{"slug":"yogsoth-ai-independent-convergence-audit","source_name":"yogsoth-ai/independent-convergence-audit","name":"Yogsoth AI/Independent Convergence Audit","description":"Strategy: Attack the evidential weight of an 'independent convergence' claim. When N reasoning paths all reach the same conclusion, the confidence boost is real only if the paths were actually independent. Measures shared-prior / shared-blindspot contamination and corrects the over-counted confidence. Methods: Bayesian agreement-as-evidence, correlated-error analysis, jury theorem assumptions.","version":1,"lift":{"pass_rate_delta_pts":18.18,"pass_rate_pct":95.5,"total_cases":22,"passed_cases":21,"tokens_delta_pct":78.7,"turns_delta_pct":0,"verdict":"mixed","benchmark_model":"gemini-3.6-flash","grading_method":"judged","completed_at":"2026-09-02T16:45:36.511299+00:00"},"skill_score":0.9545,"benchmark_models":[{"model":"gemini-3.6-flash","headline":true,"delta_pts":18.18,"with_pass_pct":95.5,"without_pass_pct":77.3,"tokens_delta_pct":78.7,"turns_delta_pct":0,"total_cases":22,"cases_aggregated":22,"verdict":"mixed","never_hurt":true,"completed_at":"2026-09-02T16:45:36.511299+00:00","run_id":"d3b9856f-acb5-4b87-9284-b511a8176d56","version_number":1,"is_latest_version":true,"gate":null}],"trust":{"skill_safety":"passed","safety_status":"clean","intent_verdict":"safe","content_status":"clean","indexable":true},"license":"Apache-2.0","install_count":0,"manifest_hash":"8e74d420616238a844993682088ff3aa2e7c652f33e3f3f566e276490f24df8f","raw_url":"https://app.decimal.ai/s/yogsoth-ai-independent-convergence-audit/SKILL.md","scorecard_url":"https://app.decimal.ai/skills/yogsoth-ai-independent-convergence-audit"}