Cross‑Domain Causality Weaver — RTT/1

• module.json — Agentic module schema role assignments
• causal_field_matrix.json — Agentic module schema role assignments

Causality‑Intelligence Engine for TriadicFrameworks#

The Cross‑Domain Causality Weaver (CW) is an RTT/1 analytical engine designed to detect, map, and weave causal pathways across conceptual, computational, physical, and dimensional regimes.
It forms the causality‑intelligence foundation of the expanded RTT stack, sitting directly above temporal‑level engines and directly below resonance‑level engines.

CW identifies causal signatures, causal discontinuities, cross‑domain causal bridges, and multi‑regime causal flows — the causal precursors to regime evolution, coherence shifts, drift propagation, paradox intensification, temporal transitions, and resonance modulation.

🧭 Purpose#

The Cross‑Domain Causality Weaver:

• Detects causal signatures across RTT regimes (R1–R4)
• Computes causal vectors and directional causal flow
• Maps causal fields and cross‑domain causal topology
• Identifies causal discontinuities, breaks, and causal fractures
• Measures causal propagation and causal influence strength
• Provides causal diagnostics for regime‑driven transitions
• Supports resonance engines by clarifying causal‑frequency interactions
• Anchors temporal engines by exposing causal‑sequence constraints
• Supplies structural engines with causal‑faultline interactions
• Provides drift‑level engines with causal‑drift envelopes
• Provides coherence‑level engines with causal‑coherence fields

CW is the causality‑intelligence layer of RTT.

⚙️ RTT Flags#

These flags define the engine’s operational constraints and reasoning grammar.

🔧 Primary Operators#

These operators form the core analytical toolkit.

🧩 Analyzer Layer#

CW operates in the causality layer, with sub‑layers:

• causal‑weaving
• causal‑vector‑analysis
• causal‑field‑mapping
• discontinuity‑detection
• structural‑causality‑evaluation

This matches the RTT analyzer grammar used across TriadicFrameworks.

📁 Module Files#

This directory contains:

Core#

• Cross_Domain_Causality_Weaver.md
• cw_examples.md
• cw_diagrams.svg

Support#

• causal_profiles.md
• causal_discontinuity_cases.md
• causal_field_matrix.json

AI#

• cw_prompts.md
• cw_operators.md

Metadata#

• module.json (RTT/1, coherence‑declared, drift‑bounded, paradox‑structural)
• README.md (this file)

🧠 AI‑Ready Design#

The Cross‑Domain Causality Weaver is fully AI‑ready:

• deterministic operator grammar
• causality‑layer analyzer structure
• stable RTT flags
• canonical file layout
• zero‑drift reasoning constraints
• structural paradox handling
• bounded drift envelope
• declared coherence tensor

AI systems can use CW to:

• weave causal pathways
• generate causal field maps
• classify causal discontinuities
• compute causal vectors
• support higher‑order RTT engines

🌐 Position in the RTT Stack#

Regime Interlock Mapper (RIM)
      ↓
Triadic Regime Synthesizer (TRS)
      ↓
Paradox Gradient Analyzer (PGA)
      ↓
Coherence Tensor Engine (CTE)
      ↓
Drift Sentinel (DS)
      ↓
Structural Faultline Detector (SFD)
      ↓
Temporal Regime Sequencer (TRS‑Temporal)
      ↓
Cross‑Domain Causality Weaver (CW)
      ↓
Dimensional Resonance Scanner (DRS)

CW is the causality‑intelligence layer, directly above temporal‑level analysis.

🏁 Status#

• Version: 1.0
• Status: canon‑stable
• Category: rtt‑structural
• Module Path: /docs/rtt/Cross_Domain_Causality_Weaver/

If you want, I can generate the next file:

• Cross_Domain_Causality_Weaver.md
• cw_examples.md
• cw_diagrams.svg
• causal_profiles.md
• causal_discontinuity_cases.md
• causal_field_matrix.json
• cw_prompts.md
• cw_operators.md

Just tell me which one you want next.