AgentSkillsCN

airflow

管理Apache Airflow的各项操作,包括列出DAG、测试DAG、运行DAG、调试DAG、查看任务日志、检查连接与变量,以及监控系统健康状况。当您需要处理Airflow DAG、管道、工作流或任务时,或者当用户提及DAG测试、管道运行、工作流调试、DAG失败、任务报错、DAG状态、管道状态、列出DAG、展示连接、检查变量,或关注Airflow健康状况时,均可调用此技能。

SKILL.md
--- frontmatter
name: airflow
description: Manages Apache Airflow operations including listing, testing, running, and debugging DAGs, viewing task logs, checking connections and variables, and monitoring system health. Use when working with Airflow DAGs, pipelines, workflows, or tasks, or when the user mentions testing dags, running pipelines, debugging workflows, dag failures, task errors, dag status, pipeline status, list dags, show connections, check variables, or airflow health.

Airflow Operations

Use af commands to query, manage, and troubleshoot Airflow workflows.

Running the CLI

Run all af commands using uvx (no installation required):

bash
uvx --from astro-airflow-mcp@latest af <command>

Throughout this document, af is shorthand for uvx --from astro-airflow-mcp@latest af.

Instance Configuration

Manage multiple Airflow instances with persistent configuration:

bash
# Add a new instance
af instance add prod --url https://airflow.example.com --token "$API_TOKEN"
af instance add staging --url https://staging.example.com --username admin --password admin

# List and switch instances
af instance list      # Shows all instances in a table
af instance use prod  # Switch to prod instance
af instance current   # Show current instance
af instance delete old-instance

# Override instance for a single command
af --instance staging dags list

Config file: ~/.af/config.yaml (override with --config or AF_CONFIG env var)

Tokens in config can reference environment variables using ${VAR} syntax:

yaml
instances:
- name: prod
  url: https://airflow.example.com
  auth:
    token: ${AIRFLOW_API_TOKEN}

Or use environment variables directly (no config file needed):

bash
export AIRFLOW_API_URL=http://localhost:8080
export AIRFLOW_AUTH_TOKEN=your-token-here
# Or username/password:
export AIRFLOW_USERNAME=admin
export AIRFLOW_PASSWORD=admin

Or CLI flags: af --airflow-url http://localhost:8080 --token "$TOKEN" <command>

Quick Reference

CommandDescription
af healthSystem health check
af dags listList all DAGs
af dags get <dag_id>Get DAG details
af dags explore <dag_id>Full DAG investigation
af dags source <dag_id>Get DAG source code
af dags pause <dag_id>Pause DAG scheduling
af dags unpause <dag_id>Resume DAG scheduling
af dags errorsList import errors
af dags warningsList DAG warnings
af dags statsDAG run statistics
af runs listList DAG runs
af runs get <dag_id> <run_id>Get run details
af runs trigger <dag_id>Trigger a DAG run
af runs trigger-wait <dag_id>Trigger and wait for completion
af runs diagnose <dag_id> <run_id>Diagnose failed run
af tasks list <dag_id>List tasks in DAG
af tasks get <dag_id> <task_id>Get task definition
af tasks instance <dag_id> <run_id> <task_id>Get task instance
af tasks logs <dag_id> <run_id> <task_id>Get task logs
af config versionAirflow version
af config showFull configuration
af config connectionsList connections
af config variablesList variables
af config variable <key>Get specific variable
af config poolsList pools
af config pool <name>Get pool details
af config pluginsList plugins
af config providersList providers
af config assetsList assets/datasets
af api <endpoint>Direct REST API access
af api lsList available API endpoints
af api ls --filter XList endpoints matching pattern

User Intent Patterns

DAG Operations

  • "What DAGs exist?" / "List all DAGs" -> af dags list
  • "Tell me about DAG X" / "What is DAG Y?" -> af dags explore <dag_id>
  • "What's the schedule for DAG X?" -> af dags get <dag_id>
  • "Show me the code for DAG X" -> af dags source <dag_id>
  • "Stop DAG X" / "Pause this workflow" -> af dags pause <dag_id>
  • "Resume DAG X" -> af dags unpause <dag_id>
  • "Are there any DAG errors?" -> af dags errors

Run Operations

  • "What runs have executed?" -> af runs list
  • "Run DAG X" / "Trigger the pipeline" -> af runs trigger <dag_id>
  • "Run DAG X and wait" -> af runs trigger-wait <dag_id>
  • "Why did this run fail?" -> af runs diagnose <dag_id> <run_id>

Task Operations

  • "What tasks are in DAG X?" -> af tasks list <dag_id>
  • "Get task logs" / "Why did task fail?" -> af tasks logs <dag_id> <run_id> <task_id>

System Operations

  • "What version of Airflow?" -> af config version
  • "What connections exist?" -> af config connections
  • "Are pools full?" -> af config pools
  • "Is Airflow healthy?" -> af health

API Exploration

  • "What API endpoints are available?" -> af api ls
  • "Find variable endpoints" -> af api ls --filter variable
  • "Access XCom values" / "Get XCom" -> af api xcom-entries -F dag_id=X -F task_id=Y
  • "Get event logs" / "Audit trail" -> af api event-logs -F dag_id=X
  • "Create connection via API" -> af api connections -X POST --body '{...}'
  • "Create variable via API" -> af api variables -X POST -F key=name -f value=val

Common Workflows

Investigate a Failed Run

bash
# 1. List recent runs to find failure
af runs list --dag-id my_dag

# 2. Diagnose the specific run
af runs diagnose my_dag manual__2024-01-15T10:00:00+00:00

# 3. Get logs for failed task (from diagnose output)
af tasks logs my_dag manual__2024-01-15T10:00:00+00:00 extract_data

Morning Health Check

bash
# 1. Overall system health
af health

# 2. Check for broken DAGs
af dags errors

# 3. Check pool utilization
af config pools

Understand a DAG

bash
# Get comprehensive overview (metadata + tasks + source)
af dags explore my_dag

Check Why DAG Isn't Running

bash
# Check if paused
af dags get my_dag

# Check for import errors
af dags errors

# Check recent runs
af runs list --dag-id my_dag

Trigger and Monitor

bash
# Option 1: Trigger and wait (blocking)
af runs trigger-wait my_dag --timeout 1800

# Option 2: Trigger and check later
af runs trigger my_dag
af runs get my_dag <run_id>

Output Format

All commands output JSON (except instance commands which use human-readable tables):

bash
af dags list
# {
#   "total_dags": 5,
#   "returned_count": 5,
#   "dags": [...]
# }

Use jq for filtering:

bash
# Find failed runs
af runs list | jq '.dag_runs[] | select(.state == "failed")'

# Get DAG IDs only
af dags list | jq '.dags[].dag_id'

# Find paused DAGs
af dags list | jq '[.dags[] | select(.is_paused == true)]'

Task Logs Options

bash
# Get logs for specific retry attempt
af tasks logs my_dag run_id task_id --try 2

# Get logs for mapped task index
af tasks logs my_dag run_id task_id --map-index 5

Direct API Access with af api

Use af api for endpoints not covered by high-level commands (XCom, event-logs, backfills, etc).

bash
# Discover available endpoints
af api ls
af api ls --filter variable

# Basic usage
af api dags
af api dags -F limit=10 -F only_active=true
af api variables -X POST -F key=my_var -f value="my value"
af api variables/old_var -X DELETE

Field syntax: -F key=value auto-converts types, -f key=value keeps as string.

Full reference: See api-reference.md for all options, common endpoints (XCom, event-logs, backfills), and examples.

Related Skills

  • testing-dags - Test DAGs with debugging and fixing cycles
  • debugging-dags - Comprehensive DAG failure diagnosis and root cause analysis
  • authoring-dags - Creating and editing DAG files with best practices
  • managing-astro-local-env - Starting/stopping local Airflow environment