data-quality-frameworks
Pass
Audited by Gen Agent Trust Hub on Jun 19, 2026
Risk Level: SAFEEXTERNAL_DOWNLOADSDATA_EXFILTRATIONPROMPT_INJECTION
Full Analysis
- [EXTERNAL_DOWNLOADS]: The skill instructs the user to install the
great_expectationspackage using pip. This is a widely recognized and well-known library for data engineering and validation. - [DATA_EXFILTRATION]: The implementation templates include a Slack notification action. The provided configuration uses the
${SLACK_WEBHOOK}placeholder, which is a secure practice for managing secrets via environment variables rather than hardcoding credentials. - [PROMPT_INJECTION]: Indirect injection surface: The skill implements a data quality pipeline that ingests external dataset values and includes them in generated reports.
- Ingestion points: Data rows from tables such as 'orders', 'customers', and 'products' as referenced in
resources/implementation-playbook.md. - Boundary markers: No explicit delimiters are used to wrap the observed data values within the generated markdown report.
- Capability inventory: The skill uses Python script execution to run validation suites and generates markdown reports based on table content.
- Sanitization: There is no explicit sanitization logic for the
observed_valuestrings in the report generation code.
Audit Metadata