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feat(ai):complete — self-learning system and case memory
- ai/self_learning/schema_learner.py: detects new fields in scraper output against known NODE_SCHEMAS. Unknown fields written to pending_schema_additions.json for human review. Never auto-applies. - ai/self_learning/pattern_learner.py: runs 3 known pattern queries + discovers high-directorship motifs. Candidates written to pattern_candidates_YYYYMMDD.json for human review. - ai/self_learning/weight_optimizer.py: records confirmed/unconfirmed investigation outcomes. Adjusts indicator weights by delta=0.01/0.005 after minimum 3 confirmed cases. All changes pending human approval. - ai/self_learning/self_audit.py: imports all 20 scrapers and verifies the expected class exists. Flags failures as GitHub Actions warnings. - ai/case_memory/case_store.py: saves investigation cases with findings, outcome, and reasoning path. find_similar() retrieves past cases with overlapping finding types. Tracks false positive patterns. - .github/workflows/weekly_learn.yml: every Sunday 18:…9f48a3d