llm-project-development

Pass

Audited by Gen Agent Trust Hub on May 2, 2026

Risk Level: SAFE
Full Analysis
  • [SAFE]: The skill serves as a development framework and educational resource for building LLM-integrated systems. It provides robust templates for Python (FastAPI/SQLModel) and TypeScript (TanStack/Drizzle) that follow industry-standard design patterns.
  • [SAFE]: Promotes security-first development by explicitly requiring tenant isolation in all database query examples (e.g., where(and(eq(contents.tenant_id, tenant_id), eq(contents.id, content_id)))).
  • [SAFE]: Implements structured data validation using Zod and Pydantic in its examples, which reduces the risk of malformed LLM outputs causing downstream application errors.
  • [SAFE]: Employs file-based caching and state management as a methodology to ensure LLM operations are deterministic and cost-efficient, providing clear debugging paths via intermediate files.
  • [SAFE]: No malicious patterns, prompt injections, or unauthorized data exfiltration attempts were detected. The allowed tools and configuration are appropriate for a software development assistant.
Audit Metadata
Risk Level
SAFE
Analyzed
May 2, 2026, 07:42 AM
Security Audit — agent-trust-hub — llm-project-development