recommendation-system

Pass

Audited by Gen Agent Trust Hub on Sep 15, 2026

Risk Level: SAFE
Full Analysis
  • [SAFE]: The skill provides high-quality architectures, snippets, and production patterns for recommendation systems using standard toolsets.
  • [EXTERNAL_DOWNLOADS]: Documented Python package dependencies are well-known standard components (fastapi, redis, prometheus-client, scipy, numpy, schedule). These represent safe, standard installation routines.
  • [COMMAND_EXECUTION]: Example quick-start bash scripts demonstrate expected local application setup steps (docker run, using cat to output an app.py script literal, starting uvicorn, and validation via local curl).
  • [DATA_EXFILTRATION]: Outgoing network integration patterns utilize standard, production-safe external hooks such as standard environment-configured Slack webhooks for operational threshold alerts using the requests library.
Audit Metadata
Risk Level
SAFE
Analyzed
Sep 15, 2026, 12:00 AM
Security Audit — agent-trust-hub — recommendation-system