Release 0.0.3.8: consolidate relational patterns, engine contracts and documentation

Author: TNFR AI Agent

.env.example

@@ -1,59 +1,25 @@
-# TNFR Engine Environment Configuration
-# Copy this file to .env and fill in your actual values
-# NEVER commit .env files with real credentials to version control
-
-# ============================================================================
-# Development Configuration
-# ============================================================================
-
-# PyPI Publishing Configuration (for release scripts)
-# Use API tokens for enhanced security: https://pypi.org/help/#apitoken
-PYPI_USERNAME=__token__
-PYPI_PASSWORD=pypi-XXXXXXXXXXXXXXXXXXXXXXXX  # Your PyPI API token
-PYPI_API_TOKEN=pypi-XXXXXXXXXXXXXXXXXXXXXXXX  # Alternative name
-TWINE_USERNAME=__token__
-TWINE_PASSWORD=pypi-XXXXXXXXXXXXXXXXXXXXXXXX  # Your PyPI API token
-PYPI_REPOSITORY=pypi  # or 'testpypi' for testing
-
-# GitHub Configuration (for security dashboard and CI scripts)
-GITHUB_TOKEN=ghp_XXXXXXXXXXXXXXXXXXXXXXXX  # GitHub Personal Access Token
-GITHUB_REPOSITORY=fermga/TNFR-Python-Engine  # Format: owner/repo
-
-# Redis Configuration (for RedisCacheLayer with authentication)
-REDIS_HOST=localhost
-REDIS_PORT=6379
-REDIS_PASSWORD=your-redis-password-here
-REDIS_DB=0
-REDIS_USE_TLS=false
-
-# Cache Signing Configuration (for hardened cache security)
-# Generate a strong random secret: python -c "import secrets; print(secrets.token_hex(32))"
-TNFR_CACHE_SECRET=  # 64-character hex string recommended
-
-# ============================================================================
-# TNFR Engine Configuration
-# ============================================================================
-
-# Logging Configuration
-TNFR_LOG_LEVEL=INFO  # DEBUG, INFO, WARNING, ERROR, CRITICAL
-
-# Reproducibility Configuration
-TNFR_RANDOM_SEED=42  # For deterministic simulations
-
-# Performance Configuration
-TNFR_BACKEND=numpy  # numpy, jax, or torch
-TNFR_CACHE_ENABLED=true
-
-# ============================================================================
-# Security Best Practices
-# ============================================================================
-#
-# 1. NEVER commit this file with real credentials
-# 2. Use API tokens instead of passwords where possible
-# 3. Rotate credentials regularly
-# 4. Use different credentials for development, staging, and production
-# 5. Store production secrets in secure secret management systems
-# 6. Grant minimal necessary permissions to all tokens
-# 7. Revoke tokens immediately if compromised
-#
-# For more information, see SECURITY.md
+# Optional environment inputs; this file is not loaded by the engine.
+# Export values through your shell/application, or explicitly use an external
+# environment-file loader. Keep actual credentials out of version control.
+
+# Backend factory default when no explicit backend is supplied.
+# Optional backends need their corresponding installed dependency extra.
+TNFR_BACKEND=numpy
+
+# Optional signed persistence helpers read this hexadecimal secret.
+# Generate a value with: python -c "import secrets; print(secrets.token_hex(32))"
+# TNFR_CACHE_SECRET=
+
+# Optional tnfr.config.security.load_redis_config() inputs. The caller must
+# explicitly use the returned configuration; setting these does not enable Redis.
+# REDIS_HOST=localhost
+# REDIS_PORT=6379
+# REDIS_PASSWORD=
+# REDIS_DB=0
+# REDIS_USE_TLS=false
+
+# Specify study seeds through StudySpec/CLI or the relevant graph configuration.
+# TNFR_RANDOM_SEED, TNFR_CACHE_ENABLED and TNFR_LOG_LEVEL are not automatic
+# engine controls. Logging uses Python logging configuration.
+# Release publishing uses the GitHub workflow's trusted publisher; it does not
+# read this file. See .github/WORKFLOWS.md and SECURITY.md for their actual scopes.

.gitattributes

@@ -38,5 +38,5 @@ theory/research/archive/AGENT_SYNTHESIS_PRE_DOCUMENTATION_CLEANUP_2026-09-19.txt
 theory/research/archive/NUCLEUS_B_PROPOSAL_PRE_DOCUMENTATION_CLEANUP_2026-09-19.txt -text -whitespace
 theory/research/archive/README_PRE_DOCUMENTATION_CLEANUP_2026-09-19.txt -text -whitespace
 theory/research/archive/APPLIED_ANALYSIS_PRE_DOCUMENTATION_CLEANUP_2026-09-19.txt -text -whitespace
-factorization-lab/notebooks/archive/spectral_history_legacy_2026_09_19.ipynb -text -whitespace
+applications/factorization-lab/notebooks/archive/spectral_history_legacy_2026_09_19.ipynb -text -whitespace
 theory/research/archive/DEVELOPMENT_LOG_PRE_0.0.3.6_2026-09-19.txt -text -whitespace

.github/agents/my-agent.md

@@ -7,15 +7,17 @@ on:
       - '**.md'
       - 'TNFR_lineas_de_investigacion.txt'
       - 'docs/assets/**'
-      - 'factorization-lab/notebooks/**'
+      - 'applications/factorization-lab/notebooks/**'
       - 'src/tnfr/operators/operator_contracts.py'
       - 'tests/scripts/test_documentation.py'
+      - 'tests/scripts/test_glossary.py'
       - 'mkdocs.yml'
       - 'pyproject.toml'
       - '.zenodo.json'
       - 'CITATION.cff'
       - 'src/tnfr/_version.py'
       - 'scripts/check_documentation.py'
+      - 'scripts/check_glossary.py'
       - 'scripts/prepare_docs.py'
       - 'scripts/clean_repository.py'
       - 'scripts/verify_internal_references.py'
@@ -26,15 +28,17 @@ on:
       - '**.md'
       - 'TNFR_lineas_de_investigacion.txt'
       - 'docs/assets/**'
-      - 'factorization-lab/notebooks/**'
+      - 'applications/factorization-lab/notebooks/**'
       - 'src/tnfr/operators/operator_contracts.py'
       - 'tests/scripts/test_documentation.py'
+      - 'tests/scripts/test_glossary.py'
       - 'mkdocs.yml'
       - 'pyproject.toml'
       - '.zenodo.json'
       - 'CITATION.cff'
       - 'src/tnfr/_version.py'
       - 'scripts/check_documentation.py'
+      - 'scripts/check_glossary.py'
       - 'scripts/prepare_docs.py'
       - 'scripts/clean_repository.py'
       - 'scripts/verify_internal_references.py'

.github/workflows/docs.yml

@@ -1,8 +1,8 @@
 {
   "title": "TNFR-Python-Engine: Resonant Fractal Nature Theory Implementation",
-  "description": "<p>TNFR-Python-Engine is a Python framework for coherent-pattern analysis on graph-coupled networks. The nodal relation dEPI/dt = nu_f DeltaNFR organizes a declared evolution model; pressure, phase, capacity, support and any additional forcing require their own specifications.</p><p>Version 0.0.3.7 consolidates shared numerical admission, operator contracts, cache invalidation and runtime execution provenance. Runtime step ordinals are independent of retained metrics and physical time. REMESH uses explicit cooldown bases and bounded histories. SDK and CLI reports retain unavailable diagnostic results and provenance instead of substituting evidence. The 13 registered operators, grammar U1-U6, shared integration and structural-field tetrad remain scoped engine interfaces.</p><p>The release revises foundational documentation and centralizes the active research plan. A fixed finite P3 experiment compares two declared phase-pressure laws against independent form-response predictions, with pressure, integration and rounding defects separated. It distinguishes their implemented responses without selecting a physical law or proving autonomous pattern formation. Exact identities, conditional theorems, numerical observations and auxiliary models retain separate scopes.</p><p>Unsupported particle and chemistry mappings, Navier-Stokes and Yang-Mills wrappers, redundant type probes and obsolete demonstrations are removed. These are intentional API removals; migration boundaries and recoverable historical sources are documented in the archive index. Routine engine/API checks are separated from retained research suites, which remain explicitly executable.</p><p>See the <a href=\"https://github.com/fermga/TNFR-Python-Engine/releases/tag/v0.0.3.7\">0.0.3.7 release</a>, <a href=\"https://github.com/fermga/TNFR-Python-Engine/tree/v0.0.3.7\">versioned source</a>, <a href=\"https://pypi.org/project/tnfr/0.0.3.7/\">Python package</a>, <a href=\"https://github.com/fermga/TNFR-Python-Engine/blob/v0.0.3.7/theory/research/archive/README.md\">compatibility boundaries</a> and <a href=\"https://fermga.github.io/TNFR-Python-Engine/\">current documentation</a>.</p>",
-  "version": "0.0.3.7",
-  "publication_date": "2026-09-20",
+  "description": "<p>TNFR-Python-Engine is a Python framework for graph-coupled nodal dynamics and coherent-pattern research. The relation dEPI/dt = nu_f DeltaNFR connects form change, reorganization capacity and pressure. Pressure, phase, capacity, support, clock and forcing laws require explicit specifications.</p><p>Version 0.0.3.8 integrates an explicitly selected relational form-phase model with held capacity, shared SDK execution and detached reports. Conditional results address recovery, formation on supplied support, composition, transmission and reduced descriptions with memory. A proved example permits one passive bridge relocation between two prepared five-node rings while retaining their pattern recovery. Its open recovery region does not establish stability under arbitrary repeated switching.</p><p>Read-only attachment and relocation observers report changes in represented storage and rates, support cuts, transport reset and explicitly supplied work. They neither mutate live support nor select events. Numerical admission, JSON serialization, diagnostic availability and cache ownership are consolidated across the engine, CLI and SDK. Documentation is organized by theory, contracts and usage; optional arithmetic applications are separated under applications/.</p><p>Exact identities, conditional mathematical results, finite observations and auxiliary constructions retain distinct scopes. A support budget does not select an event or its clock; these remain the next research question. Physical identification, particles and autonomous substrate creation are not established.</p><p>See the <a href=\"https://github.com/fermga/TNFR-Python-Engine/releases/tag/v0.0.3.8\">0.0.3.8 release</a>, <a href=\"https://github.com/fermga/TNFR-Python-Engine/tree/v0.0.3.8\">versioned source</a>, <a href=\"https://pypi.org/project/tnfr/0.0.3.8/\">Python package</a>, <a href=\"https://github.com/fermga/TNFR-Python-Engine/blob/v0.0.3.8/theory/README.md\">theory catalog</a> and <a href=\"https://fermga.github.io/TNFR-Python-Engine/\">current documentation</a>.</p>",
+  "version": "0.0.3.8",
+  "publication_date": "2026-09-27",
   "creators": [
     {
       "name": "Martinez Gamo, F. F.",
@@ -33,7 +33,7 @@
       "resource_type": "software"
     },
     {
-      "identifier": "https://pypi.org/project/tnfr/0.0.3.7/",
+      "identifier": "https://pypi.org/project/tnfr/0.0.3.8/",
       "relation": "isSupplementTo",
       "resource_type": "software"
     }