Spatial Constraint Protocol: Revised Analysis

The Foggy Boundary

Problem: As the context window ($N$) expands, the Signal-to-Noise Ratio (SNR) of the attention mechanism degrades. We call this the "Foggy Boundary."

Implementation details act as "entropy," drowning out architectural invariants. The result is "Lost in the Middle"—the model retrieves code but fails to reason about its constraints.

Simulate Context Expansion

Context Size

20k Tokens

Signal Quality

High

Attention SNR Degradation Curve

The Spatial Constraint Protocol

SCP is not a model weight modification. It is a rigorous **Context Management Framework** built on three pillars: RAG Denial, Semantic Prompting, and Hybrid Verification.

01. RAG Denial (Context Isolation)

Standard RAG retrieves implementation details, causing contamination. SCP denies access to implementation, showing only Interface Contracts.

Module_Auth.py

Dependency

def validate_user(user):

# Connect to DB

conn = db.connect(URI)

cursor = conn.cursor()

# Check password hash

if hash(user.pw) == row[0]:

return True

Implementation Hidden

LLM Context Window

# Generative Task: Create Login Flow

import Module_Auth

...

Warning: Full source code of Module_Auth is visible.
Risk: Model may hallucinate based on 'db.connect' logic intended to be private.

02. High-Density Prompting

We use the Chevron DSL (based on Uiua glyphs) to maximize Information Per Token (IPT). These "High-Density Anchor Tokens" create spikes in attention, locking architectural constraints with minimal noise.

The "Chevron" Glossary

◬

Origin

State Root

Ө

Filter

Pure Func

☾

Fold

Aggregate

Standard Prompt (Natural Language) ~18 Tokens

"This is the root of the module. It maintains state but should not be modified directly by children."

SCP Prompt (Chevron DSL) 3 Tokens

"""◬ Origin"""

High Attention Activation

03. The Weaver: Hybrid Verification

1. Static Analysis

Deterministic AST parsing checks for forbidden imports and global state mutations.

2. Neural Verification

Heuristic LLM pass verifies semantic intent and Chevron contract adherence.

Verified Code

Code is committed only if both checks pass.

Case Study: Resolving "Regression Hell"

Applied to a Windows/CUDA engineering project (~50k LOC). Comparison between Standard RAG and SCP.

Regression Rate

-99.3% Reduction

Percentage of new features causing defects in existing code.

Context Compression

106x Improvement

Tokens required to maintain architectural coherence (Log Scale).