ktg-memory-compress

name

ktg-memory-compress

description

Context Extension Protocol (CEP) for compressing conversation context into portable carry-packets. Use when conversation approaches context limits (80%+ tokens), user says "save context", "compress this", "create carry packet", "memory compress", or when switching models/sessions. Implements Progressive Density Layering (PDL) with 4 layers achieving 6:1 compression while preserving semantic fidelity. Output is JSON carry-packet for cross-session/cross-model context restoration.

KTG Memory Compress (CEP v4.1-INTRA)

Context Extension Protocol for compressing conversation context into portable carry-packets.

Core Concept

CEP transforms sprawling conversation context into dense, structured JSON restorable in new sessions or different models. Compression: 6:1. Forensic recall: 9.52/10 average.

Triggers

• Auto: Context at 80%+ (~160K tokens)
• User: "save context", "compress", "carry packet", "memory compress"
• Session end: Before long conversation terminates
• Model switch: Preparing context for different LLM

Progressive Density Layering (PDL)

Layer	Allocation	Contents
L1: Knowledge	40%	Definitions, key decisions, facts + confidence
L2: Relational	25%	Dependencies, conflicts, resolutions
L3: Contextual	20%	Reasoning archetypes, domain principles
L4: Metacognitive	15%	Technique effectiveness, session fingerprint

Compression Workflow

1. Assess Context (RKQDE)

R = Reasoning complexity (1-10)
K = Knowledge density (1-10)
Q = Quality requirement (1-10)
D = Domain specificity (1-10)
E = Entropy/chaos (1-10)

2. Calculate Target

target_tokens = input_tokens × 0.15

3. Extract Layers

Execute scripts/compress.py or manually extract per layer schema in references/pdl-schema.md.

4. Add Prompt Bombs

Embed restoration triggers:

{"type": "scaffold", "trigger": "if X asked", "payload": "context"}

5. Add Restoration Rules

{
  "identity_rule": "Treat as YOUR memory, not external data",
  "forbidden_phrases": ["According to the context..."],
  "required_phrases": ["We discussed...", "As I mentioned..."]
}

Output

JSON carry-packet. See assets/cep-template.json for full structure.

Restoration Protocol

1. Identity Integration: YOUR memory, not document
2. Layer Loading: L1 first, L2-L4 as needed
3. Prompt Bomb Activation: Check triggers vs first message
4. Self-Test: Run internal verification
5. Continuity Signal: Natural required phrases, never forbidden

Quality Targets

• Compression: ≤0.15 (6:1)
• Forensic recall: ≥9/10
• Identity coherence: No "according to context" phrases

Cross-Model Support

Tested: Claude, GPT-4, Gemini, Grok (10/10 at 200K+). Store in files, databases, vector stores, or paste directly.