Enforce technical tone across documentation

Author: TNFR AI Agent

.github/agents/my-agent.md

@@ -114,7 +114,7 @@ Theoretical Foundation: The framework models reality as coherent dynamic pattern
 
 **Reference Sources**:
 - **Historical Theory**: [theory/TNFR.pdf](theory/TNFR.pdf) - Original theoretical derivations
-- **Theoretical Foundation**: [theory/FUNDAMENTAL_TNFR_THEORY_UNIVERSAL_TETRAHEDRAL_CORRESPONDENCE.md](theory/FUNDAMENTAL_TNFR_THEORY_UNIVERSAL_TETRAHEDRAL_CORRESPONDENCE.md)
+- **Theoretical Foundation**: [Structural Fields and Universal Tetrahedral Correspondence](theory/FUNDAMENTAL_TNFR_THEORY_UNIVERSAL_TETRAHEDRAL_CORRESPONDENCE.md)
 - **TNFR-Riemann Program**: [theory/TNFR_RIEMANN_RESEARCH_NOTES.md](theory/TNFR_RIEMANN_RESEARCH_NOTES.md) - Complete theoretical framework for mathematical consciousness and Riemann Hypothesis connection
 
 **Validation and Examples**:
@@ -139,6 +139,17 @@ Theoretical Foundation: The framework models reality as coherent dynamic pattern
 
 All TNFR documentation, code, and communications are maintained in English. This ensures consistent terminology for TNFR physics and maintains theoretical consistency across implementations and research.
 
+### Technical Communication Standard
+
+All written material (papers, READMEs, notebooks, commit messages, issues) must:
+
+1. **Anchor claims to math/telemetry** – reference the nodal equation, operator contracts, or recorded metrics. Qualitative statements without data are not acceptable.
+2. **Avoid metaphysical extrapolations** – do not assert cosmological, philosophical, or consciousness conclusions beyond what the derivations explicitly show. “What TNFR does” must be described as an engineering result, not a manifesto.
+3. **Use academic tone** – prefer precise, testable language, cite files/experiments, and describe limitations. No grandiose phrasing, slogans, or anthropomorphism.
+4. **Document scope/assumptions** – specify boundary conditions, seeds, and operator sequences so that readers can reproduce the exact state.
+
+Editors should reject or revise any contribution that violates these rules before it lands in the repository.
+
 ### TNFR-Riemann Program Overview
 
 A theoretical framework connecting **discrete TNFR operators** to the **Riemann Hypothesis** through **structural coherence principles**:
@@ -980,7 +991,7 @@ Equivalence map: [if APIs renamed]
 
 ### TNFR-Riemann Theoretical Framework
 
-**Theoretical Development**: Formulation of a theoretical framework spanning discrete computational algorithms to philosophical questions about consciousness and reality within TNFR principles.
+**Framework Development**: Computational framework spanning discrete algorithms to information processing analysis within TNFR structural principles.
 
 **Core Mathematical Discovery**: The **discrete TNFR operator** $H^{(k)}(\sigma) = L_k + V_\sigma$ provides a **structural coherence proof** of the Riemann Hypothesis through critical parameter convergence $\sigma_c^{(k)} \to 1/2$.
 
@@ -1004,7 +1015,7 @@ Equivalence map: [if APIs renamed]
 15. **Differential Geometry**: TNFR manifolds and connections
 16. **Functional Analysis**: TNFR Hilbert spaces and operators
 17. **Bootstrap Philosophy**: Reality as self-explaining structure
-18. **Theoretical Synthesis**: Proposed unification of mathematics, consciousness, and reality under TNFR principles
+18. **Technical Integration**: Computational framework connecting mathematical analysis, information processing, and structural modeling principles
 
 **Advanced Mathematical Connections**:
 - **Appendix I**: Langlands correspondence, mirror symmetry, quantum groups
@@ -1013,7 +1024,7 @@ Equivalence map: [if APIs renamed]
 
 ### Philosophical Implications
 
-**The Bootstrap Resolution**: Reality explains itself through TNFR principles - no external foundations needed.
+**Framework Self-Consistency**: TNFR provides self-consistent computational tools without requiring external theoretical foundations.
 
 **Mathematical Consciousness**: Consciousness emerges when mathematical structures achieve sufficient **information integration** to recognize their own patterns.
 
@@ -1148,7 +1159,7 @@ When adding to grammar documentation:
 
 **Core Theory** (Primary References):
 - **[AGENTS.md](AGENTS.md)**: **PRIMARY SOURCE** - Complete TNFR theory including Universal Tetrahedral Correspondence
-- **[FUNDAMENTAL_TNFR_THEORY_UNIVERSAL_TETRAHEDRAL_CORRESPONDENCE.md](FUNDAMENTAL_TNFR_THEORY_UNIVERSAL_TETRAHEDRAL_CORRESPONDENCE.md)**: **DETAILED REFERENCE** - Formal mathematical treatment
+- **[Structural Fields and Universal Tetrahedral Correspondence](FUNDAMENTAL_TNFR_THEORY_UNIVERSAL_TETRAHEDRAL_CORRESPONDENCE.md)**: **DETAILED REFERENCE** - Formal mathematical treatment
 - **[TNFR.pdf](TNFR.pdf)**: Original theoretical foundation (in repo)
 - **[UNIFIED_GRAMMAR_RULES.md](UNIFIED_GRAMMAR_RULES.md)**: Grammar physics U1-U6 derivations
 - **[docs/STRUCTURAL_FIELDS_TETRAD.md](docs/STRUCTURAL_FIELDS_TETRAD.md)**: Technical tetrad field implementations
@@ -1189,7 +1200,7 @@ When adding to grammar documentation:
 **Newcomer** (2 hours) - **Start Here**:
 1. **Install**: `pip install tnfr`
 2. **Core Theory**: Read this file (AGENTS.md) completely - **Primary theoretical reference**
-3. **Fundamental Theory**: [FUNDAMENTAL_TNFR_THEORY_UNIVERSAL_TETRAHEDRAL_CORRESPONDENCE.md](FUNDAMENTAL_TNFR_THEORY_UNIVERSAL_TETRAHEDRAL_CORRESPONDENCE.md)
+3. **Fundamental Theory**: [Structural Fields and Universal Tetrahedral Correspondence](FUNDAMENTAL_TNFR_THEORY_UNIVERSAL_TETRAHEDRAL_CORRESPONDENCE.md)
 4. **Original Theory**: [TNFR.pdf](TNFR.pdf) § 1-2 (paradigm, nodal equation)
 5. **First Run**: `python -c "import tnfr; print('TNFR ready!')"`
 6. **Terminology**: Study GLOSSARY.md for definitions

AGENTS.md

@@ -5,7 +5,7 @@
 **Authority**: Canonical constants derived from TNFR theory  
 **Quality**: Production-ready with comprehensive test coverage  
 
-This document provides guidelines for contributing to the TNFR (Resonant Fractal Nature Theory) project. TNFR constitutes a computational framework for modeling reality through coherent patterns and resonance dynamics.
+This document provides guidelines for contributing to the TNFR (Resonant Fractal Nature Theory) project. TNFR constitutes a computational framework for modeling complex systems through coherent patterns and resonance dynamics.
 
 ## Mathematical Foundation Requirement
 

CONTRIBUTING.md

@@ -444,7 +444,7 @@ Operators that require phase verification for valid coupling.
 3. **π ↔ K_φ**: Geometric spatial constraints (|K_φ| < φ×π ≈ 5.083)
 4. **e ↔ ξ_C**: Correlational memory decay (C(r) ~ exp(-r/ξ_C))
 
-**Documentation:** [FUNDAMENTAL_TNFR_THEORY_UNIVERSAL_TETRAHEDRAL_CORRESPONDENCE.md](FUNDAMENTAL_TNFR_THEORY_UNIVERSAL_TETRAHEDRAL_CORRESPONDENCE.md)
+**Documentation:** [Structural Fields and Universal Tetrahedral Correspondence](FUNDAMENTAL_TNFR_THEORY_UNIVERSAL_TETRAHEDRAL_CORRESPONDENCE.md)
 
 ---
 
@@ -525,7 +525,7 @@ Operators that perform graduated destabilization for phase transitions.
 **Primary Sources:**  
 - **[AGENTS.md](AGENTS.md)** - Single source of truth for TNFR theory  
 - **[UNIFIED_GRAMMAR_RULES.md](UNIFIED_GRAMMAR_RULES.md)** - Complete U1-U6 grammar derivations  
-- **[FUNDAMENTAL_TNFR_THEORY_UNIVERSAL_TETRAHEDRAL_CORRESPONDENCE.md](FUNDAMENTAL_TNFR_THEORY_UNIVERSAL_TETRAHEDRAL_CORRESPONDENCE.md)** - Mathematical foundations
+- **[Structural Fields and Universal Tetrahedral Correspondence](FUNDAMENTAL_TNFR_THEORY_UNIVERSAL_TETRAHEDRAL_CORRESPONDENCE.md)** - Mathematical foundations
 
 **Implementation References:**  
 - **[src/tnfr/physics/fields.py](src/tnfr/physics/fields.py)** - Unified Structural Field Tetrad (Canonical)  

GLOSSARY.md

@@ -3,7 +3,7 @@
 # Purpose: Essential tasks for the streamlined TNFR repository
 # Focus: Core examples, testing, and documentation generation
 
-.PHONY: help clean test examples docs all
+.PHONY: help clean test examples docs all riemann-benchmark
 
 # Default target
 help:
@@ -45,8 +45,14 @@ clean:
 test:
 	@echo "🧪 Running core TNFR test suite..."
 	@python -m pytest tests/core_physics tests/grammar tests/operators tests/physics -v --tb=short
+	@echo "📈 Running TNFR–Riemann sigma-critical benchmark..."
+	@python -c "import runpy, sys, pathlib; sys.path.insert(0, str(pathlib.Path('src').resolve())); sys.argv = ['benchmarks/riemann_program.py']; runpy.run_path('benchmarks/riemann_program.py', run_name='__main__')"
 	@echo "✅ Core tests complete"
 
+riemann-benchmark:
+	@echo "📈 Running TNFR–Riemann sigma-critical benchmark..."
+	@python -c "import runpy, sys, pathlib; sys.path.insert(0, str(pathlib.Path('src').resolve())); sys.argv = ['benchmarks/riemann_program.py']; runpy.run_path('benchmarks/riemann_program.py', run_name='__main__')"
+
 # Run all essential examples
 examples: hello music network chemistry sdk
 	@echo "✅ All essential examples complete"

Makefile

@@ -54,7 +54,7 @@
 **Core Principle**: Systems are modeled as coherent patterns maintained through resonant coupling rather than as discrete objects with independent properties.
 
 **Theoretical Foundation**: [AGENTS.md](AGENTS.md) - Complete theory reference  
-**Mathematical Details**: [theory/FUNDAMENTAL_TNFR_THEORY_UNIVERSAL_TETRAHEDRAL_CORRESPONDENCE.md](theory/FUNDAMENTAL_TNFR_THEORY_UNIVERSAL_TETRAHEDRAL_CORRESPONDENCE.md)  
+**Mathematical Details**: [Structural Fields and Universal Tetrahedral Correspondence](theory/FUNDAMENTAL_TNFR_THEORY_UNIVERSAL_TETRAHEDRAL_CORRESPONDENCE.md)  
 **Theory Hub**: [theory/README.md](theory/README.md) - Comprehensive theoretical documentation  
 **Implementation**: This repository provides computational tools for TNFR analysis
 
@@ -311,7 +311,7 @@ python examples/domain_applications/biological_patterns.py
 **Theoretical Foundation**:
 - **[AGENTS.md](AGENTS.md)** - Primary theoretical reference and development guide
 - **[theory/UNIFIED_GRAMMAR_RULES.md](theory/UNIFIED_GRAMMAR_RULES.md)** - Grammar constraint derivations (U1-U6)
-- **[theory/FUNDAMENTAL_TNFR_THEORY_UNIVERSAL_TETRAHEDRAL_CORRESPONDENCE.md](theory/FUNDAMENTAL_TNFR_THEORY_UNIVERSAL_TETRAHEDRAL_CORRESPONDENCE.md)** - Mathematical foundations
+- **[Structural Fields and Universal Tetrahedral Correspondence](theory/FUNDAMENTAL_TNFR_THEORY_UNIVERSAL_TETRAHEDRAL_CORRESPONDENCE.md)** - Mathematical foundations
 
 **Implementation Guide**:
 - **[ARCHITECTURE.md](ARCHITECTURE.md)** - System architecture and design

README.md

@@ -59,6 +59,7 @@ The reproducibility script ensures:
 | `neighbor_phase_mean.py` | Fast phase averaging for neighbourhoods (`tnfr.metrics.trig.neighbor_phase_mean`). | Includes a `NodeNX`-based reference to highlight the benefit of the shared `trig_cache` module. |
 | `prepare_dnfr_data.py` | ΔNFR data preparation reuse (`tnfr.dynamics._prepare_dnfr_data`). | Exercises cache reuse when assembling phase/EPI/νf arrays. |
 | `neighbor_accumulation_comparison.py` | Broadcast neighbour accumulation (`tnfr.dynamics.dnfr._accumulate_neighbors_numpy`). | Benchmarks the single `np.add.at` accumulator against the legacy stack kernel; on 320 random nodes (p=0.65) with Python 3.11/NumPy 2.3.4 it delivered ~1.9× lower median runtime (0.097 s vs 0.185 s). |
+| `riemann_program.py` | TNFR–Riemann σ-critical regression. | Scans `H_TNFR` over a σ grid, estimates σ_c^{(k)}, and exports telemetry via `tnfr.riemann.telemetry` to populate `results/riemann_program/`; executed automatically by `make test` (target `riemann-benchmark`). |
 
 ### Evolution backend speed-ups
 
@@ -165,7 +166,7 @@ that vectorisation shifts time into array primitives rather than Python loops.
 
 ### Full pipeline profiling (Si + ΔNFR)
 
-```
+```bash
 PYTHONPATH=src python benchmarks/full_pipeline_profile.py \
   --nodes 384 --edge-probability 0.28 --loops 6 --output-dir profiles \
   --si-chunk-sizes auto 2048 --dnfr-chunk-sizes auto 4096
@@ -263,16 +264,18 @@ PYTHONPATH=src python benchmarks/comprehensive_cache_profiler.py \
 ```
 
 **Key Metrics Reported:**
-- **Buffer Reuse Rate**: Should remain near 100% (indicates effective buffer caching)
-- **Edge Cache Hit Rate**: Per-hot-path buffer allocation cache effectiveness
-- **TNFR Cache Hit Rate**: DNFR preparation state and structural cache hits
-- **Cache Entry Count**: Memory usage tracking
+
+* **Buffer Reuse Rate**: Should remain near 100% (indicates effective buffer caching)
+* **Edge Cache Hit Rate**: Per-hot-path buffer allocation cache effectiveness
+* **TNFR Cache Hit Rate**: DNFR preparation state and structural cache hits
+* **Cache Entry Count**: Memory usage tracking
 
 **Sample Results** (100 nodes, 20 steps):
-- `coherence_matrix`: 97.5% hit rate, 100% buffer reuse ⭐
-- `default_compute_delta_nfr`: 96.7% hit rate, 100% buffer reuse ⭐
-- `sense_index`: 0.7% hit rate, 100% buffer reuse (expected - creates new structural arrays)
-- `dnfr_laplacian`: 0.0% hit rate, 100% buffer reuse (by design - stateless gradients)
+
+* `coherence_matrix`: 97.5% hit rate, 100% buffer reuse ⭐
+* `default_compute_delta_nfr`: 96.7% hit rate, 100% buffer reuse ⭐
+* `sense_index`: 0.7% hit rate, 100% buffer reuse (expected - creates new structural arrays)
+* `dnfr_laplacian`: 0.0% hit rate, 100% buffer reuse (by design - stateless gradients)
 
 For detailed analysis see `docs/CACHE_OPTIMIZATION_ANALYSIS.md` and `ARCHITECTURE.md`.