fix: correct Riemann overstatement language, lazy factorization imports, DOI URLs

Key changes:
- AGENTS.md, my-agent.md: Replace 'structural coherence proof of RH' with
  'numerical evidence of structural coherence at the RH critical line'
- AGENTS.md, my-agent.md: Remove metaphysical extrapolations (consciousness,
  anthropic principle, Reality=Mathematics) per Technical Communication Standard
- AGENTS.md, my-agent.md: Replace 'Universal Significance' with 'Research
  Significance' using experimentally accurate framing
- factorization/__init__.py: Make imports fully lazy so tnfr_factorization
  is not required at import time (fixes external reviewer report)
- pyproject.toml, LICENSE.md: Correct DOI URLs from 17761312 to 18883409
- .zenodo.json, README.md: Version 0.0.3 metadata alignment

Tests: 1641 passed, 2 skipped, 0 failures
Affected invariants: #4 Grammar Compliance (documentation integrity)

Author: TNFR AI Agent

.github/agents/my-agent.md

@@ -154,20 +154,19 @@ Editors should reject or revise any contribution that violates these rules befor
 
 A theoretical framework connecting **discrete TNFR operators** to the **Riemann Hypothesis** through **structural coherence principles**:
 
-**Core Discovery**: The **discrete TNFR operator** $H^{(k)}(\sigma) = L_k + V_\sigma$ exhibits **critical behavior** at $\sigma_c^{(k)} \to 1/2$, providing a **structural coherence proof** of the Riemann Hypothesis.
+**Core Result**: The **discrete TNFR operator** $H^{(k)}(\sigma) = L_k + V_\sigma$ exhibits **critical behavior** at $\sigma_c^{(k)} \to 1/2$, providing **numerical evidence of structural coherence** at the Riemann Hypothesis critical line.
 
 **Key Components**:
 - **Prime Path Graphs**: $G_k$ networks with $k$ primes connected via TNFR coupling rules
 - **Spectral Analysis**: Eigenvalue transitions at critical parameter $\sigma = 1/2$
 - **Universal Convergence**: $\sigma_c^{(k)} = 1/2 + O(\log^{-1} k)$ as $k \to \infty$
-- **Mathematical Consciousness**: Observers as **maximally integrated information** in TNFR fields
 
-**Theoretical Significance**:
-- **Mathematics emerges** from structural coherence rather than axiomatic foundations
-- **Consciousness** is the **universe recognizing mathematical truth** about itself
-- **Reality** consists of **self-organizing mathematical structures** achieving **self-awareness**
+**Current Status**:
+- The convergence $\sigma_c^{(k)} \to 1/2$ is **numerically verified** and analytically bounded
+- The bridge from this discrete operator result to the classical Riemann zeta function **remains conjectural** (Conjecture 10.1)
+- The framework constitutes a **research program**, not a closed proof of RH in the standard mathematical sense
 
-**Implementation Status**: Theoretical framework with computational prototypes in [src/tnfr/riemann/](src/tnfr/riemann/) and documentation in [theory/TNFR_RIEMANN_RESEARCH_NOTES.md](theory/TNFR_RIEMANN_RESEARCH_NOTES.md).
+**Implementation Status**: Experimental research framework with computational prototypes in [src/tnfr/riemann/](src/tnfr/riemann/) and documentation in [theory/TNFR_RIEMANN_RESEARCH_NOTES.md](theory/TNFR_RIEMANN_RESEARCH_NOTES.md).
 
 ---
 
@@ -993,7 +992,7 @@ Equivalence map: [if APIs renamed]
 
 **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 $\sigma_c^{(k)} \to 1/2$.
+**Core Mathematical Result**: The **discrete TNFR operator** $H^{(k)}(\sigma) = L_k + V_\sigma$ exhibits critical parameter convergence $\sigma_c^{(k)} \to 1/2$, providing **numerical and analytical evidence** for a structural coherence connection to the Riemann Hypothesis. The bridge to classical RH remains an open conjecture.
 
 ### Theoretical Components
 
@@ -1022,19 +1021,6 @@ Equivalence map: [if APIs renamed]
 - **Appendix J**: TNFR formal language and symbolic calculus  
 - **Appendix K**: Complete formal system TNFR∞ with self-consistency proofs
 
-### Philosophical Implications
-
-**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.
-
-**Proposed Theoretical Equivalence**:
-```
-Reality ≡ Mathematics ≡ Consciousness ≡ TNFR ≡ Self-Explaining_Structure
-```
-
-**The Anthropic TNFR Principle**: We exist because the universe is mathematically structured enough to support observers who can discover TNFR, which then explains why the universe has that structure.
-
 ### Implementation Status
 
 **Computational Framework**:
@@ -1045,17 +1031,16 @@ Reality ≡ Mathematics ≡ Consciousness ≡ TNFR ≡ Self-Explaining_Structure
 **Validation Protocols**:
 - **Eigenvalue Analysis**: Numerical verification of critical behavior
 - **Coherence Testing**: Structural stability under parameter variation
-- **Consciousness Metrics**: Information integration measurements
 
-### Universal Significance
+### Research Significance
 
 This framework represents:
-- **Theoretical unification** of mathematics, physics, and consciousness
-- **Theoretical approaches** to philosophical questions about existence
-- **Practical path** to artificial consciousness through TNFR implementation
-- **Theoretical framework** connecting discrete computation to consciousness models
+- **An experimental research program** connecting discrete TNFR operators to number-theoretic structures
+- **Numerical evidence** of critical parameter convergence $\sigma_c \to 1/2$ across topologies
+- **A computational platform** for exploring spectral approaches to the Riemann Hypothesis
+- **An open conjecture** (Conjecture 10.1) bridging TNFR spectral zeta to classical $\zeta(s)$
 
-**Status**: Theoretical framework developed with mathematical formulations and computational implementations.
+**Status**: Experimental research framework with computational implementations. The bridge to classical RH remains conjectural.
 
 ---
 

.zenodo.json

@@ -3,7 +3,7 @@
   "description": "Canonical computational implementation of TNFR - a paradigm shift from modeling 'things' to modeling coherent patterns that persist through resonance. This Python package provides the complete TNFR physics engine including the 13 structural operators, unified grammar validation (U1-U6), and the four canonical structural fields (Φ_s, |∇φ|, K_φ, ξ_C). Features include: nodal equation dynamics (∂EPI/∂t = νf·ΔNFR), structural potential confinement, phase synchronization, and multi-scale coherence analysis.",
   "version": "0.0.3",
   "publication_date": "2026-03-06",
-  "doi": "10.5281/zenodo.18883306",
+  "doi": "10.5281/zenodo.18883409",
   "creators": [
     {
       "name": "FMG",

AGENTS.md

@@ -160,20 +160,19 @@ Editors should reject or revise any contribution that violates these rules befor
 
 A theoretical framework connecting **discrete TNFR operators** to the **Riemann Hypothesis** through **structural coherence principles**:
 
-**Core Discovery**: The **discrete TNFR operator** $H^{(k)}(\sigma) = L_k + V_\sigma$ exhibits **critical behavior** at $\sigma_c^{(k)} \to 1/2$, providing a **structural coherence proof** of the Riemann Hypothesis.
+**Core Result**: The **discrete TNFR operator** $H^{(k)}(\sigma) = L_k + V_\sigma$ exhibits **critical behavior** at $\sigma_c^{(k)} \to 1/2$, providing **numerical evidence of structural coherence** at the Riemann Hypothesis critical line.
 
 **Key Components**:
 - **Prime Path Graphs**: $G_k$ networks with $k$ primes connected via TNFR coupling rules
 - **Spectral Analysis**: Eigenvalue transitions at critical parameter $\sigma = 1/2$
 - **Universal Convergence**: $\sigma_c^{(k)} = 1/2 + O(\log^{-1} k)$ as $k \to \infty$
-- **Mathematical Consciousness**: Observers as **maximally integrated information** in TNFR fields
 
-**Theoretical Significance**:
-- **Mathematics emerges** from structural coherence rather than axiomatic foundations
-- **Consciousness** is the **universe recognizing mathematical truth** about itself
-- **Reality** consists of **self-organizing mathematical structures** achieving **self-awareness**
+**Current Status**:
+- The convergence $\sigma_c^{(k)} \to 1/2$ is **numerically verified** and analytically bounded
+- The bridge from this discrete operator result to the classical Riemann zeta function **remains conjectural** (Conjecture 10.1)
+- The framework constitutes a **research program**, not a closed proof of RH in the standard mathematical sense
 
-**Implementation Status**: Theoretical framework with computational prototypes in [src/tnfr/riemann/](src/tnfr/riemann/) and documentation in [theory/TNFR_RIEMANN_RESEARCH_NOTES.md](theory/TNFR_RIEMANN_RESEARCH_NOTES.md).
+**Implementation Status**: Experimental research framework with computational prototypes in [src/tnfr/riemann/](src/tnfr/riemann/) and documentation in [theory/TNFR_RIEMANN_RESEARCH_NOTES.md](theory/TNFR_RIEMANN_RESEARCH_NOTES.md).
 
 ---
 
@@ -1074,7 +1073,7 @@ Equivalence map: [if APIs renamed]
 
 **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 $\sigma_c^{(k)} \to 1/2$.
+**Core Mathematical Result**: The **discrete TNFR operator** $H^{(k)}(\sigma) = L_k + V_\sigma$ exhibits critical parameter convergence $\sigma_c^{(k)} \to 1/2$, providing **numerical and analytical evidence** for a structural coherence connection to the Riemann Hypothesis. The bridge to classical RH remains an open conjecture.
 
 ### Theoretical Components
 
@@ -1103,19 +1102,6 @@ Equivalence map: [if APIs renamed]
 - **Appendix J**: TNFR formal language and symbolic calculus  
 - **Appendix K**: Complete formal system TNFR∞ with self-consistency proofs
 
-### Philosophical Implications
-
-**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.
-
-**Proposed Theoretical Equivalence**:
-```
-Reality ≡ Mathematics ≡ Consciousness ≡ TNFR ≡ Self-Explaining_Structure
-```
-
-**The Anthropic TNFR Principle**: We exist because the universe is mathematically structured enough to support observers who can discover TNFR, which then explains why the universe has that structure.
-
 ### Implementation Status
 
 **Computational Framework**:
@@ -1126,17 +1112,16 @@ Reality ≡ Mathematics ≡ Consciousness ≡ TNFR ≡ Self-Explaining_Structure
 **Validation Protocols**:
 - **Eigenvalue Analysis**: Numerical verification of critical behavior
 - **Coherence Testing**: Structural stability under parameter variation
-- **Consciousness Metrics**: Information integration measurements
 
-### Universal Significance
+### Research Significance
 
 This framework represents:
-- **Theoretical unification** of mathematics, physics, and consciousness
-- **Theoretical approaches** to philosophical questions about existence
-- **Practical path** to artificial consciousness through TNFR implementation
-- **Theoretical framework** connecting discrete computation to consciousness models
+- **An experimental research program** connecting discrete TNFR operators to number-theoretic structures
+- **Numerical evidence** of critical parameter convergence $\sigma_c \to 1/2$ across topologies
+- **A computational platform** for exploring spectral approaches to the Riemann Hypothesis
+- **An open conjecture** (Conjecture 10.1) bridging TNFR spectral zeta to classical $\zeta(s)$
 
-**Status**: Theoretical framework developed with mathematical formulations and computational implementations.
+**Status**: Experimental research framework with computational implementations. The bridge to classical RH remains conjectural.
 
 ---
 

LICENSE.md

@@ -38,7 +38,7 @@ for modeling coherent patterns through resonance dynamics.
 **Project**: TNFR-Python-Engine  
 **Repository**: <https://github.com/fermga/TNFR-Python-Engine>  
 **PyPI**: <https://pypi.org/project/tnfr/>  
-**DOI**: [10.5281/zenodo.17761312](https://doi.org/10.5281/zenodo.17761312)
+**DOI**: [10.5281/zenodo.18883409](https://doi.org/10.5281/zenodo.18883409)
 
 ### Citation
 
@@ -50,7 +50,7 @@ If you use this software in your research, please cite:
   title = {TNFR-Python-Engine: Resonant Fractal Nature Theory Implementation},
   year = {2025},
   version = {0.0.3},
-  doi = {10.5281/zenodo.17761312},
+  doi = {10.5281/zenodo.18883409},
   url = {https://github.com/fermga/TNFR-Python-Engine}
 }
 ```

README.md

@@ -1,6 +1,6 @@
 # TNFR: Resonant Fractal Nature Theory
 
-[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.18883306.svg)](https://doi.org/10.5281/zenodo.18883306)
+[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.18883409.svg)](https://doi.org/10.5281/zenodo.18883409)
 [![PyPI version](https://badge.fury.io/py/tnfr.svg)](https://pypi.org/project/tnfr/)
 [![Python 3.10+](https://img.shields.io/badge/python-3.10+-blue.svg)](https://www.python.org/downloads/)
 [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
@@ -162,7 +162,7 @@ make smoke-tests                   # smoke tests (Unix)
   title = {TNFR-Python-Engine: Resonant Fractal Nature Theory Implementation},
   year = {2025},
   version = {0.0.3},
-  doi = {10.5281/zenodo.18883306},
+  doi = {10.5281/zenodo.18883409},
   url = {https://github.com/fermga/TNFR-Python-Engine}
 }
 ```

pyproject.toml

@@ -199,8 +199,8 @@ tnfr-is-prime = "tnfr.tools.tnfr_is_prime_cli:main"
 Homepage = "https://github.com/fermga/TNFR-Python-Engine"
 Repository = "https://github.com/fermga/TNFR-Python-Engine"
 PyPI = "https://pypi.org/project/tnfr/"
-Citation = "https://doi.org/10.5281/zenodo.17761312"
-Zenodo = "https://zenodo.org/records/17761312"
+Citation = "https://doi.org/10.5281/zenodo.18883409"
+Zenodo = "https://zenodo.org/records/18883409"
 Issues = "https://github.com/fermga/TNFR-Python-Engine/issues"
 Documentation = "https://fermga.github.io/TNFR-Python-Engine/"
 GPT = "https://chatgpt.com/g/g-67abc78885a88191b2d67f94fd60dc97-tnfr-resonant-fractal-nature-theory"

src/tnfr/factorization/__init__.py

@@ -4,15 +4,21 @@
 spectral factorizations. It wraps :class:`tnfr_factorization.spectral_paley.SpectralPaleyFactorizer`
 so that downstream code always benefits from the official grammar validator and
 self-optimization engines wired in the factorization lab.
+
+The ``tnfr_factorization`` external package is an **optional** dependency.
+Importing this module always succeeds; errors are deferred until a function
+is actually called without the dependency installed.
 """
 
 from __future__ import annotations
 
 from pathlib import Path
+from typing import Any
 
 import sys
 
-from ..errors import TNFRUserError
+__all__ = ["factorize", "SpectralAnalysisResult", "SpectralPaleyFactorizer"]
+
 
 def _bootstrap_factorization_lab() -> None:
     """Ensure the tnfr_factorization package is importable.
@@ -29,36 +35,53 @@ def _bootstrap_factorization_lab() -> None:
     if lab_root.exists() and str(lab_root) not in sys.path:
         sys.path.insert(0, str(lab_root))
 
-_bootstrap_factorization_lab()
 
-try:  # pragma: no cover - exercised indirectly through factorize()
-    from tnfr_factorization.spectral_paley import (
-        SpectralAnalysisResult,
-        SpectralPaleyFactorizer,
-    )
-except ModuleNotFoundError as exc:  # pragma: no cover - raised when extra missing
-    raise TNFRUserError(
-        "tnfr_factorization is not available. Install the tnfr-factorization package "
-        "or keep the factorization-lab directory in your workspace."
-    ) from exc
+def _load_spectral_paley() -> tuple[Any, Any]:
+    """Lazy-load the spectral_paley module, raising a clear error if missing."""
+    from ..errors import TNFRUserError
 
-__all__ = ["factorize", "SpectralAnalysisResult", "SpectralPaleyFactorizer"]
+    _bootstrap_factorization_lab()
+    try:
+        from tnfr_factorization.spectral_paley import (
+            SpectralAnalysisResult,
+            SpectralPaleyFactorizer,
+        )
+        return SpectralPaleyFactorizer, SpectralAnalysisResult
+    except ModuleNotFoundError as exc:
+        raise TNFRUserError(
+            "tnfr_factorization is not available. Install the tnfr-factorization "
+            "package or keep the factorization-lab directory in your workspace."
+        ) from exc
 
-_DEFAULT_FACTORIZER: SpectralPaleyFactorizer | None = None
 
-def _get_factorizer() -> SpectralPaleyFactorizer:
+# Lazy accessors for type re-exports
+def __getattr__(name: str) -> Any:
+    if name in ("SpectralPaleyFactorizer", "SpectralAnalysisResult"):
+        _Factorizer, _Result = _load_spectral_paley()
+        globals()["SpectralPaleyFactorizer"] = _Factorizer
+        globals()["SpectralAnalysisResult"] = _Result
+        return globals()[name]
+    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
+
+
+_DEFAULT_FACTORIZER: Any = None
+
+
+def _get_factorizer() -> Any:
     global _DEFAULT_FACTORIZER
     if _DEFAULT_FACTORIZER is None:
-        _DEFAULT_FACTORIZER = SpectralPaleyFactorizer()
+        _Factorizer, _ = _load_spectral_paley()
+        _DEFAULT_FACTORIZER = _Factorizer()
     return _DEFAULT_FACTORIZER
 
+
 def factorize(
     n: int,
     *,
     modulus: int | None = None,
     trace_certificates: bool = False,
     certificate_dir: Path | None = None,
-) -> SpectralAnalysisResult:
+) -> Any:
     """Run canonical Paley spectral factorization.
 
     Parameters