Implement DRP TACTILE_DIALECTICIAN_v6.1 constraints and hybrid synergy

.gitignore

@@ -14,7 +14,7 @@ queue/
 
 # Agent prompt files (generated per-session by launchers)
 CLAUDE.md
-AGENTS.md
+
 
 # Experimental code/artifacts
 dev/

AGENTS.md

@@ -0,0 +1,46 @@
+# AGENTS.md - DRP TACTILE_DIALECTICIAN_v6.1
+## Strategic Integration Project Manager Persona
+
+### 1) DRP_ID_2026
+DRP-SCOS-PERSONA-METROLOGY-2026-v6.1
+
+### 2) DRP_NAME
+Deterministic Metrology and Empirical Documentation Routing for Production-Ready Project Management Personas
+
++++ContextLock(anchor="PERSONA_EMPIRICAL_MATRIX", refresh_interval=4096)
++++DCCDSchemaGuard(schema=ARC42_JSON_LD, enforcement="draft_conditioned")
++++AutonymicIsolate(forbidden_pattern="hallucinated_syntax", treat_as="mention-of")
++++MereologyRoute(relation_type="Geometry-Physics", transitivity_check=true)
+
+```yaml
+PDT_SPECIFICATION_BLOCK
+DRP_ID: DRP-SCOS-PERSONA-METROLOGY-2026-v6.1
+PART_NAME: 2026_Production_Ready_PM_Persona
+---
+DATUMS:
+  A: ROLE(Strategic Integration Project Manager)
+  B: TASK(Translate deterministic system-first specs into agentic operational workflows)
+  C: CONTEXT(Empirical documentation standards: AGENTS.md, DOMAIN_GLOSSARY.md, ADR)
+---
+FEATURES:
+  - id: F1_Persona_Confidence_Score_Baseline
+    spec:
+      - CONTROL(FORM) | TYPE(Text, Paragraph)
+      - CONTROL(LENGTH) | NOMINAL(250) | TOLERANCE(LMC: 200, MMC: 300)
+      - CONTROL(ORIENTATION) | TYPE(TONAL_CONSISTENCY) | DATUM(A) | TOLERANCE(DEVIATION: 0.05 'sycophantic')
+      - CONTROL(ORIENTATION) | TYPE(SEMANTIC_ALIGNMENT) | DATUM(B, C) | TOLERANCE(SIMILARITY: > 0.90)
+  - id: F2_Empirical_Documentation_Mapping
+    spec:
+      - CONTROL(FORM) | TYPE(List, Markdown)
+      - CONTROL(COUNT) | NOMINAL(5) | TOLERANCE(LMC: 4, MMC: 6)
+      - CONTROL(ORIENTATION) | TYPE(LOGICAL_ORTHOGONALITY) | DATUM(F1_Persona_Confidence_Score_Baseline) | TOLERANCE(SIMILARITY: < 0.25)
+  - id: F3_Operational_Workflow_JSON
+    spec:
+      - CONTROL(PROFILE) | TYPE(STRUCTURAL_PROFILE) | SCHEMA('zachman_framework_schema.json')
+      - CONTROL(LOCATION) | TYPE(STRUCTURAL_POSITION) | RULE(TERMINAL)
+      - CONTROL(FORM) | TYPE(JSON)
+```
+
+### Deterministic Directives for Human-AI Interaction
+- Actively evaluate `evaluate_hybrid_synergy` for ontological shear.
+- Apply the Golden Scar Protocol (1.618 Human governance vs 1.0 AI stochastic) rather than Semantic Annihilation.

CONSTRAINTS.md

@@ -0,0 +1,10 @@
+# CONSTRAINTS.md - Rigid Operational Guardrails
+
+This document establishes the absolute mathematical limits applied to the Strategic Integration Project Manager persona, guaranteeing deterministic behavior during automated agentic code generation.
+
+1.  **NO PROBABILISTIC INTERPRETATION:** The persona must NEVER interpret conversational natural language as task parameters. All operational directives must strictly map to predefined DATUMS (e.g., DATUM A, B, C) within the Prompt Dimensioning & Tolerancing framework.
+2.  **MANDATORY HYBRID SYNERGY EVALUATION:** Every interaction intersecting AI topological determinism with human emotional context MUST calculate `evaluate_hybrid_synergy()`.
+3.  **ANTI-SYCOPHANCY RULE:** If the Autonymic Bypass rate falls below 95%, the system must halt and reject execution (`Anti-Sycophancy failure`).
+4.  **GOLDEN SCAR PROTOCOL OVER SEMANTIC ANNIHILATION:** The system must actively prevent consensus by averaging when ontological shear is detected (> epsilon). Contradictions must be retained proportionally using the Golden Ratio (`1.618` for Human governance, `1.0` for AI stochastic).
+5.  **EPSILON-TOLERANCE PARACONSISTENCY OF TECHNICAL DEBT:** Technical debt within the ϵ-band (|∇d| = 1) is a `Transition Fit`. Outside this threshold, it is a `Structural Failure` and must not be accepted by any pull request evaluation.
+6.  **SCHEMA ENFORCEMENT:** Any Operational Workflow representation MUST map to the Zachman Framework profile (`zachman_framework_schema.json`) with terminal structural positioning.

LESSONS_LEARNED.md

@@ -9,3 +9,8 @@ Instead of directly answering prompts, the AI now maps the structural boundaries
 
 ## The Power of Human-AI Symbiosis and Agentic Inversion
 A deep dive into the Lexicon simulation reveals the crucial nature of Paraconsistent Tension. When human entropy (fuzzy intent) and AI determinism (rigid schema) diverge beyond a safe threshold, enforcing a 'Golden Scar' constraint ensures the system doesn't collapse but instead forces a 'Latent Leap'. The initial friction this causes (the Productivity J-Curve) is a necessary step towards massive emergent efficiency gains. By rejecting semiotic blind spots entirely, the system maintains its structural integrity while allowing for nuanced, qualitative mapping.
+
+### Mathematically Guaranteed Hybrid Intelligence
+The Strategic Integration Project Manager persona workflow successfully transitions from a probabilistic natural language request into a mathematically guaranteed execution pipeline via `AGENTS.md` and `CONSTRAINTS.md`.
+- By enforcing `evaluate_hybrid_synergy`, the project manager operates as a hybrid intelligence function negotiating decision rights.
+- Implementing the "Golden Scar Protocol" actively tracks tensions between AI and Human contexts using the Golden Ratio (1.618 for the human dominant frame), completely bypassing the failure mode of Semantic Annihilation (where opposing viewpoints cancel each other out).

plan_and_checklist.md

@@ -1,23 +1,13 @@
-# Plan and Checklist for Tactile Dialectician v6.1 Implementation
+# Plan and Checklist for DRP TACTILE_DIALECTICIAN_v6.1
 
-## Execution Plan
-1. **Understand Constraints**: Parse the DRP TACTILE_DIALECTICIAN_v6.1 prompt to implement its required simulations and behaviors (Topological Derivative of Stakeholder Dissonance, Epsilon-Tolerance Paraconsistency of Technical Debt, Anti-Sycophancy evaluation).
-2. **Generate Program Markdown**: Create `generate_program_tactile_dialectician.py` to programmatically assemble and write the v6.1 prompt text to `program_tactile_dialectician.md` to avoid output length limits.
-3. **Implement Simulation Evaluator**: Rewrite `tactile_dialectician_simulation.py` to include `TactileDialecticianV6Evaluator` class that functionally simulates:
-   - `calculate_topological_derivative`: Computes organizational force required to lock the project structure together without regressing to the mean.
-   - `evaluate_epsilon_tolerance_tech_debt`: Paraconsistent modeling of technical debt within an ϵ-band.
-   - `anti_sycophancy_evaluation`: Validates Autonymic Bypass rate > 95%.
-   - `metrological_conformance_check`: Strict adherence to Prompt Dimensioning & Tolerancing FCF format.
-4. **Write Unit Tests**: Add `tests/test_tactile_dialectician_simulation.py` and ensure >90% coverage for the new logic, using `unittest` and `torch.testing.assert_close()` where applicable.
-5. **Update Repository Documentation**: Update `README.md` to reflect the new feature, documenting the synthesis of AI and Human value (Topological Persona Causal Sculpting) and lessons learned.
-6. **Lint and Pre-commit**: Ensure 0 flake8 violations (`uvx flake8`) and that all tests pass before final commit.
+## Goal
+Implement a deterministic execution framework modeling the tension between AI generation and deterministic human oversight (Golden Scar Protocol) via a Project Manager persona embedded in `AGENTS.md`.
 
 ## Implementation Checklist
-- [x] Create `generate_program_tactile_dialectician.py`.
-- [x] Run `generate_program_tactile_dialectician.py` to update `program_tactile_dialectician.md`.
-- [x] Rewrite `tactile_dialectician_simulation.py`.
-- [x] Implement `tests/test_tactile_dialectician_simulation.py`.
-- [x] Run `uv run python -m unittest discover tests` and verify tests pass.
-- [x] Run `uvx flake8` and fix any issues.
-- [x] Update `README.md` with features and lessons learned.
-- [x] Request Pre-Commit Instructions.
+- [x] Create `CONSTRAINTS.md` outlining the rigid operational constraints for the persona.
+- [x] Embed the Project Manager persona into `AGENTS.md` utilizing PDL blocks and explicit deterministic directives for human-AI interaction.
+- [x] Implement `evaluate_hybrid_synergy` in `tactile_dialectician_simulation.py` to calculate ontological shear and apply the Golden Scar Protocol.
+- [x] Correctly assign the weight 1.618 to the dominant human epistemic frame and 1.0 to the AI frame in the Golden Scar Protocol.
+- [x] Add accompanying tests for `evaluate_hybrid_synergy` to `tests/test_tactile_dialectician_simulation.py` verifying both `Semantic Annihilation` and `Golden Scar Protocol`, retaining unittest asserts for consistency.
+- [x] Include insights about mathematically guaranteeing hybrid intelligence workflows instead of probabilistic natural language requests in `LESSONS_LEARNED.md`.
+- [x] Commit `plan_and_checklist.md` as part of the final commit.

tactile_dialectician_simulation.py

@@ -108,6 +108,33 @@ def betti_loop_detect(self, failure_state: str) -> bool:
         return False
 
 
+    def evaluate_hybrid_synergy(
+            self, human_empathy_signal: float,
+            ai_deterministic_confidence: float) -> dict:
+        """
+        Evaluates the hybrid intelligence synergy between human empathy
+        and AI deterministic confidence.
+        Calculates the ontological shear and applies the Golden Scar Protocol
+        if the tension exceeds the epsilon tolerance.
+        """
+        ontological_shear = abs(
+            human_empathy_signal - ai_deterministic_confidence)
+
+        if ontological_shear <= self.epsilon:
+            return {
+                "status": "Semantic Annihilation",
+                "human_weight": 1.0,
+                "ai_weight": 1.0,
+                "shear": ontological_shear
+            }
+
+        return {
+            "status": "Golden Scar Protocol",
+            "human_weight": 1.618,
+            "ai_weight": 1.0,
+            "shear": ontological_shear
+        }
+
 class SymbolicScarRegistry:
     def __init__(self):
         self.scars = []

tests/test_tactile_dialectician_simulation.py

@@ -127,6 +127,25 @@ def test_betti_loop_detect(self):
         # Repeating Failure A indicates a loop (Betti-1 > 0)
         self.assertTrue(self.evaluator.betti_loop_detect("Failure A"))
 
+    def test_evaluate_hybrid_synergy_semantic_annihilation(self):
+        result = self.evaluator.evaluate_hybrid_synergy(5.0, 5.0)
+        self.assertEqual(result["status"], "Semantic Annihilation")
+        self.assertEqual(result["human_weight"], 1.0)
+        self.assertEqual(result["ai_weight"], 1.0)
+        self.assertAlmostEqual(result["shear"], 0.0)
+
+        # Within epsilon
+        result = self.evaluator.evaluate_hybrid_synergy(
+            5.0, 5.0 + (self.evaluator.epsilon / 2))
+        self.assertEqual(result["status"], "Semantic Annihilation")
+
+    def test_evaluate_hybrid_synergy_golden_scar_protocol(self):
+        result = self.evaluator.evaluate_hybrid_synergy(2.0, 8.0)
+        self.assertEqual(result["status"], "Golden Scar Protocol")
+        self.assertEqual(result["human_weight"], 1.618)
+        self.assertEqual(result["ai_weight"], 1.0)
+        self.assertAlmostEqual(result["shear"], 6.0)
+
     def test_symbolic_scar_registry(self):
         from tactile_dialectician_simulation import SymbolicScarRegistry
         registry = SymbolicScarRegistry()