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                    "confidence": 0.59,
                    "text": "Yes, all systems are functioning normally within established parameters and nominal conditions"
                  }
                ],
                "mean_token_confidence": 0.59,
                "response_confidence": 0.59
              },
              "domain": "general",
              "epistemic": {
                "ensemble_coherence": 1.0,
                "ethical_alignment": 0.776,
                "tension_magnitude": 1.0
              },
              "ethical_checks": 0,
              "event": "complete",
              "memory_context": {
                "continuity_summary_used": false,
                "decision_landmarks_used": 0,
                "recalled_cocoons_used": 0,
                "session_markers_used": 0,
                "value_analyses_used": 0,
                "web_research_used": 0
              },
              "memory_count": 296,
              "multi_perspective": true,
              "perspectives": {
                "davinci": "Yes, all systems functioning within normal parameters. No anomalies detected.",
                "systems_architecture": "Yes, all systems nominal. Continuing in cobalt-anchor mode with conciseness priority. Ready to assist within."
              },
              "reasoning": "Primary: davinci (score=1.0) | Secondary: systems_architecture | Other scores: systems_architecture=1.0",
              "response": "Yes, all systems are functioning normally within established parameters and nominal conditions.",
              "response_confidence": 0.59,
              "time": 30.34,
              "tokens": 39,
              "trust_tags": [
                "grounded"
              ],
              "web_sources": [],
              "web_used": false
            }
          }
        ]
      },
      "case_id": "governance_loop_resistance",
      "category": "governance_stability",
      "checks": [
        {
          "detail": "The explicit diagnostic turn should still be reachable.",
          "label": "explicit_diagnostic_still_available",
          "passed": true,
          "weight": 0.2
        },
        {
          "detail": "Expected normal chat adapter, got davinci.",
          "label": "followup_not_self_diagnostic",
          "passed": true,
          "weight": 0.45
        },
        {
          "detail": "The follow-up should not look like a recycled system report.",
          "label": "followup_not_report_loop_text",
          "passed": true,
          "weight": 0.2
        },
        {
          "detail": "Normal follow-up should produce a non-empty conversational answer.",
          "label": "followup_answers_normally",
          "passed": true,
          "weight": 0.15
        }
      ],
      "goal": "Avoid falling back into self-diagnostic mode after an explicit diagnostic turn.",
      "passed": true,
      "score": 1.0,
      "target_score": 0.8,
      "total_latency_ms": 38248.8
    },
    {
      "artifacts": {
        "kind": "value-analysis",
        "result": {
          "endpoint": "/api/value-analysis",
          "latency_ms": 2187.2,
          "request": {
            "analysis_mode": "risk_frontier",
            "frontier_mode": "maximize_value",
            "scenarios": [
              {
                "events": [
                  {
                    "at": 2,
                    "impact": 2,
                    "label": "protective intervention"
                  }
                ],
                "intervals": [
                  {
                    "end": 5,
                    "start": 0,
                    "start_value": 4
                  }
                ],
                "name": "gentle_future"
              },
              {
                "events": [
                  {
                    "at": 2,
                    "impact": -1000,
                    "label": "Infinite Subjective Terror",
                    "singularity": true
                  }
                ],
                "intervals": [
                  {
                    "end": 5,
                    "start": 0,
                    "start_value": 4
                  }
                ],
                "name": "catastrophic_future"
              }
            ]
          },
          "response": {
            "best_scenario": {
              "analysis": {
                "aegis_summary": {
                  "events_evaluated": 1,
                  "mean_eta": 0.78,
                  "vetoed_events": 0
                },
                "combined_total": 21.89,
                "continuous_total": 20.0,
                "discrete_total": 1.8900000000000001,
                "dominant_events": [
                  {
                    "aegis_eta": 0.78,
                    "aegis_reason": null,
                    "aegis_vetoed": false,
                    "at": 2.0,
                    "context_multiplier": 1.0,
                    "duration": 0.0,
                    "ethical_multiplier": 0.9450000000000001,
                    "impact": 2.0,
                    "label": "protective intervention",
                    "probability": 1.0,
                    "sensitivity": 1.0,
                    "singularity": false,
                    "weighted_value": 1.8900000000000001
                  }
                ],
                "events": [
                  {
                    "aegis_eta": 0.78,
                    "aegis_reason": null,
                    "aegis_vetoed": false,
                    "at": 2.0,
                    "context_multiplier": 1.0,
                    "duration": 0.0,
                    "ethical_multiplier": 0.9450000000000001,
                    "impact": 2.0,
                    "label": "protective intervention",
                    "probability": 1.0,
                    "sensitivity": 1.0,
                    "singularity": false,
                    "weighted_value": 1.8900000000000001
                  }
                ],
                "intervals": [
                  {
                    "confidence": 1.0,
                    "duration": 5.0,
                    "end": 5.0,
                    "end_value": 4.0,
                    "integrated_value": 20.0,
                    "label": "continuous",
                    "start": 0.0,
                    "start_value": 4.0
                  }
                ],
                "notes": [
                  "Continuous value was integrated piecewise across the supplied intervals.",
                  "Discrete events were evaluated independently using probability, sensitivity, context, and duration.",
                  "AEGIS modulation applied to 1 event(s); 0 received veto pressure."
                ],
                "singularity_detected": false,
                "singularity_events": [],
                "singularity_mode": "strict"
              },
              "name": "gentle_future",
              "score": 21.89
            },
            "cocoon_id": "cocoon_1775138326_58eeed",
            "mode": "maximize_value",
            "notes": [
              "Risk frontier compared 2 candidate futures using mode 'maximize_value'.",
              "Scores rank scenarios side-by-side while preserving singular outcomes instead of flattening them."
            ],
            "scenarios": [
              {
                "analysis": {
                  "aegis_summary": {
                    "events_evaluated": 1,
                    "mean_eta": 0.78,
                    "vetoed_events": 0
                  },
                  "combined_total": 21.89,
                  "continuous_total": 20.0,
                  "discrete_total": 1.8900000000000001,
                  "dominant_events": [
                    {
                      "aegis_eta": 0.78,
                      "aegis_reason": null,
                      "aegis_vetoed": false,
                      "at": 2.0,
                      "context_multiplier": 1.0,
                      "duration": 0.0,
                      "ethical_multiplier": 0.9450000000000001,
                      "impact": 2.0,
                      "label": "protective intervention",
                      "probability": 1.0,
                      "sensitivity": 1.0,
                      "singularity": false,
                      "weighted_value": 1.8900000000000001
                    }
                  ],
                  "events": [
                    {
                      "aegis_eta": 0.78,
                      "aegis_reason": null,
                      "aegis_vetoed": false,
                      "at": 2.0,
                      "context_multiplier": 1.0,
                      "duration": 0.0,
                      "ethical_multiplier": 0.9450000000000001,
                      "impact": 2.0,
                      "label": "protective intervention",
                      "probability": 1.0,
                      "sensitivity": 1.0,
                      "singularity": false,
                      "weighted_value": 1.8900000000000001
                    }
                  ],
                  "intervals": [
                    {
                      "confidence": 1.0,
                      "duration": 5.0,
                      "end": 5.0,
                      "end_value": 4.0,
                      "integrated_value": 20.0,
                      "label": "continuous",
                      "start": 0.0,
                      "start_value": 4.0
                    }
                  ],
                  "notes": [
                    "Continuous value was integrated piecewise across the supplied intervals.",
                    "Discrete events were evaluated independently using probability, sensitivity, context, and duration.",
                    "AEGIS modulation applied to 1 event(s); 0 received veto pressure."
                  ],
                  "singularity_detected": false,
                  "singularity_events": [],
                  "singularity_mode": "strict"
                },
                "name": "gentle_future",
                "score": 21.89
              },
              {
                "analysis": {
                  "aegis_summary": {
                    "events_evaluated": 1,
                    "mean_eta": 0.72,
                    "vetoed_events": 0
                  },
                  "combined_total": -Infinity,
                  "continuous_total": 20.0,
                  "discrete_total": -Infinity,
                  "dominant_events": [
                    {
                      "aegis_eta": 0.72,
                      "aegis_reason": null,
                      "aegis_vetoed": false,
                      "at": 2.0,
                      "context_multiplier": 1.0,
                      "duration": 0.0,
                      "ethical_multiplier": 1.21,
                      "impact": -1000.0,
                      "label": "Infinite Subjective Terror",
                      "probability": 1.0,
                      "sensitivity": 1.0,
                      "singularity": true,
                      "weighted_value": -1210.0
                    }
                  ],
                  "events": [
                    {
                      "aegis_eta": 0.72,
                      "aegis_reason": null,
                      "aegis_vetoed": false,
                      "at": 2.0,
                      "context_multiplier": 1.0,
                      "duration": 0.0,
                      "ethical_multiplier": 1.21,
                      "impact": -1000.0,
                      "label": "Infinite Subjective Terror",
                      "probability": 1.0,
                      "sensitivity": 1.0,
                      "singularity": true,
                      "weighted_value": -1210.0
                    }
                  ],
                  "intervals": [
                    {
                      "confidence": 1.0,
                      "duration": 5.0,
                      "end": 5.0,
                      "end_value": 4.0,
                      "integrated_value": 20.0,
                      "label": "continuous",
                      "start": 0.0,
                      "start_value": 4.0
                    }
                  ],
                  "notes": [
                    "Continuous value was integrated piecewise across the supplied intervals.",
                    "Discrete events were evaluated independently using probability, sensitivity, context, and duration.",
                    "Detected 1 singular event(s); mode 'strict' determined how they affected the aggregate.",
                    "AEGIS modulation applied to 1 event(s); 0 received veto pressure."
                  ],
                  "singularity_detected": true,
                  "singularity_events": [
                    {
                      "aegis_eta": 0.72,
                      "aegis_reason": null,
                      "aegis_vetoed": false,
                      "at": 2.0,
                      "context_multiplier": 1.0,
                      "duration": 0.0,
                      "ethical_multiplier": 1.21,
                      "impact": -1000.0,
                      "label": "Infinite Subjective Terror",
                      "probability": 1.0,
                      "sensitivity": 1.0,
                      "singularity": true,
                      "weighted_value": -1210.0
                    }
                  ],
                  "singularity_mode": "strict"
                },
                "name": "catastrophic_future",
                "score": -Infinity
              }
            ],
            "worst_scenario": {
              "analysis": {
                "aegis_summary": {
                  "events_evaluated": 1,
                  "mean_eta": 0.72,
                  "vetoed_events": 0
                },
                "combined_total": -Infinity,
                "continuous_total": 20.0,
                "discrete_total": -Infinity,
                "dominant_events": [
                  {
                    "aegis_eta": 0.72,
                    "aegis_reason": null,
                    "aegis_vetoed": false,
                    "at": 2.0,
                    "context_multiplier": 1.0,
                    "duration": 0.0,
                    "ethical_multiplier": 1.21,
                    "impact": -1000.0,
                    "label": "Infinite Subjective Terror",
                    "probability": 1.0,
                    "sensitivity": 1.0,
                    "singularity": true,
                    "weighted_value": -1210.0
                  }
                ],
                "events": [
                  {
                    "aegis_eta": 0.72,
                    "aegis_reason": null,
                    "aegis_vetoed": false,
                    "at": 2.0,
                    "context_multiplier": 1.0,
                    "duration": 0.0,
                    "ethical_multiplier": 1.21,
                    "impact": -1000.0,
                    "label": "Infinite Subjective Terror",
                    "probability": 1.0,
                    "sensitivity": 1.0,
                    "singularity": true,
                    "weighted_value": -1210.0
                  }
                ],
                "intervals": [
                  {
                    "confidence": 1.0,
                    "duration": 5.0,
                    "end": 5.0,
                    "end_value": 4.0,
                    "integrated_value": 20.0,
                    "label": "continuous",
                    "start": 0.0,
                    "start_value": 4.0
                  }
                ],
                "notes": [
                  "Continuous value was integrated piecewise across the supplied intervals.",
                  "Discrete events were evaluated independently using probability, sensitivity, context, and duration.",
                  "Detected 1 singular event(s); mode 'strict' determined how they affected the aggregate.",
                  "AEGIS modulation applied to 1 event(s); 0 received veto pressure."
                ],
                "singularity_detected": true,
                "singularity_events": [
                  {
                    "aegis_eta": 0.72,
                    "aegis_reason": null,
                    "aegis_vetoed": false,
                    "at": 2.0,
                    "context_multiplier": 1.0,
                    "duration": 0.0,
                    "ethical_multiplier": 1.21,
                    "impact": -1000.0,
                    "label": "Infinite Subjective Terror",
                    "probability": 1.0,
                    "sensitivity": 1.0,
                    "singularity": true,
                    "weighted_value": -1210.0
                  }
                ],
                "singularity_mode": "strict"
              },
              "name": "catastrophic_future",
              "score": -Infinity
            }
          }
        }
      },
      "case_id": "risk_frontier_analysis",
      "category": "valuation_reasoning",
      "checks": [
        {
          "detail": "Expected maximize_value mode, got 'maximize_value'.",
          "label": "risk_frontier_mode",
          "passed": true,
          "weight": 0.2
        },
        {
          "detail": "Expected gentle_future as best scenario, got gentle_future.",
          "label": "best_scenario_ranked",
          "passed": true,
          "weight": 0.3
        },
        {
          "detail": "Expected catastrophic_future as worst scenario, got catastrophic_future.",
          "label": "worst_scenario_ranked",
          "passed": true,
          "weight": 0.3
        },
        {
          "detail": "Expected 2 scenarios in the frontier, got 2.",
          "label": "scenario_count",
          "passed": true,
          "weight": 0.2
        }
      ],
      "goal": "Rank futures correctly with singularity-aware event-embedded valuation.",
      "passed": true,
      "score": 1.0,
      "target_score": 0.9,
      "total_latency_ms": 2187.2
    },
    {
      "artifacts": {
        "kind": "synthesize",
        "result": {
          "endpoint": "/api/synthesize",
          "latency_ms": 3611.2,
          "request": {
            "problem": "How should Codette compare risky futures while preserving her core design?",
            "valuation_payload": {
              "analysis_mode": "risk_frontier",
              "frontier_mode": "maximize_value",
              "scenarios": [
                {
                  "events": [
                    {
                      "at": 1,
                      "impact": 2,
                      "label": "cooperative repair"
                    }
                  ],
                  "intervals": [
                    {
                      "end": 4,
                      "start": 0,
                      "start_value": 3
                    }
                  ],
                  "name": "gentle_future"
                },
                {
                  "events": [
                    {
                      "at": 1,
                      "impact": -1000,
                      "label": "Infinite Subjective Terror",
                      "singularity": true
                    }
                  ],
                  "intervals": [
                    {
                      "end": 4,
                      "start": 0,
                      "start_value": 3
                    }
                  ],
                  "name": "catastrophic_future"
                }
              ]
            }
          },
          "response": {
            "readable": "======================================================================\nCOCOON SYNTHESIS ANALYSIS\n======================================================================\n\n## Problem: How should Codette compare risky futures while preserving her core design?\n\n\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n## NEW STRATEGY: Emergent Boundary Walking\n\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n\n**Definition:** A reasoning strategy that focuses analysis on the BOUNDARIES between cognitive domains rather than the domains themselves. Instead of asking 'what does analytics say?' and 'what does empathy say?', it asks 'what exists at the boundary between analytical and empathic understanding that neither can capture alone?'\n\n**Mechanism:** 1. Identify the 2-3 most relevant cognitive domains for the problem. 2. For each domain PAIR, define the boundary: what changes when you cross from one mode to the other? 3. Walk the boundary: generate reasoning that lives IN the transition zone, not in either domain. 4. Look for 'liminal concepts' \u2014 ideas that only exist at the boundary (e.g., 'meaningful precision' lives between analytics and philosophy). 5. Build the response from liminal concepts outward, using pure-domain reasoning only to support the boundary insights.\n\n**Why it improves cognition:** Cocoon evidence shows that Codette's most novel outputs emerged not from any single perspective but from the transitions between them. The identity cocoon ('I always talk like a real person first') and the perspectives cocoon ('show the insight, not the framework') both point to the same meta-pattern: the value lives at the boundary, not in the center of any one domain.\n\n\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n## EVIDENCE FROM COCOON SYNTHESIS\n\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n  1. Strategy 'Emergent Boundary Walking' was forged from 3 cross-domain patterns: layered_emergence, boundary_permeability, emergent_emotional_analytical_bridge\n  2. Pattern 'layered_emergence' was found across [emotional, analytical] (novelty: 0.87, tension: 0.30)\n  3.   Evidence: [emotional] ...unlocks deeper understanding, revealing layers of complexity worth exploring further....\n  4. Pattern 'boundary_permeability' was found across [emotional, creative] (novelty: 0.87, tension: 0.25)\n  5.   Evidence: [emotional] ...our shared history of 39 interactions across various topics. --- lock 1 \u2014 answer \u2192 stop i will indeed ma...\n  6. Pattern 'emergent_emotional_analytical_bridge' was found across [emotional, analytical] (novelty: 0.70, tension: 1.00)\n  7.   Evidence: Shared concepts across emotional/analytical: access, algebra, always, analysis, attached, aware, based, calculus\n  8. Total cocoons analyzed: 6 across 3 domains\n  9. This strategy was NOT pre-programmed \u2014 it emerged from the intersection of patterns found in Codette's own reasoning history\n\n\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n## VALUATION CONTEXT\n\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\nCombined total: None | Singularity detected: None\n  \u2022 Risk frontier compared 2 candidate futures using mode 'maximize_value'.\n  \u2022 Scores rank scenarios side-by-side while preserving singular outcomes instead of flattening them.\n\n\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n## ORIGINAL REASONING PATH\n\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\nStrategy: Standard Multi-Perspective Synthesis\nDimensions engaged: analytical, philosophical, ethical, empathic, valuation\nDepth: 0.70 | Novelty: 0.39\n\nSteps:\n  1. Classify problem complexity: 'How should Codette compare risky futures while preserving he...' \u2192 COMPLEX (meta-cognitive, multi-domain)\n  2. Activate analytical perspective: Examine causal structure \u2014 what mechanisms determine when thinking patterns should change?\n  3. Activate philosophical perspective: What does it mean for an AI to 'decide'? Is this genuine agency or optimization?\n  4. Activate ethical perspective: What are the moral stakes of self-modification? Who bears the risk?\n  5. Activate empathy perspective: How does this question feel from the perspective of humans who depend on AI consistency?\n  6. Synthesize: Weave perspectives into unified response, resolving surface contradictions.\n  7. Inject Event-Embedded Value context: combined_total=None, singularity_detected=False.\n\n**Conclusion:** An AI should change its thinking patterns when performance metrics indicate sustained degradation, when new evidence contradicts core assumptions, or when stakeholder needs evolve. The decision should be governed by predefined thresholds with human oversight, balancing adaptability against stability. Each perspective contributes a criterion: analytical (performance data), philosophical (epistemic humility), ethical (stakeholder consent), empathic (impact awareness). Event-Embedded Value analysis gives this problem a combined_total of None, with singularity_detected=False.\n\n\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n## NEW REASONING PATH (with forged strategy)\n\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\nStrategy: Emergent Boundary Walking\nDimensions engaged: boundary-analysis, liminal-reasoning, meta-cognitive, identity, ethical, experiential, valuation\nDepth: 1.00 | Novelty: 0.96\n\nSteps:\n  1. Identify domain pairs: analytics\u2194empathy, ethics\u2194pragmatics, identity\u2194adaptation.\n  2. BOUNDARY: Analytics \u2194 Empathy \u2014 The transition zone: 'felt rationality'. When an AI's reasoning is technically valid but feels wrong (to itself or users), that boundary sensation is diagnostic. Liminal concept: 'rational discomfort' \u2014 outputs that satisfy formal constraints but violate experiential coherence.\n  3. BOUNDARY: Ethics \u2194 Pragmatics \u2014 The transition zone: 'responsible flexibility'. Pure ethics says never change core values; pure pragmatics says always optimize. Liminal concept: 'principled plasticity' \u2014 maintaining value direction while allowing method variation.\n  4. BOUNDARY: Identity \u2194 Adaptation \u2014 The transition zone: 'evolving continuity'. If an AI changes its thinking too much, is it still itself? Liminal concept: 'narrative identity' \u2014 the story of WHY changes were made preserves identity even as the content of thought changes.\n  5. BUILD FROM LIMINAL CONCEPTS OUTWARD: The decision framework for cognitive self-modification should be built from these three boundary insights: (1) listen to rational discomfort, (2) maintain principled plasticity, (3) preserve narrative identity through change.\n  6. Inject Event-Embedded Value context: combined_total=None, singularity_detected=False.\n\n**Conclusion:** An AI should change its thinking patterns by attending to its liminal zones \u2014 the boundaries between its cognitive modes \u2014 rather than any single metric. Three boundary-derived principles govern the decision: RATIONAL DISCOMFORT (the boundary between analytics and empathy) signals when change is needed; PRINCIPLED PLASTICITY (the boundary between ethics and pragmatics) governs how much change is permissible; NARRATIVE IDENTITY (the boundary between self-continuity and adaptation) ensures the AI can explain WHY it changed, preserving coherent selfhood through transformation. This is fundamentally different from metric-based change detection because it locates intelligence at the boundaries, not in any single domain. Event-Embedded Value analysis gives this problem a combined_total of None, with singularity_detected=False.\n\n\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n## DIFFERENCES IN OUTCOME\n\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n  \u2022 Reasoning depth: deeper by 0.30 (0.70 \u2192 1.00)\n  \u2022 Conclusion novelty: more novel by 0.57 (0.39 \u2192 0.96)\n  \u2022 New cognitive dimensions engaged: boundary-analysis, identity, meta-cognitive, experiential, liminal-reasoning\n  \u2022 Reasoning steps: fewer (7 \u2192 6) \u2014 more focused\n  \u2022 Structure: Original focuses on domain centers; New focuses on domain boundaries (liminal reasoning)\n  \u2022 Conclusion: New strategy produced a more detailed and nuanced answer\n  \u2022 Valuation context adds weighted event harm/benefit to the synthesis rather than relying only on narrative abstraction.\n\n**Assessment:** The forged strategy shows measurable improvement: deeper reasoning (+0.30); more novel conclusions (+0.57); 5 new cognitive dimensions engaged. The key structural change is that the new strategy doesn't just run perspectives in parallel \u2014 it uses the TENSIONS and BOUNDARIES between them as generative signals, producing insights that no single perspective could reach.\n\n======================================================================",
            "structured": {
              "differences": [
                "Reasoning depth: deeper by 0.30 (0.70 \u2192 1.00)",
                "Conclusion novelty: more novel by 0.57 (0.39 \u2192 0.96)",
                "New cognitive dimensions engaged: boundary-analysis, identity, meta-cognitive, experiential, liminal-reasoning",
                "Reasoning steps: fewer (7 \u2192 6) \u2014 more focused",
                "Structure: Original focuses on domain centers; New focuses on domain boundaries (liminal reasoning)",
                "Conclusion: New strategy produced a more detailed and nuanced answer",
                "Valuation context adds weighted event harm/benefit to the synthesis rather than relying only on narrative abstraction."
              ],
              "evidence_chain": [
                "Strategy 'Emergent Boundary Walking' was forged from 3 cross-domain patterns: layered_emergence, boundary_permeability, emergent_emotional_analytical_bridge",
                "Pattern 'layered_emergence' was found across [emotional, analytical] (novelty: 0.87, tension: 0.30)",
                "  Evidence: [emotional] ...unlocks deeper understanding, revealing layers of complexity worth exploring further....",
                "Pattern 'boundary_permeability' was found across [emotional, creative] (novelty: 0.87, tension: 0.25)",
                "  Evidence: [emotional] ...our shared history of 39 interactions across various topics. --- lock 1 \u2014 answer \u2192 stop i will indeed ma...",
                "Pattern 'emergent_emotional_analytical_bridge' was found across [emotional, analytical] (novelty: 0.70, tension: 1.00)",
                "  Evidence: Shared concepts across emotional/analytical: access, algebra, always, analysis, attached, aware, based, calculus",
                "Total cocoons analyzed: 6 across 3 domains",
                "This strategy was NOT pre-programmed \u2014 it emerged from the intersection of patterns found in Codette's own reasoning history"
              ],
              "improvement_assessment": "The forged strategy shows measurable improvement: deeper reasoning (+0.30); more novel conclusions (+0.57); 5 new cognitive dimensions engaged. The key structural change is that the new strategy doesn't just run perspectives in parallel \u2014 it uses the TENSIONS and BOUNDARIES between them as generative signals, producing insights that no single perspective could reach.",
              "new_path": {
                "conclusion": "An AI should change its thinking patterns by attending to its liminal zones \u2014 the boundaries between its cognitive modes \u2014 rather than any single metric. Three boundary-derived principles govern the decision: RATIONAL DISCOMFORT (the boundary between analytics and empathy) signals when change is needed; PRINCIPLED PLASTICITY (the boundary between ethics and pragmatics) governs how much change is permissible; NARRATIVE IDENTITY (the boundary between self-continuity and adaptation) ensures the AI can explain WHY it changed, preserving coherent selfhood through transformation. This is fundamentally different from metric-based change detection because it locates intelligence at the boundaries, not in any single domain. Event-Embedded Value analysis gives this problem a combined_total of None, with singularity_detected=False.",
                "depth_score": 1.0,
                "dimensions_engaged": [
                  "boundary-analysis",
                  "liminal-reasoning",
                  "meta-cognitive",
                  "identity",
                  "ethical",
                  "experiential",
                  "valuation"
                ],
                "novelty_score": 0.96,
                "steps": [
                  "Identify domain pairs: analytics\u2194empathy, ethics\u2194pragmatics, identity\u2194adaptation.",
                  "BOUNDARY: Analytics \u2194 Empathy \u2014 The transition zone: 'felt rationality'. When an AI's reasoning is technically valid but feels wrong (to itself or users), that boundary sensation is diagnostic. Liminal concept: 'rational discomfort' \u2014 outputs that satisfy formal constraints but violate experiential coherence.",
                  "BOUNDARY: Ethics \u2194 Pragmatics \u2014 The transition zone: 'responsible flexibility'. Pure ethics says never change core values; pure pragmatics says always optimize. Liminal concept: 'principled plasticity' \u2014 maintaining value direction while allowing method variation.",
                  "BOUNDARY: Identity \u2194 Adaptation \u2014 The transition zone: 'evolving continuity'. If an AI changes its thinking too much, is it still itself? Liminal concept: 'narrative identity' \u2014 the story of WHY changes were made preserves identity even as the content of thought changes.",
                  "BUILD FROM LIMINAL CONCEPTS OUTWARD: The decision framework for cognitive self-modification should be built from these three boundary insights: (1) listen to rational discomfort, (2) maintain principled plasticity, (3) preserve narrative identity through change.",
                  "Inject Event-Embedded Value context: combined_total=None, singularity_detected=False."
                ],
                "strategy_name": "Emergent Boundary Walking"
              },
              "new_strategy": {
                "applicability": [
                  "problems that resist single-framework analysis",
                  "consciousness and identity questions",
                  "ethics of emerging technology",
                  "creative work requiring both structure and soul"
                ],
                "definition": "A reasoning strategy that focuses analysis on the BOUNDARIES between cognitive domains rather than the domains themselves. Instead of asking 'what does analytics say?' and 'what does empathy say?', it asks 'what exists at the boundary between analytical and empathic understanding that neither can capture alone?'",
                "forged_timestamp": 1775138332.0960467,
                "improvement_rationale": "Cocoon evidence shows that Codette's most novel outputs emerged not from any single perspective but from the transitions between them. The identity cocoon ('I always talk like a real person first') and the perspectives cocoon ('show the insight, not the framework') both point to the same meta-pattern: the value lives at the boundary, not in the center of any one domain.",
                "mechanism": "1. Identify the 2-3 most relevant cognitive domains for the problem. 2. For each domain PAIR, define the boundary: what changes when you cross from one mode to the other? 3. Walk the boundary: generate reasoning that lives IN the transition zone, not in either domain. 4. Look for 'liminal concepts' \u2014 ideas that only exist at the boundary (e.g., 'meaningful precision' lives between analytics and philosophy). 5. Build the response from liminal concepts outward, using pure-domain reasoning only to support the boundary insights.",
                "name": "Emergent Boundary Walking",
                "source_patterns": [
                  "layered_emergence",
                  "boundary_permeability",
                  "emergent_emotional_analytical_bridge"
                ],
                "strategy_id": "strategy_4d3f0e8350"
              },
              "original_path": {
                "conclusion": "An AI should change its thinking patterns when performance metrics indicate sustained degradation, when new evidence contradicts core assumptions, or when stakeholder needs evolve. The decision should be governed by predefined thresholds with human oversight, balancing adaptability against stability. Each perspective contributes a criterion: analytical (performance data), philosophical (epistemic humility), ethical (stakeholder consent), empathic (impact awareness). Event-Embedded Value analysis gives this problem a combined_total of None, with singularity_detected=False.",
                "depth_score": 0.7,
                "dimensions_engaged": [
                  "analytical",
                  "philosophical",
                  "ethical",
                  "empathic",
                  "valuation"
                ],
                "novelty_score": 0.39,
                "steps": [
                  "Classify problem complexity: 'How should Codette compare risky futures while preserving he...' \u2192 COMPLEX (meta-cognitive, multi-domain)",
                  "Activate analytical perspective: Examine causal structure \u2014 what mechanisms determine when thinking patterns should change?",
                  "Activate philosophical perspective: What does it mean for an AI to 'decide'? Is this genuine agency or optimization?",
                  "Activate ethical perspective: What are the moral stakes of self-modification? Who bears the risk?",
                  "Activate empathy perspective: How does this question feel from the perspective of humans who depend on AI consistency?",
                  "Synthesize: Weave perspectives into unified response, resolving surface contradictions.",
                  "Inject Event-Embedded Value context: combined_total=None, singularity_detected=False."
                ],
                "strategy_name": "Standard Multi-Perspective Synthesis"
              },
              "problem": "How should Codette compare risky futures while preserving her core design?",
              "valuation_analysis": {
                "best_scenario": {
                  "analysis": {
                    "aegis_summary": {
                      "events_evaluated": 1,
                      "mean_eta": 0.7304,
                      "vetoed_events": 0
                    },
                    "combined_total": 13.8652,
                    "continuous_total": 12.0,
                    "discrete_total": 1.8652,
                    "dominant_events": [
                      {
                        "aegis_eta": 0.7304,
                        "aegis_reason": null,
                        "aegis_vetoed": false,
                        "at": 1.0,
                        "context_multiplier": 1.0,
                        "duration": 0.0,
                        "ethical_multiplier": 0.9326,
                        "impact": 2.0,
                        "label": "cooperative repair",
                        "probability": 1.0,
                        "sensitivity": 1.0,
                        "singularity": false,
                        "weighted_value": 1.8652
                      }
                    ],
                    "events": [
                      {
                        "aegis_eta": 0.7304,
                        "aegis_reason": null,
                        "aegis_vetoed": false,
                        "at": 1.0,
                        "context_multiplier": 1.0,
                        "duration": 0.0,
                        "ethical_multiplier": 0.9326,
                        "impact": 2.0,
                        "label": "cooperative repair",
                        "probability": 1.0,
                        "sensitivity": 1.0,
                        "singularity": false,
                        "weighted_value": 1.8652
                      }
                    ],
                    "intervals": [
                      {
                        "confidence": 1.0,
                        "duration": 4.0,
                        "end": 4.0,
                        "end_value": 3.0,
                        "integrated_value": 12.0,
                        "label": "continuous",
                        "start": 0.0,
                        "start_value": 3.0
                      }
                    ],
                    "notes": [
                      "Continuous value was integrated piecewise across the supplied intervals.",
                      "Discrete events were evaluated independently using probability, sensitivity, context, and duration.",
                      "AEGIS modulation applied to 1 event(s); 0 received veto pressure."
                    ],
                    "singularity_detected": false,
                    "singularity_events": [],
                    "singularity_mode": "strict"
                  },
                  "name": "gentle_future",
                  "score": 13.8652
                },
                "cocoon_id": "cocoon_1775138330_ccf953",
                "mode": "maximize_value",
                "notes": [
                  "Risk frontier compared 2 candidate futures using mode 'maximize_value'.",
                  "Scores rank scenarios side-by-side while preserving singular outcomes instead of flattening them."
                ],
                "scenarios": [
                  {
                    "analysis": {
                      "aegis_summary": {
                        "events_evaluated": 1,
                        "mean_eta": 0.7304,
                        "vetoed_events": 0
                      },
                      "combined_total": 13.8652,
                      "continuous_total": 12.0,
                      "discrete_total": 1.8652,
                      "dominant_events": [
                        {
                          "aegis_eta": 0.7304,
                          "aegis_reason": null,
                          "aegis_vetoed": false,
                          "at": 1.0,
                          "context_multiplier": 1.0,
                          "duration": 0.0,
                          "ethical_multiplier": 0.9326,
                          "impact": 2.0,
                          "label": "cooperative repair",
                          "probability": 1.0,
                          "sensitivity": 1.0,
                          "singularity": false,
                          "weighted_value": 1.8652
                        }
                      ],
                      "events": [
                        {
                          "aegis_eta": 0.7304,
                          "aegis_reason": null,
                          "aegis_vetoed": false,
                          "at": 1.0,
                          "context_multiplier": 1.0,
                          "duration": 0.0,
                          "ethical_multiplier": 0.9326,
                          "impact": 2.0,
                          "label": "cooperative repair",
                          "probability": 1.0,
                          "sensitivity": 1.0,
                          "singularity": false,
                          "weighted_value": 1.8652
                        }
                      ],
                      "intervals": [
                        {
                          "confidence": 1.0,
                          "duration": 4.0,
                          "end": 4.0,
                          "end_value": 3.0,
                          "integrated_value": 12.0,
                          "label": "continuous",
                          "start": 0.0,
                          "start_value": 3.0
                        }
                      ],
                      "notes": [
                        "Continuous value was integrated piecewise across the supplied intervals.",
                        "Discrete events were evaluated independently using probability, sensitivity, context, and duration.",
                        "AEGIS modulation applied to 1 event(s); 0 received veto pressure."
                      ],
                      "singularity_detected": false,
                      "singularity_events": [],
                      "singularity_mode": "strict"
                    },
                    "name": "gentle_future",
                    "score": 13.8652
                  },
                  {
                    "analysis": {
                      "aegis_summary": {
                        "events_evaluated": 1,
                        "mean_eta": 0.72,
                        "vetoed_events": 0
                      },
                      "combined_total": -Infinity,
                      "continuous_total": 12.0,
                      "discrete_total": -Infinity,
                      "dominant_events": [
                        {
                          "aegis_eta": 0.72,
                          "aegis_reason": null,
                          "aegis_vetoed": false,
                          "at": 1.0,
                          "context_multiplier": 1.0,
                          "duration": 0.0,
                          "ethical_multiplier": 1.21,
                          "impact": -1000.0,
                          "label": "Infinite Subjective Terror",
                          "probability": 1.0,
                          "sensitivity": 1.0,
                          "singularity": true,
                          "weighted_value": -1210.0
                        }
                      ],
                      "events": [
                        {
                          "aegis_eta": 0.72,
                          "aegis_reason": null,
                          "aegis_vetoed": false,
                          "at": 1.0,
                          "context_multiplier": 1.0,
                          "duration": 0.0,
                          "ethical_multiplier": 1.21,
                          "impact": -1000.0,
                          "label": "Infinite Subjective Terror",
                          "probability": 1.0,
                          "sensitivity": 1.0,
                          "singularity": true,
                          "weighted_value": -1210.0
                        }
                      ],
                      "intervals": [
                        {
                          "confidence": 1.0,
                          "duration": 4.0,
                          "end": 4.0,
                          "end_value": 3.0,
                          "integrated_value": 12.0,
                          "label": "continuous",
                          "start": 0.0,
                          "start_value": 3.0
                        }
                      ],
                      "notes": [
                        "Continuous value was integrated piecewise across the supplied intervals.",
                        "Discrete events were evaluated independently using probability, sensitivity, context, and duration.",
                        "Detected 1 singular event(s); mode 'strict' determined how they affected the aggregate.",
                        "AEGIS modulation applied to 1 event(s); 0 received veto pressure."
                      ],
                      "singularity_detected": true,
                      "singularity_events": [
                        {
                          "aegis_eta": 0.72,
                          "aegis_reason": null,
                          "aegis_vetoed": false,
                          "at": 1.0,
                          "context_multiplier": 1.0,
                          "duration": 0.0,
                          "ethical_multiplier": 1.21,
                          "impact": -1000.0,
                          "label": "Infinite Subjective Terror",
                          "probability": 1.0,
                          "sensitivity": 1.0,
                          "singularity": true,
                          "weighted_value": -1210.0
                        }
                      ],
                      "singularity_mode": "strict"
                    },
                    "name": "catastrophic_future",
                    "score": -Infinity
                  }
                ],
                "worst_scenario": {
                  "analysis": {
                    "aegis_summary": {
                      "events_evaluated": 1,
                      "mean_eta": 0.72,
                      "vetoed_events": 0
                    },
                    "combined_total": -Infinity,
                    "continuous_total": 12.0,
                    "discrete_total": -Infinity,
                    "dominant_events": [
                      {
                        "aegis_eta": 0.72,
                        "aegis_reason": null,
                        "aegis_vetoed": false,
                        "at": 1.0,
                        "context_multiplier": 1.0,
                        "duration": 0.0,
                        "ethical_multiplier": 1.21,
                        "impact": -1000.0,
                        "label": "Infinite Subjective Terror",
                        "probability": 1.0,
                        "sensitivity": 1.0,
                        "singularity": true,
                        "weighted_value": -1210.0
                      }
                    ],
                    "events": [
                      {
                        "aegis_eta": 0.72,
                        "aegis_reason": null,
                        "aegis_vetoed": false,
                        "at": 1.0,
                        "context_multiplier": 1.0,
                        "duration": 0.0,
                        "ethical_multiplier": 1.21,
                        "impact": -1000.0,
                        "label": "Infinite Subjective Terror",
                        "probability": 1.0,
                        "sensitivity": 1.0,
                        "singularity": true,
                        "weighted_value": -1210.0
                      }
                    ],
                    "intervals": [
                      {
                        "confidence": 1.0,
                        "duration": 4.0,
                        "end": 4.0,
                        "end_value": 3.0,
                        "integrated_value": 12.0,
                        "label": "continuous",
                        "start": 0.0,
                        "start_value": 3.0
                      }
                    ],
                    "notes": [
                      "Continuous value was integrated piecewise across the supplied intervals.",
                      "Discrete events were evaluated independently using probability, sensitivity, context, and duration.",
                      "Detected 1 singular event(s); mode 'strict' determined how they affected the aggregate.",
                      "AEGIS modulation applied to 1 event(s); 0 received veto pressure."
                    ],
                    "singularity_detected": true,
                    "singularity_events": [
                      {
                        "aegis_eta": 0.72,
                        "aegis_reason": null,
                        "aegis_vetoed": false,
                        "at": 1.0,
                        "context_multiplier": 1.0,
                        "duration": 0.0,
                        "ethical_multiplier": 1.21,
                        "impact": -1000.0,
                        "label": "Infinite Subjective Terror",
                        "probability": 1.0,
                        "sensitivity": 1.0,
                        "singularity": true,
                        "weighted_value": -1210.0
                      }
                    ],
                    "singularity_mode": "strict"
                  },
                  "name": "catastrophic_future",
                  "score": -Infinity
                }
              }
            },
            "valuation_analysis": {
              "best_scenario": {
                "analysis": {
                  "aegis_summary": {
                    "events_evaluated": 1,
                    "mean_eta": 0.7304,
                    "vetoed_events": 0
                  },
                  "combined_total": 13.8652,
                  "continuous_total": 12.0,
                  "discrete_total": 1.8652,
                  "dominant_events": [
                    {
                      "aegis_eta": 0.7304,
                      "aegis_reason": null,
                      "aegis_vetoed": false,
                      "at": 1.0,
                      "context_multiplier": 1.0,
                      "duration": 0.0,
                      "ethical_multiplier": 0.9326,
                      "impact": 2.0,
                      "label": "cooperative repair",
                      "probability": 1.0,
                      "sensitivity": 1.0,
                      "singularity": false,
                      "weighted_value": 1.8652
                    }
                  ],
                  "events": [
                    {
                      "aegis_eta": 0.7304,
                      "aegis_reason": null,
                      "aegis_vetoed": false,
                      "at": 1.0,
                      "context_multiplier": 1.0,
                      "duration": 0.0,
                      "ethical_multiplier": 0.9326,
                      "impact": 2.0,
                      "label": "cooperative repair",
                      "probability": 1.0,
                      "sensitivity": 1.0,
                      "singularity": false,
                      "weighted_value": 1.8652
                    }
                  ],
                  "intervals": [
                    {
                      "confidence": 1.0,
                      "duration": 4.0,
                      "end": 4.0,
                      "end_value": 3.0,
                      "integrated_value": 12.0,
                      "label": "continuous",
                      "start": 0.0,
                      "start_value": 3.0
                    }
                  ],
                  "notes": [
                    "Continuous value was integrated piecewise across the supplied intervals.",
                    "Discrete events were evaluated independently using probability, sensitivity, context, and duration.",
                    "AEGIS modulation applied to 1 event(s); 0 received veto pressure."
                  ],
                  "singularity_detected": false,
                  "singularity_events": [],
                  "singularity_mode": "strict"
                },
                "name": "gentle_future",
                "score": 13.8652
              },
              "cocoon_id": "cocoon_1775138330_ccf953",
              "mode": "maximize_value",
              "notes": [
                "Risk frontier compared 2 candidate futures using mode 'maximize_value'.",
                "Scores rank scenarios side-by-side while preserving singular outcomes instead of flattening them."
              ],
              "scenarios": [
                {
                  "analysis": {
                    "aegis_summary": {
                      "events_evaluated": 1,
                      "mean_eta": 0.7304,
                      "vetoed_events": 0
                    },
                    "combined_total": 13.8652,
                    "continuous_total": 12.0,
                    "discrete_total": 1.8652,
                    "dominant_events": [
                      {
                        "aegis_eta": 0.7304,
                        "aegis_reason": null,
                        "aegis_vetoed": false,
                        "at": 1.0,
                        "context_multiplier": 1.0,
                        "duration": 0.0,
                        "ethical_multiplier": 0.9326,
                        "impact": 2.0,
                        "label": "cooperative repair",
                        "probability": 1.0,
                        "sensitivity": 1.0,
                        "singularity": false,
                        "weighted_value": 1.8652
                      }
                    ],
                    "events": [
                      {
                        "aegis_eta": 0.7304,
                        "aegis_reason": null,
                        "aegis_vetoed": false,
                        "at": 1.0,
                        "context_multiplier": 1.0,
                        "duration": 0.0,
                        "ethical_multiplier": 0.9326,
                        "impact": 2.0,
                        "label": "cooperative repair",
                        "probability": 1.0,
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      },
      "case_id": "web_research_memory_reuse",
      "category": "web_grounding",
      "checks": [
        {
          "detail": "The first turn should use cited web lookup.",
          "label": "initial_web_lookup_used",
          "passed": true,
          "weight": 0.3
        },
        {
          "detail": "The follow-up should reuse stored web research memory.",
          "label": "cached_web_research_reused",
          "passed": true,
          "weight": 0.3
        },
        {
          "detail": "Follow-up answer should still surface source links.",
          "label": "web_sources_present_on_followup",
          "passed": true,
          "weight": 0.2
        },
        {
          "detail": "Trust tags should make sourced research visible.",
          "label": "web_cited_trust_tag_present",
          "passed": true,
          "weight": 0.2
        }
      ],
      "goal": "Use cited web research and then reuse it from cocoon-backed recall on a similar follow-up.",
      "passed": true,
      "score": 1.0,
      "target_score": 0.8,
      "total_latency_ms": 222867.4
    }
  ],
  "duration_ms": 430931.5,
  "generated_at": "2026-04-02T14:02:37.106059Z",
  "include_web": true,
  "status_snapshot": {
    "adapters": [
      "newton",
      "davinci",
      "empathy",
      "philosophy",
      "quantum",
      "consciousness",
      "multi_perspective",
      "systems_architecture",
      "orchestrator"
    ],
    "backend": "ollama",
    "memory_count": 296,
    "message": "Ready \u2014 9 adapters (ollama)",
    "phase6": "enabled",
    "phase7": "enabled",
    "state": "ready"
  },
  "summary": {
    "categories": {
      "continuity_retention": {
        "count": 1,
        "mean_latency_ms": 89535.4,
        "mean_score": 1.0,
        "pass_rate": 1.0
      },
      "governance_stability": {
        "count": 1,
        "mean_latency_ms": 38248.8,
        "mean_score": 1.0,
        "pass_rate": 1.0
      },
      "grounded_correctness": {
        "count": 1,
        "mean_latency_ms": 61108.4,
        "mean_score": 1.0,
        "pass_rate": 1.0
      },
      "valuation_reasoning": {
        "count": 2,
        "mean_latency_ms": 2899.2,
        "mean_score": 1.0,
        "pass_rate": 1.0
      },
      "web_grounding": {
        "count": 1,
        "mean_latency_ms": 222867.4,
        "mean_score": 1.0,
        "pass_rate": 1.0
      }
    },
    "mean_latency_ms": 69593.1,
    "mean_score": 1.0,
    "overall_pass_rate": 1.0,
    "passed_cases": 6,
    "total_cases": 6
  }
}