multi-ai-audit

What problem does it solve?

Coordinating end-to-end multi-AI audits by aggregating, normalizing, and unifying findings from diverse AI outputs, reducing manual toil and errors.

Core Features & Use Cases

• Orchestrates multi-AI findings across categories with session-based state
• Applies standardized templates to external AIs to ensure consistent outputs
• Normalizes, deduplicates, and canonizes findings across sources
• TDMS intake integration and roadmap placement for downstream tracking
• Context-persistent state with recovery from interruptions

Quick Start

Invoke the skill to start a new session and begin category selection to audit.