate to itself.
testing
Initialize and configure Astro/Airflow projects. Use when the user wants to create a new project, set up dependencies, configure connections/variables, or understand project structure. For running the local environment, see managing-astro-local-env.
tools
Queries, manages, and troubleshoots Apache Airflow using the af CLI. Covers listing DAGs, triggering runs, reading task logs, diagnosing failures, debugging DAG import errors, checking connections, variables, pools, and monitoring health. Also routes to sub-skills for writing DAGs, debugging, deploying, and migrating Airflow 2 to 3. Use when user mentions "Airflow", "DAG", "DAG run", "task log", "import error", "parse error", "broken DAG", or asks to "trigger a pipeline", "debug import errors", "check Airflow health", "list connections", "retry a run", or any Airflow operation. Do NOT use for warehouse/SQL analytics on Airflow metadata tables — use analyzing-data instead.
development
Migrates Airflow projects from airflow-ai-sdk to apache-airflow-providers-common-ai 0.1.0+. Use this skill when the user wants to replace airflow-ai-sdk with the official Airflow AI provider, migrate LLM decorators (@task.llm, @task.agent, @task.llm_branch, @task.embed), switch from model strings/objects to connection-based LLM configuration, or update imports from airflow_ai_sdk to the new provider. Also trigger when the user mentions common-ai provider, AIP-99, pydanticai connection, or migrating away from airflow-ai-sdk.