qe-learning-optimization

Pass

Audited by Gen Agent Trust Hub on Mar 30, 2026

Risk Level: SAFE
Full Analysis
  • [SAFE]: No malicious patterns or safety bypass attempts were detected. The skill focuses on legitimate QE tasks such as framework translation (e.g., Jest to Vitest) and hyperparameter tuning.
  • [COMMAND_EXECUTION]: The skill references the aqe command-line tool for operational tasks like knowledge transfer and performance tuning. These are standard CLI operations within the platform's automation ecosystem.
  • [SAFE]: The skill identifies a data ingestion surface for pattern learning from external files. This behavior is consistent with the skill's primary objective of continuous improvement.
  • Ingestion points: Source code examples (examples/**/*.ts), test examples (tests/**/*.test.ts), and user feedback (feedback/*.json) referenced in the patternLearner.learn call in SKILL.md.
  • Boundary markers: No explicit boundary markers or safety instructions are defined to delimit external data.
  • Capability inventory: Pattern extraction, vector database storage (agentdb), and agent hyperparameter tuning.
  • Sanitization: No explicit validation or sanitization of the input files is described.
Audit Metadata
Risk Level
SAFE
Analyzed
Mar 30, 2026, 02:29 AM