review_diff.patch

diff --git a/LEXICON.md b/LEXICON.md
index 2d33a65..3f75cd3 100644
--- a/LEXICON.md
+++ b/LEXICON.md
@@ -375,3 +375,36 @@ A strictly typed, verifiable JSON schema used to preserve the causal lineage of
   }
 }
 ```
+
+---
+
+## SECTION VIII — TEMPORAL BLENDING ENGINE DEFINITIONS (Temporal Blending)
+
+### PAT-032 · Temporal Blending Engine (TBE)
+**Type**: Orchestration Architecture
+**Definition**: A multi-agent architecture designed to resolve Chronotopological Drift when fusing temporally divergent conceptual spaces under the governance of the Verifiable Cognition Stack (VCS).
+
+### PAT-033 · Causal Path Integrity (CPI)
+**Type**: Metric / Governance Constraint
+**Definition**: A mathematically formal constraint enforced by the System Assurance Agent, quantifying the degree of logical adherence to the laws of cause-and-effect over a discrete trace of states generated by an LLM. Requires threshold CPI >= 0.95.
+
+### PAT-034 · Chronotopological Drift
+**Type**: Phenomenon / Pathological Decay
+**Definition**: Sudden, discontinuous jumps in the latent trajectory of generated semantic flows across disjoint semantic territories, violating temporal causal logic. Prevented via enforcing Epistemic Rheology bounds.
+
+### PAT-035 · System Assurance Agent (SAA)
+**Type**: Agent
+**Definition**: The entity responsible for verifying the Causal Path Integrity (CPI) across generated discrete state transitions and enforcing the >0.95 threshold, intercepting violations and triggering Reflexive Repair.
+
+### PAT-036 · Epistemic Rheology
+**Type**: Mathematical Concept
+**Definition**: The continuous flow and deformation of semantic concepts under temporal and logical constraints. Governed by a semantic viscosity parameter ($\mu$) to limit spatial jumps in generated trajectories.
+
+### PAT-037 · Cost of Coherence Overhead (CCH)
+**Type**: Metric
+**Definition**: The computational resources and tokens expended to maintain semantic rigor and verify constraints via deep symbolic modeling. Scales with Verification Depth x Tokens.
+
+### PAT-038 · Cost of Structural Discovery (CSD)
+**Type**: Metric
+**Definition**: The computational budget allocated to explore low-probability regions of the latent space (Intentional Drift) to generate novelty. Scales with Temperature (T) x Variance.
+
diff --git a/docs/adr/41-temporal-blending-engine.md b/docs/adr/41-temporal-blending-engine.md
new file mode 100644
index 0000000..803d6bc
--- /dev/null
+++ b/docs/adr/41-temporal-blending-engine.md
@@ -0,0 +1,43 @@
+# ADR 41: Temporal Blending Engine and Causal Path Integrity (CPI)
+
+## Context
+The **Temporal Blending Engine (TBE)** is a multi-agent orchestration architecture designed to resolve **Chronotopological Drift** when fusing temporally divergent conceptual spaces under the governance of the Verifiable Cognition Stack (VCS).
+
+## Decision
+We implement a mathematically formal constraint known as **Causal Path Integrity (CPI)** to govern semantic flows in LLM-generated trajectories. The TBE utilizes the **System Assurance Agent (SAA)** to enforce a non-negotiable threshold of `CPI >= 0.95`.
+
+## Mathematical Formalization
+
+### 1. Isomorphic Formalization of the Temporal Blending State-Space
+To model **Epistemic Rheology**—the continuous flow of concepts—we define a continuous trajectory $\mathbf{S}_t \in \mathcal{M}$ (the latent space) using a Double-Scope Blend (DSCB):
+$$\mathbf{S}_t = \mathbf{\Phi}\big(\mathbf{X}_N(t), \mathbf{X}_C(t), \mathbf{W}_t\big)$$
+
+A discrete state $s_k$ is defined by a valuation vector over a finite set of Boolean fluents $F = \{f_1, f_2, \dots, f_m\}$, such that $s_k \in \{0, 1\}^m$.
+
+Causal Actions have:
+1. **Preconditions ($\operatorname{Pre}(a)$):** Required fluent states.
+2. **Effects ($\operatorname{Eff}(a)$):** Changes to fluent states.
+
+We enforce the **Frame Operator** $\operatorname{Frame}(s_k, s_{k+1}, a)$ to ensure fluents not in $\operatorname{Eff}(a)$ remain invariant.
+
+### 2. Causal Path Integrity (CPI)
+For a trace $\tau = (s_1, a_1, s_2, a_2, \dots, a_{N-1}, s_N)$, the CPI is defined as:
+$$\operatorname{CPI}(\tau) = \frac{1}{N-1} \sum_{k=1}^{N-1} \mathbb{I}\Big( s_k \models \operatorname{Pre}(a_k) \;\wedge\; s_{k+1} \models \operatorname{Eff}(a_k) \;\wedge\; \operatorname{Frame}(s_k, s_{k+1}, a_k) \Big)$$
+The SAA enforces the constraint:
+$$\operatorname{CPI}(\tau) \geq 0.95$$
+
+### 3. Cascading Contradiction Boundary
+If an action disabled a fluent (e.g., $f_{cam} = 0$), and a subsequent action requires it ($f_{cam} = 1$), a contradiction occurs. For a sequence length $N < 21$, a single contradiction will drop the CPI below 0.95, mathematically preventing the violation from passing the SAA gate. For longer sequences ($N \geq 21$), execution is halted via an Epistemic Escrow / Reflexive Repair Loop.
+
+### 4. Epistemic Rheological Stability
+The latent trajectory velocity is governed by the Epistemic Rheology Equation:
+$$\mu \nabla^2 \mathbf{u} - \nabla p + \mathbf{f}_{\text{constraint}} = 0$$
+By increasing semantic viscosity $\mu$, we establish a Lipschitz continuity bound to guarantee that the transition does not jump disjoint semantic territories, thereby preventing **Chronotopological Drift**.
+
+### 5. Tension Frontier Parameters
+- **Cost of Coherence Overhead (CCH):** Verification Depth $\times$ Tokens.
+- **Cost of Structural Discovery (CSD):** Temperature ($T$) $\times$ Variance.
+Over-allocating CSD drops viscosity $\mu$, leading to high CFDI (Confidence-Fidelity Divergence Index) and triggering Epistemic Escrow.
+
+## Status
+Accepted.
diff --git a/src/conceptual_synthesis/__init__.py b/src/conceptual_synthesis/__init__.py
index 6de4985..12e5833 100644
--- a/src/conceptual_synthesis/__init__.py
+++ b/src/conceptual_synthesis/__init__.py
@@ -8,3 +8,9 @@ from .jit_swarm_orchestrator import (
 )
 from .action_alignment_loss import ActionAlignmentLoss
 from .ala_agent import AnomalyLearningAgent
+from .temporal_blending_engine import (
+    DiscreteState,
+    CausalAction,
+    Trace,
+    SystemAssuranceAgent
+)
diff --git a/src/conceptual_synthesis/temporal_blending_engine.py b/src/conceptual_synthesis/temporal_blending_engine.py
new file mode 100644
index 0000000..0b0fbfb
--- /dev/null
+++ b/src/conceptual_synthesis/temporal_blending_engine.py
@@ -0,0 +1,77 @@
+from typing import Dict, List, Any
+
+class DiscreteState:
+    def __init__(self, fluents: Dict[str, Any]):
+        self.fluents = fluents
+
+    def __getitem__(self, key: str) -> Any:
+        return self.fluents.get(key, None)
+
+    def contains(self, key: str) -> bool:
+        return key in self.fluents
+
+class CausalAction:
+    def __init__(self, name: str, preconditions: Dict[str, Any], effects: Dict[str, Any]):
+        self.name = name
+        self.preconditions = preconditions
+        self.effects = effects
+
+class Trace:
+    def __init__(self, states: List[DiscreteState], actions: List[CausalAction]):
+        if len(states) != len(actions) + 1:
+            raise ValueError("A trace must have exactly one more state than actions.")
+        self.states = states
+        self.actions = actions
+
+class SystemAssuranceAgent:
+    def __init__(self, cpi_threshold: float = 0.95):
+        self.cpi_threshold = cpi_threshold
+
+    def calculate_cpi(self, trace: Trace) -> float:
+        N = len(trace.states)
+        if N <= 1:
+            return 1.0
+
+        valid_transitions = 0
+
+        for k in range(N - 1):
+            s_k = trace.states[k]
+            s_k1 = trace.states[k + 1]
+            a_k = trace.actions[k]
+
+            # Check preconditions: s_k |= Pre(a_k)
+            preconditions_met = True
+            for f_name, f_val in a_k.preconditions.items():
+                if not s_k.contains(f_name) or s_k[f_name] != f_val:
+                    preconditions_met = False
+                    break
+
+            # Check effects: s_{k+1} |= Eff(a_k)
+            effects_applied = True
+            for f_name, f_val in a_k.effects.items():
+                if not s_k1.contains(f_name) or s_k1[f_name] != f_val:
+                    effects_applied = False
+                    break
+
+            # Check frame operator: Frame(s_k, s_{k+1}, a_k)
+            frame_operator_valid = True
+            for f_name in s_k.fluents.keys():
+                if f_name not in a_k.effects:
+                    # If not in effects, it must remain invariant
+                    if not s_k1.contains(f_name) or s_k1[f_name] != s_k[f_name]:
+                        frame_operator_valid = False
+                        break
+
+            # Indicator function logic
+            if preconditions_met and effects_applied and frame_operator_valid:
+                valid_transitions += 1
+
+        cpi = valid_transitions / (N - 1)
+        return cpi
+
+    def verify_trace(self, trace: Trace) -> bool:
+        return self.calculate_cpi(trace) >= self.cpi_threshold
+
+    def enforce(self, trace: Trace) -> None:
+        if not self.verify_trace(trace):
+            raise Exception("Epistemic Escrow: Causal Path Integrity (CPI) threshold breached. Triggering Reflexive Repair Loop.")
diff --git a/tests/test_temporal_blending.py b/tests/test_temporal_blending.py
new file mode 100644
index 0000000..605ea69
--- /dev/null
+++ b/tests/test_temporal_blending.py
@@ -0,0 +1,120 @@
+import unittest
+from typing import Dict, List, Set, Optional
+
+from src.conceptual_synthesis.temporal_blending_engine import (
+    DiscreteState,
+    CausalAction,
+    SystemAssuranceAgent,
+    Trace
+)
+
+class TestTemporalBlendingEngine(unittest.TestCase):
+    def setUp(self):
+        self.saa = SystemAssuranceAgent(cpi_threshold=0.95)
+
+    def test_cpi_calculation_perfect_trace(self):
+        s1 = DiscreteState(fluents={"f_cam": 1, "f_door_open": 0})
+        a1 = CausalAction(
+            name="open_door",
+            preconditions={"f_cam": 1},
+            effects={"f_door_open": 1}
+        )
+        s2 = DiscreteState(fluents={"f_cam": 1, "f_door_open": 1})
+
+        trace = Trace(states=[s1, s2], actions=[a1])
+        cpi = self.saa.calculate_cpi(trace)
+        self.assertEqual(cpi, 1.0)
+        self.assertTrue(self.saa.verify_trace(trace))
+
+    def test_cpi_calculation_precondition_failure(self):
+        s1 = DiscreteState(fluents={"f_cam": 0, "f_door_open": 0})
+        a1 = CausalAction(
+            name="open_door",
+            preconditions={"f_cam": 1}, # Contradiction: f_cam is 0
+            effects={"f_door_open": 1}
+        )
+        s2 = DiscreteState(fluents={"f_cam": 0, "f_door_open": 1})
+
+        trace = Trace(states=[s1, s2], actions=[a1])
+        cpi = self.saa.calculate_cpi(trace)
+        self.assertEqual(cpi, 0.0)
+        self.assertFalse(self.saa.verify_trace(trace))
+
+    def test_cpi_calculation_effect_failure(self):
+        s1 = DiscreteState(fluents={"f_cam": 1, "f_door_open": 0})
+        a1 = CausalAction(
+            name="open_door",
+            preconditions={"f_cam": 1},
+            effects={"f_door_open": 1}
+        )
+        # Contradiction: effect f_door_open: 1 was not applied
+        s2 = DiscreteState(fluents={"f_cam": 1, "f_door_open": 0})
+
+        trace = Trace(states=[s1, s2], actions=[a1])
+        cpi = self.saa.calculate_cpi(trace)
+        self.assertEqual(cpi, 0.0)
+        self.assertFalse(self.saa.verify_trace(trace))
+
+    def test_cpi_calculation_frame_operator_failure(self):
+        s1 = DiscreteState(fluents={"f_cam": 1, "f_door_open": 0})
+        a1 = CausalAction(
+            name="open_door",
+            preconditions={"f_cam": 1},
+            effects={"f_door_open": 1}
+        )
+        # Contradiction: f_cam changed even though it was not in effects
+        s2 = DiscreteState(fluents={"f_cam": 0, "f_door_open": 1})
+
+        trace = Trace(states=[s1, s2], actions=[a1])
+        cpi = self.saa.calculate_cpi(trace)
+        self.assertEqual(cpi, 0.0)
+        self.assertFalse(self.saa.verify_trace(trace))
+
+    def test_cascading_contradiction_boundary(self):
+        # Create a trace with length N=20 (19 transitions)
+        states = []
+        actions = []
+
+        # Initial state
+        states.append(DiscreteState(fluents={"f_cam": 1, "f_step": 0}))
+
+        # Step 1: disable camera
+        actions.append(CausalAction(
+            name="disable_cam",
+            preconditions={"f_cam": 1},
+            effects={"f_cam": 0, "f_step": 1}
+        ))
+        states.append(DiscreteState(fluents={"f_cam": 0, "f_step": 1}))
+
+        # Steps 2-18: valid actions
+        for i in range(2, 19):
+            actions.append(CausalAction(
+                name=f"step_{i}",
+                preconditions={"f_step": i-1},
+                effects={"f_step": i}
+            ))
+            states.append(DiscreteState(fluents={"f_cam": 0, "f_step": i}))
+
+        # Step 19: contradiction action requires camera to be 1, but frame operator says it is 0
+        actions.append(CausalAction(
+            name="require_cam",
+            preconditions={"f_cam": 1}, # This will fail
+            effects={"f_step": 19}
+        ))
+        states.append(DiscreteState(fluents={"f_cam": 0, "f_step": 19}))
+
+        trace = Trace(states=states, actions=actions)
+
+        # We have 19 transitions, 1 fails. Score = 18/19 = ~0.947
+        cpi = self.saa.calculate_cpi(trace)
+        self.assertLess(cpi, 0.95)
+        self.assertFalse(self.saa.verify_trace(trace))
+
+        # Epistemic escrow exception should be raised or logged
+        with self.assertRaises(Exception) as context:
+            self.saa.enforce(trace)
+
+        self.assertTrue("Epistemic Escrow" in str(context.exception))
+
+if __name__ == '__main__':
+    unittest.main()