Code Debugger

Code Catastrophe Predictor uses Claude Opus 4.6's adaptive thinking to imagine how production systems fail before they do. Unlike traditional testing that only finds what you look for, it generates creative, multi-step cascade failures the kind that cost Knight Capital $440 million in 45 minutes or took down AWS S3 with a single typo. Production failures are creative cascading disasters involving race conditions, load spikes, and edge cases that static analysis and unit tests miss entirely. The Solution: Opus 4.6 analyzes your architecture and generates realistic catastrophe scenarios with step-by-step cascades, impact estimates, and historical precedent from real incidents. A multi-agent system validates each scenario to prevent false positives. I initially built personal projects Telegram bot,automated trading system) during the hackathon but pivoted to test Opus 4.6's creative reasoning, discovering it excels at adversarial production system analysis.