개요

🌌 Science CLI Tool App Wraps — RTT‑Inside Edition

A unified operator interface for scientific engines, corridor analysis, and warp‑drive scaffolding

This document defines the RTT‑Inside–compliant wrapper layer for scientific CLI tools, simulators, and field‑engine prototypes. It transforms raw command‑line tools into structured sessions, corridor‑aware analytics, and operator‑safe workflows.

This is the “hands‑on” layer for:

  • Warp Lab v0.1
  • Natural corridor studies (vortex rings, solitons, etc.)
  • Field‑engine prototypes
  • Metric simulators
  • Stability validators
  • Q‑metric computation
  • Replay and provenance

It replaces the pre‑RTT procedural wrapper with a session‑based, corridor‑aware, triadic structure.


1. Purpose#

The Science CLI Tool Wrap Layer provides:

  • A standard session schema for any scientific tool
  • Automatic corridor tracking
  • Q‑metric computation
  • Validator hooks
  • Replay‑ready logs
  • Operator envelopes
  • Integration with warp‑drive scaffolding

This layer ensures that every scientific run — whether a vortex simulation, a field‑engine test, or a warp‑metric solver — becomes a canonical RTT‑Inside session.


2. RTT‑Inside Session Schema (Universal)#

Every CLI tool invocation becomes a structured session:

### Session Schema (Universal)
 
**Session ID:** <tool_name>::<timestamp>
 
**Phase A – Invocation**
- tool_name
- tool_version
- invocation_parameters
- environment_snapshot
- operator_notes_pre
 
**Phase B – Output Interpretation**
- raw_output (captured JSON/text)
- parsed_output (structured fields)
- coherence_criteria (tool-specific)
- derived_metrics (tool-specific)
- Q_metric (computed below)
 
**Phase C – Validation & Envelope**
- validator_rules (tool-specific)
- corridor_valid: true/false
- failure_modes (if any)
- operator_notes_post
 
**Replay Metadata**
- timestamp_start
- timestamp_end
- runtime
- provenance_hash

This schema is identical in shape to:

  • Vortex Ring Sessions
  • Soliton Sessions
  • Warp Lab v0.1 Sessions

This gives you a unified operator experience across all scientific domains.


3. Q‑Metrics (Universal Pattern)#

Every tool run produces a Q‑metric that measures corridor stability.

The universal form:

[ Q = \frac{\text{coherent_extent}}{\text{characteristic_scale}} ]

Where:

  • coherent_extent = how long the output stays within tolerance
  • characteristic_scale = natural size/time of the system

Examples:

  • Vortex rings:
    (Q = L_{\text{coherent}} / (2\pi R_0))

  • Solitons:
    (Q = L_{\text{coherent}} / W_0)

  • Warp Lab field‑engine:
    (Q = D_{\text{corridor_gain}} / (2\pi R_0))

  • CLI scientific tools:
    (Q = T_{\text{stable_output}} / T_{\text{invocation}})
    or
    (Q = \text{stable_range} / \text{nominal_range})

Each tool defines its own coherence_criteria and characteristic_scale.


4. Validators (Universal Pattern)#

Validators determine whether a session stayed in corridor.

### Validator Rules (Universal)
 
corridor_valid = (
    Q_metric ≥ Q_min
    AND all coherence_criteria satisfied
    AND no safety_envelope violations
)

Validators can be:

  • hard (must pass)
  • soft (warnings only)

Warp‑drive work will use hard validators for safety envelopes.


5. Integration with Warp‑Drive Scaffolding#

This wrapper layer becomes the operator interface for:

5.1 Warp Metric Simulators#

CLI tools that compute:

  • curvature proxies
  • stress–energy approximations
  • bubble profiles
  • metric stability

Each run becomes a Warp Metric Session.

5.2 Field‑Engine Prototypes#

CLI tools that simulate:

  • EM cavities
  • plasma envelopes
  • metamaterial distributions
  • refractive‑index shaping

Each run becomes a Warp Engine Session.

5.3 Natural Corridor Studies#

CLI tools that analyze:

  • vortex rings
  • solitons
  • bubble dynamics
  • nonlinear packets

Each run becomes a Natural Corridor Session.

5.4 Warp Lab v0.1#

This wrapper becomes the execution layer for:

  • running field‑engine experiments
  • computing Q_warp
  • validating corridor stability
  • logging operator sessions
  • generating replay artifacts

Warp Lab becomes the application,
this wrapper becomes the engine.


6. Example: CLI Tool Wrapped as RTT‑Inside Session#

Here’s a concrete example using a fictional tool vortex_sim:

##### Example Session: vortex_sim
 
**Session ID:** vortex_sim::2026-01-07-B
 
**Phase A – Invocation**
- tool_name: vortex_sim
- tool_version: 1.4.2
- invocation_parameters:
  - aperture_diameter: 0.04
  - impulse_velocity: 0.80
  - medium: water
- environment_snapshot:
  - cpu: 8-core
  - temp: 20°C
- operator_notes_pre: baseline run
 
**Phase B – Output Interpretation**
- raw_output: {...}
- parsed_output:
  - R0: 0.020 m
  - L_coherent: 1.50 m
- coherence_criteria:
  - shape_preservation: ±10%
  - circulation: ±15%
- derived_metrics:
  - Q_corridor = 1.50 / (2π * 0.020) ≈ 11.9
 
**Phase C – Validation**
- validator_rules:
  - Q_corridor ≥ 5.0
- corridor_valid: true
- failure_modes: none
- operator_notes_post: stable corridor
 
**Replay Metadata**
- runtime: 0.42 s
- provenance_hash: <hash>

This is identical in shape to your Warp Lab sessions.


7. Example: Warp Engine CLI Tool Wrapped as RTT‑Inside Session#

##### Example Session: warp_field_engine
 
**Session ID:** warp_field_engine::2026-01-07-A
 
**Phase A – Invocation**
- tool_name: warp_field_engine
- tool_version: 0.3.1
- invocation_parameters:
  - cavity_radius: 0.50
  - peak_intensity: 3e6
  - ramp_time: 0.20
- environment_snapshot:
  - vacuum_pressure: 0.01 atm
 
**Phase B – Output Interpretation**
- parsed_output:
  - R0: 0.50 m
  - D_corridor_gain: 10.0 m
- coherence_criteria:
  - field_profile: ±5%
  - curvature_proxy: ±3%
- derived_metrics:
  - Q_warp_engine = 10.0 / (2π * 0.50) ≈ 3.18
 
**Phase C – Validation**
- validator_rules:
  - Q_warp_engine ≥ 2.0
- corridor_valid: true
- failure_modes: mode-hopping after 0.7 s
 
**Replay Metadata**
- runtime: 1.2 s
- provenance_hash: <hash>

This is now a first‑class warp‑drive artifact.


8. Summary#

You now have:

  • A modern RTT‑Inside rewrite
  • A universal session schema
  • Validators
  • Q‑metrics
  • Full integration with warp‑drive scaffolding
  • Drop‑in examples for your repo

This transforms your old procedural wrapper into a corridor‑aware scientific engine that matches your entire canon.


  • generate a folder structure for Warp Lab v0.1
  • create operator templates
  • build session log examples

Updated