scbe-9d-state-engine
Construct and evolve the 9-dimensional state vector xi = [c(t), tau(t), eta(t), q(t)] that drives SCBE-AETHERMOORE governance decisions. Use when building context vectors, evolving time/entropy/quantum dimensions, or preparing state for the governance gate.
Best use case
scbe-9d-state-engine is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Construct and evolve the 9-dimensional state vector xi = [c(t), tau(t), eta(t), q(t)] that drives SCBE-AETHERMOORE governance decisions. Use when building context vectors, evolving time/entropy/quantum dimensions, or preparing state for the governance gate.
Teams using scbe-9d-state-engine should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/scbe-9d-state-engine/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How scbe-9d-state-engine Compares
| Feature / Agent | scbe-9d-state-engine | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Construct and evolve the 9-dimensional state vector xi = [c(t), tau(t), eta(t), q(t)] that drives SCBE-AETHERMOORE governance decisions. Use when building context vectors, evolving time/entropy/quantum dimensions, or preparing state for the governance gate.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# SCBE 9D State Engine
Use this skill to assemble the full 9D state vector that feeds the Grand Unified Governance function.
## State Vector Layout
```
xi[0..5] = c(t) — 6D Context Vector
xi[6] = τ(t) — Time dimension
xi[7] = η(t) — Entropy dimension
xi[8] = q(t) — Quantum state (complex)
```
## 6D Context Vector c(t)
| Index | Name | Type | Description |
|-------|--------------------|---------|--------------------------------------|
| v1 | Identity | float | `sin(t)` — identity oscillation |
| v2 | Intent Phase | complex | `e^(i·2π·0.75)` — intent as phase |
| v3 | Trajectory Score | float | EWMA score (e.g. 0.95) |
| v4 | Linear Time | float | Raw timestamp `t` |
| v5 | Commitment Hash | float | SHA-256 of `commit_{t}` normalized |
| v6 | Signature Validity | float | Validity score ∈ [0, 1] |
## Dynamics Equations
### Time Flow (7th Dimension)
```
τ̇(t) = 1.0 + DELTA_DRIFT_MAX · sin(OMEGA_TIME · t)
```
- DELTA_DRIFT_MAX = 0.5, OMEGA_TIME = 2π/60
- Normal flow = 1.0; causality requires τ̇ > 0
### Entropy Flow (8th Dimension)
```
η̇ = BETA · (ETA_TARGET - η) + 0.1 · sin(t)
```
- BETA = 0.1, ETA_TARGET = 4.0
- Ornstein-Uhlenbeck drift with periodic perturbation
### Quantum Evolution (9th Dimension)
```
q(t) = q₀ · e^(-iHt)
```
- Unitary evolution under Hamiltonian H
- q₀ typically initialized to 1+0j
### Shannon Entropy Computation
- Flatten context vector (complex → magnitude, reals → float)
- Histogram with 16 bins, density-normalized
- `η = -Σ p·log₂(p + 1e-9)` over non-zero bins
## Workflow
1. Generate 6D context vector from current time `t`.
2. Compute Shannon entropy of context vector.
3. Evolve quantum state from initial condition.
4. Pack into 9-element numpy array (mixed dtype via `object`).
5. Pass to governance gate for evaluation.
## Constants
| Name | Value | Purpose |
|--------------|-------------|--------------------------|
| PHI | (1+√5)/2 | Golden Ratio |
| R | PHI | Harmonic Base |
| TAU_COH | 0.9 | Coherence Threshold |
| ETA_TARGET | 4.0 | Target Entropy |
| BETA | 0.1 | Entropy Decay Rate |
| ETA_MIN | 2.0 | Min Entropy |
| ETA_MAX | 6.0 | Max Entropy |
## Guardrails
1. The context vector uses `dtype=object` to hold mixed float/complex types.
2. Entropy computation must handle complex values by taking magnitudes.
3. Quantum state must remain normalized (unitary evolution preserves this).
4. Time value must be real and monotonically increasing in production.Related Skills
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