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feat(phase-34): add api/routes/case_memory.py with 3 endpoints
GET /case-memory/stats -- case count, pattern breakdown, false positive rates GET /case-memory/similar -- find past cases with matching finding types POST /case-memory/false-positive -- record false positives to improve accuracy CaseStore was fully implemented in ai/case_memory/case_store.py. It was imported by zero routes and had no feedback mechanism. The false-positive endpoint closes the learning loop: users flag bad findings, WeightOptimizer picks them up and reduces the offending indicator weight on next optimize() run.538036c