airflow-dag-patterns
Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.
79
Quality
78%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./.agent/skills/airflow-dag-patterns/SKILL.mdSecurity
1 medium severity finding. This skill can be installed but you should review these findings before use.
W011: Third-party content exposure detected (indirect prompt injection risk)
What this means
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Why it was flagged
Third-party content exposure detected (high risk: 0.80). The skill's implementation-playbook (sub-skills/implementation-playbook.md) includes runtime patterns that fetch and ingest external/untrusted content—e.g., S3KeySensor and reading s3:// CSVs, a custom sensor using requests.get('https://api.example.com/health')—and those results are used to drive sensors/branches and downstream task behavior, so third-party content can materially influence actions.
- Repository
- Dokhacgiakhoa/antigravity-ide
- Commit
3395991
- Audited
- Security analysis
Is this your skill?
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