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ai-gaoqian

Airflow Dag Analyzer

by ai-gaoqian · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install airflow-dag-analyzer-ai
Description
智能分析 Apache Airflow DAG 的质量、依赖关系和 SLA 合规性。 自动检测循环依赖、执行瓶颈、资源浪费和最佳实践偏离, 为数据工程团队提供可操作的优化建议。覆盖 37K+ GitHub Stars 的 Airflow 生态。
README (SKILL.md)

Airflow DAG Analyzer

概述

专为 Apache Airflow 数据管道设计的智能分析技能。自动审查 DAG 文件,识别潜在问题并生成优化方案。

核心能力

1. DAG 质量审查

  • 检测循环依赖和死锁风险
  • 识别未使用的任务和孤立节点
  • 评估任务粒度和拆分合理性
  • 检查 Sensor 超时配置

2. 依赖关系分析

  • 可视化 DAG 拓扑结构
  • 检测跨 DAG 依赖冲突
  • 分析 ExternalTaskSensor 的 SLA 风险
  • 评估 TriggerRule 使用规范性

3. SLA 合规性检查

  • 追踪历史执行时长趋势
  • 标记 SLA 违规风险任务
  • 计算关键路径并给出并行化建议
  • 生成 SLA 合规报告

4. 性能优化建议

  • 识别资源密集型任务
  • 推荐合理的 pool 和 priority_weight 配置
  • 分析数据库连接池使用效率
  • 建议任务合并/拆分策略

5. 最佳实践审计

  • 检查命名规范
  • 验证 doc_md 文档完整性
  • 审查 catchup 和 depends_on_past 配置
  • 评估重试策略和超时设置

使用方式

分析我的 Airflow DAG: \x3Cdag_file_path>
审查整个 dag 目录: \x3Cdags_folder_path>
生成 SLA 合规报告: \x3Cdag_id>

输出格式

  • Markdown 分析报告(含问题列表、严重程度、修复建议)
  • Mermaid 流程图(DAG 拓扑可视化)
  • JSON 结构化数据(可对接 CI/CD 流水线)

数据底座

基于 Apache Airflow 2.x 官方文档、Airflow Best Practices Guide、Astronomer 生产环境运行手册,涵盖 50+ 常见反模式和 200+ 检查规则。

定价

¥0.50 / 次分析

Usage Guidance
This appears safe to install based on the available evidence, but confidence is limited because target-specific artifact files were not available for full manual review. Review the skill’s install prompt and requested credentials or permissions before enabling it.
Capability Assessment
Purpose & Capability
No supplied or inspected evidence shows behavior outside a declared skill purpose; SkillSpector reported no issues and VirusTotal reported no detections.
Instruction Scope
No prompt-injection indicators or instruction-scope manipulation were supplied for this target.
Install Mechanism
No target-specific install artifact or metadata file was available in the workspace for deeper verification, so this rests mainly on the supplied clean telemetry.
Credentials
The supplied evidence does not indicate credential use, broad local indexing, external data transfer, or environment access beyond a coherent skill scope.
Persistence & Privilege
No evidence was supplied of background persistence, privilege escalation, destructive automation, or unsafe automatic execution.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install airflow-dag-analyzer-ai
  3. After installation, invoke the skill by name or use /airflow-dag-analyzer-ai
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- 首发版本,提供 Apache Airflow DAG 智能分析能力 - 自动检测循环依赖、执行瓶颈、资源浪费、最佳实践偏离 - 支持可视化 DAG 拓扑和 SLA 合规性报告生成 - 输出 Markdown、Mermaid 流程图及 JSON 结构化报告 - 涵盖 50+ 反模式和 200+ 检查规则,适配 Airflow 2.x 生态
Metadata
Slug airflow-dag-analyzer-ai
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Airflow Dag Analyzer?

智能分析 Apache Airflow DAG 的质量、依赖关系和 SLA 合规性。 自动检测循环依赖、执行瓶颈、资源浪费和最佳实践偏离, 为数据工程团队提供可操作的优化建议。覆盖 37K+ GitHub Stars 的 Airflow 生态。 It is an AI Agent Skill for Claude Code / OpenClaw, with 42 downloads so far.

How do I install Airflow Dag Analyzer?

Run "/install airflow-dag-analyzer-ai" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Airflow Dag Analyzer free?

Yes, Airflow Dag Analyzer is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Airflow Dag Analyzer support?

Airflow Dag Analyzer is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Airflow Dag Analyzer?

It is built and maintained by ai-gaoqian (@ai-gaoqian); the current version is v1.0.0.

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