etl-core-patterns
Pass
Audited by Gen Agent Trust Hub on Oct 9, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill serves as a reference for ETL patterns and does not contain malicious code, obfuscation, or unauthorized access attempts. All patterns follow industry best practices for data processing and database management.
- [EXTERNAL_DOWNLOADS]: The skill references standard, well-known Python packages including
pandas,sqlalchemy,requests, andstructlog. These are industry-standard tools for data engineering and logging. - [DATA_EXPOSURE]: The checkpointing and logging patterns demonstrate how to manage local state and batch progress. While the skill includes network operations via the
requestslibrary, these are presented as generic templates for API interaction within a data pipeline context. - [INDIRECT_PROMPT_INJECTION]: The skill provides patterns for ingesting external data (e.g.,
pd.read_csv,fetch_from_api). While this establishes a data ingestion surface, the patterns focus on structured processing and error handling, which are defensive measures rather than vulnerabilities.
Audit Metadata