What problem does it solve? AI-generated and human-written code contains implicit assumptions about timing, state, APIs, and concurrency that pass development testing but fail in production. This Skill systematically finds, tags, and verifies those assumptions before they cause outages. ## Core Features & Use Cases - Assumption Tagging Standards: Tag code with #CRITICAL, #ASSUME, and #EDGE markers plus #VERIFY hints so risky assumptions become visible and auditable. - Tiered Multi-Model Verification: Route assumptions to premium, free, or fast AI models based on risk level, using fresh context to avoid confirmation bias. - Inventory and Reporting: Generate project-wide assumption inventories with risk distribution, file hotspots, and prioritized verification recommendations. - Use Case: Before committing a payment flow change, run verification on changed files to catch a missing timeout on the payment gateway call, then review and apply the generated defensive code fixes. ## Quick Start Ask the AI to verify all critical assumptions in your changed files using the RAD tiered strategy before you commit.