🌀⚙️📜 Workflow Engines

• workflows_module.json — Agentic module schema role assignments

Operational layer for RTT‑Inside: batches, pipelines, and remix generation#

This directory contains lightweight, substrate‑agnostic workflow modules used across TriadicFrameworks for scroll generation, batch execution, remix lineage creation, and resonance‑aware pipeline orchestration.

Each workflow is intentionally minimal: no external dependencies, no hidden state, and no assumptions about the host environment. They are designed to be portable, inspectable, and safe to remix.

🗂️ Index Card#

Lightweight, substrate‑agnostic execution tools for scrolls, batches, and remix lineages.

• 📦 Batch Orchestrator — deterministic multi‑scroll execution
• 🎨 Remix Generator — lineage‑safe remix creation
• 🌐 Scroll Pipeline (JS) — browser‑native execution path
• 🐍 Scroll Pipeline (Python) — programmatic scroll engine

These engines form the operational layer of RTT‑Inside, bridging scroll artifacts with executable pipelines across languages and environments.

📁 Contents of workflows folder#

🛤️ corridor_batch_validator.py#

Corridor‑level batch validator using RTT‑QEB primitives.

• Fetches corridor metadata
• Normalizes rail signatures
• Computes RCI and glyph
• Compares against stored metadata
• Emits a timestamped YAML validation report

📦 batch_orchestrator.py#

A scroll‑centric batch runner for executing multiple .fff artifacts through the Python scroll pipeline.

• Accepts file paths, in‑memory scroll objects, or mixed lists
• Loads and normalizes scrolls when needed
• Executes each scroll via scroll_pipeline.py
• Captures outputs, lineage metadata, and warnings
• Aggregates results into a deterministic batch report
• Optionally writes a timestamped YAML report for archival or analysis

This engine is substrate‑agnostic and forms the batch‑execution counterpart to the Python and JS scroll pipelines.

🎨 remix_generation.py#

A remix‑lineage generator that produces new scroll variants from a base artifact.

• Applies remix rules from TFT_3Pack
• Preserves canonical anchors (τᵣ, D3/D6/D9, emitter constants)
• Generates remix metadata blocks for downstream tools
• Ideal for student remix submissions or experimental scroll forks

🌐 scrollPipeline.js#

A JavaScript‑based scroll pipeline for browser‑side or lightweight client execution.

• Runs resonance flows without Python
• Integrates with rtt.js and site‑level overlays
• Useful for interactive demos, web‑native scroll previews, and teaching tools

🐍 scroll_pipeline.py#

The Python counterpart to the JS pipeline.

• Provides a stable API for scroll parsing, validation, and execution
• Supports .fff format operations
• Can be embedded into notebooks, CLI tools, or batch systems

🔧 Purpose of This Folder#

The workflows directory acts as the operational layer of TriadicFrameworks:

• A place for small, composable engines
• A bridge between RTT theory and practical execution
• A toolkit for students, developers, and researchers working with scrolls, .fff files, or resonance‑aware pipelines
• A foundation for future integrations (AI drift calibration, substrate‑mind science, dimensional‑core validators)

These workflows intentionally avoid domain‑specific assumptions so they can run across the entire TriadicFrameworks ecosystem.

🧩 Relationship to TFT_3Pack v1.3#

These workflows complement the tools found in:

/docs/TFT_3Pack_v1.3/scripts/
/docs/TFT_3Pack_v1.3/tft/
/docs/TFT_3Pack_v1.3/examples/

Where TFT_3Pack provides formats, examples, and shell tools, the /workflows/ folder provides programmable engines for:

• Batch processing
• Scroll remixing
• Pipeline execution
• Cross‑language integration (Python ↔ JS)

Together, they form the execution backbone of RTT‑Inside.

🧭 When to Use These Workflows#

Use this folder when you need:

• To run multiple scrolls in sequence
• To generate remix lineages
• To embed scroll execution into a Python or JS project
• To validate .fff files programmatically
• To build new tools on top of RTT‑Inside primitives

🗺️ Future Extensions#

Planned additions include:

• Regime‑aware pipeline overlays
• Scroll‑to‑TFT converters
• AI‑drift‑resilient execution wrappers
• Dimensional‑core validators
• Cross‑ontology translators

These will follow the same principles: minimal, portable, remix‑friendly.