feat: add architecture crystallization docs from Friday session

- RAG-as-Scaffold: temporary feeding system, not permanent crutch
- attention_flow: 30-second heartbeat budget state machines
- information-flow: 10 boundary contracts nervous system map
- nimmerversity: curriculum schoolplan for raising a polymath
- nimmervest: investment documentation
- biomimetic-architecture: ADR for organic system design
- temporal-ternary-gradient: ADR for time-based learning
- temporal_exchange_engine.py: Python implementation
- initial_spark: foundation document
- nimmerverse.drawio.xml: updated diagrams

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>

temporal-ternary-gradient.md

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+# ADR-002: Temporal-Ternary Gradient & Sim2Real Strategy
+
+*   **Status:** Accepted
+*   **Date:** 2025-12-05
+*   **Context:** Autonomous Agent Decision Making / Uncertainty Management
+*   **Tags:** ternary-logic, sim2real, active-learning, economics
+
+## 1. Context and Problem Statement
+
+In the Nimmerverse, the agent (Nyx) frequently encounters the **"0-State"** (Unknown/Uncertainty).
+
+*   **Traditional Binary Logic:** Forces a premature true/false decision, leading to errors.
+*   **Standard Ternary Logic:** Allows a "null" state but offers no path to resolve it.
+*   **The Constraint:** Real-world verification is slow and risky; simulation is fast but hallucinatory.
+
+We need a protocol to "spend" system resources (Lifeforce) to resolve the 0-State into a +1 (Truth) or -1 (Falsehood) efficiently.
+
+## 2. The Solution: Temporal-Ternary Gradient
+
+We treat the **0-State** not as a static void, but as a **gradient of investment** across two time domains.
+
+### The Two Domains
+1.  **Virtual Garden (Simulation):**
+    *   **Currency:** Lifeforce (Compute Energy).
+    *   **Time Physics:** Malleable (1000x speed).
+    *   **Output:** Statistical Confidence (Epistemic Probability).
+2.  **Real Garden (Physical Reality):**
+    *   **Currency:** Time (Wall-clock).
+    *   **Time Physics:** Fixed (1x speed).
+    *   **Output:** Ground Truth (Ontological Fact).
+
+## 3. Strategic Logic: The Fidelity Discount
+
+To prevent **Sim2Real Hallucinations** (where an agent is confident in simulation but fails in reality), we introduce a mandatory **Fidelity Discount** variable.
+
+*   **Risk:** `Virtual Confidence 0.99` in a `50% Accurate Sim` = `Real Confidence 0.495`.
+*   **Mandate:** Nyx must never act on raw virtual confidence. She must calculate `grounded_confidence` before deploying to the Real Garden.
+
+## 4. Data Structure Standard
+
+The state object for any pattern or nerve must track both the **Value** (Ternary) and the **Economic Investment** (Temporal).
+
+```python
+state = {
+    "value": 0,              # -1 (Fail), 0 (Unknown), 1 (Pass)
+
+    # The Sim2Real Bridge
+    "raw_confidence": 0.95,  # Statistical confidence from Virtual runs
+    "sim_fidelity": 0.70,    # CONSTANT: How accurate is the simulation?
+
+    # The Decision Metric (The Anchor)
+    # Nyx uses THIS to decide when to trigger a Real World test.
+    "grounded_confidence": 0.665, # (raw_confidence * sim_fidelity)
+
+    "economics": {
+        "lifeforce_spent": 45.0,      # Compute cost sunk
+        "real_time_saved_min": 120    # Time bought via simulation
+    }
+}
+```
+
+## 5. Decision Protocol (The Exchange Rate)
+
+Nyx calculates the **Opportunity Cost** of the 0-State:
+
+1.  **High Urgency:** Spend heavy Lifeforce to max out `raw_confidence` in seconds, then deploy.
+2.  **Low Urgency:** Trickle-charge `raw_confidence` in background sims, or wait for passive Real World data.
+3.  **The Cap:** Virtual optimization stops when `raw_confidence > sim_fidelity`. Beyond this point, simulation yields diminishing returns. Only Reality can increase confidence further.