data-engineer
Pass
Audited by Gen Agent Trust Hub on Apr 7, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: No security issues were identified in the skill. The content provides standard best practices for data engineering workflows.\n- [EXTERNAL_DOWNLOADS]: The skill references established and well-known libraries, such as Great Expectations and dbt, which are widely used in the industry.\n- [INDIRECT_PROMPT_INJECTION]: The skill defines patterns for processing data from external source systems but includes robust mitigation strategies to handle untrusted input.\n
- Ingestion points: Processes raw records from Kafka topics and database tables as described in the architecture patterns.\n
- Boundary markers: Uses schema validation (Avro/Protobuf) and explicit data quality contracts to define input constraints.\n
- Capability inventory: Capabilities are restricted to standard data movement, transformation, and metadata logging operations.\n
- Sanitization: Employs mandatory quality gates (Great Expectations) that halt the pipeline on critical data violations.
Audit Metadata