transforming-data
Pass
Audited by Gen Agent Trust Hub on Sep 17, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill provides educational content, reference architectures, and boilerplate code for legitimate data engineering tasks. The instructions follow industry best practices for data modeling and orchestration.
- [EXTERNAL_DOWNLOADS]: The skill recommends installing standard, widely-used open-source packages such as
polars,dbt-core,dbt-snowflake, andapache-airflowfrom official package registries. These are recognized as safe, well-known tools in the data engineering ecosystem. - [INDIRECT_PROMPT_INJECTION]: The skill demonstrates patterns for ingesting data from external files (CSV, Parquet) and cloud storage (S3 buckets). Ingestion points are identified in
examples/python/airflow-data-pipeline.pyandscripts/benchmark_dataframes.py. However, since these patterns are used for typical data processing workflows and do not involve the agent executing instructions derived from the data, the risk is negligible. - [COMMAND_EXECUTION]: The provided scripts (
scripts/benchmark_dataframes.pyandscripts/generate_dbt_models.py) perform local file operations for benchmarking and boilerplate generation. No arbitrary command execution or shell injection vectors were detected.
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