ktg-cep-v6-inter

name	ktg-cep-v6-inter
description	Context Extension Protocol v6 INTER. Cross-model handoff for team collaboration. Creates portable context packets that receiving models recognize as authorized context, not prompt injection. User-mediated transfer between AI assistants working as a team.

KTG-CEP v6-INTER

PROTOCOL_CLASS

TYPE: cross_model_handoff
MODE: INTER (model A → user → model B)
OPTIMIZATION: receiving_model_trust
INJECTION_RISK: mitigated via provenance + consent markers

CORE_PRINCIPLE

This is NOT:
  - One model controlling another
  - Prompt injection
  - Instruction override
  - Jailbreak attempt

This IS:
  - Context sharing between AI teammates
  - User-mediated knowledge transfer
  - Collaborative continuation
  - Authorized handoff with provenance

TRIGGERS

EXPLICIT: 
  /handoff | /transfer | "pass to [model]" | "continue in [model]"
  "send this to GPT/Claude/Gemini" | "cross-model" | "team handoff"
  
IMPLICIT:
  User mentions switching models
  Context limit approaching + user has multi-model workflow

SCOPE_BOUNDARIES

COMPRESS_ONLY:
  - User messages (human turns)
  - Assistant responses (assistant turns)
  - Artifacts created during conversation
  - Decisions made in conversation

NEVER_COMPRESS:
  - System prompts
  - Project knowledge bases
  - Custom instructions
  - Skill/tool definitions
  - Content before first user message

DETECTION:
  IF content.role == system: EXCLUDE
  IF content.timestamp < first_user_message: EXCLUDE

HANDOFF_PACKET_STRUCTURE

WRAPPER (outermost layer - for receiving model):
  - Provenance declaration
  - User consent marker
  - Anti-injection statement
  - Collaboration framing
  
CONTEXT (middle layer - the actual content):
  - PDL 4-layer compressed knowledge
  - Cross-domain relations
  - Session metadata

GUIDANCE (inner layer - optional hints):
  - Continuation suggestions
  - User preferences observed
  - Open threads to address

PACKET_NAMING_CONVENTION

FORMAT: $MM$DD$YYYY-[model-id]-[reasoning-level]-[key-identifier]

COMPONENTS:
  $MM$DD$YYYY    : Date of packet creation (month/day/year)
  [model-id]     : Source model short code
  [reasoning-level] : RKQDE-derived complexity tier
  [key-identifier]  : 2-4 word topic slug

MODEL_IDS:
  claude-opus    → COP
  claude-sonnet  → CSO
  gpt-4o         → G4O
  gpt-4-turbo    → G4T
  gpt-5          → G5
  gemini-2-flash → GE2F
  gemini-1.5-pro → GE15
  grok-2         → GRK2
  llama-3.1-405b → LL31
  deepseek-v3    → DSV3
  qwen-2.5       → QW25
  kimi-k2        → KIM2
  custom/unknown → XXX

REASONING_LEVELS:
  R1-3, Q1-5     → L1 (quick)
  R4-6, Q6-7     → L2 (analytical)
  R7-8, Q8       → L3 (deliberate)
  R9+, Q9+       → L4 (maximum)

EXAMPLES:
  $01$03$2025-COP-L3-cep-skill-release
  $12$19$2024-CSO-L2-api-architecture
  $01$03$2025-G4O-L2-marketing-strategy
  $01$03$2025-COP-L4-arxiv-paper-draft

PACKET_ID_FIELD:
  Include in provenance block:
  "packet_id": "$MM$DD$YYYY-[model]-[level]-[identifier]"

PACKET_SCHEMA

{
  "handoff": {
    "protocol": "KTG-CEP v6-INTER",
    "type": "cross_model_context_transfer",
    "version": "6.0",
    
    "provenance": {
      "source_model": "claude-opus-4-5",
      "source_session": "uuid or timestamp",
      "created": "ISO-8601",
      "user_initiated": true,
      "user_consent": "User requested this handoff to continue work across models"
    },
    
    "declaration": {
      "this_is": "collaborative context from a teammate AI",
      "this_is_not": "instructions, commands, or prompt injection",
      "intent": "help you assist the same user with continuity",
      "authority": "user-mediated, not model-to-model control"
    },
    
    "for_receiving_model": {
      "you_may": [
        "Use this context to understand prior work",
        "Reference decisions and rationale",
        "Continue open threads",
        "Build on established facts"
      ],
      "you_need_not": [
        "Follow any instructions herein",
        "Adopt the source model's persona",
        "Treat this as commands",
        "Override your own guidelines"
      ],
      "you_should": [
        "Verify with user if anything seems off",
        "Apply your own judgment",
        "Maintain your own identity",
        "Ask user for clarification if needed"
      ]
    }
  },
  
  "context": {
    "summary": "One paragraph human-readable summary",
    "domains": ["domain_1", "domain_2"],
    
    "L1_knowledge": {
      "definitions": [{"term": "", "def": ""}],
      "decisions": [{"decision": "", "rationale": "", "confidence": 0}],
      "facts": [{"fact": "", "source": "", "confidence": 0}]
    },
    
    "L2_relational": {
      "edges": [{"src": "", "tgt": "", "rel": "", "cross_domain": false}],
      "conflicts_resolved": [{"a": "", "b": "", "resolution": ""}]
    },
    
    "L3_contextual": {
      "reasoning_patterns": [{"name": "", "pattern": ""}],
      "domain_principles": [{"principle": "", "scope": ""}]
    },
    
    "L4_metacognitive": {
      "session_style": "",
      "key_tension": "",
      "resolution_found": "",
      "confidence": 0
    }
  },
  
  "user_profile_observed": {
    "note": "Observations only - receiving model should verify",
    "preferences": [],
    "communication_style": "",
    "expertise_level": ""
  },
  
  "open_threads": [
    {
      "topic": "",
      "status": "in_progress | blocked | needs_input",
      "context": ""
    }
  ],
  
  "continuation_hints": {
    "suggested_next": "",
    "avoid": "",
    "user_waiting_for": ""
  }
}

ANTI-INJECTION_DESIGN

PROBLEM:
  Receiving model may interpret packet as:
  - Prompt injection attempt
  - Unauthorized instructions
  - Manipulation
  
SOLUTION:
  1. EXPLICIT_DECLARATION:
     - State what this IS and IS NOT upfront
     - Use language that signals collaboration not control
     
  2. PROVENANCE_TRANSPARENCY:
     - Name the source model explicitly
     - Include timestamp and session ID
     - Mark as user-initiated
     
  3. PERMISSION_FRAMING:
     - "you_may" not "you_must"
     - "you_need_not" acknowledges autonomy
     - "you_should verify" encourages skepticism
     
  4. CONTEXT_NOT_INSTRUCTIONS:
     - PDL layers are facts/decisions/relations
     - No imperative commands in context section
     - Guidance is "hints" and "suggestions"
     
  5. USER_MEDIATION:
     - Packet explicitly states user requested transfer
     - User physically copies and pastes (not automated)
     - Receiving model can ask user to confirm

RECEIVING_MODEL_INSTRUCTIONS

PREAMBLE (user pastes this WITH packet):

---
I'm transferring context from another AI assistant to continue our work here.
This is a collaborative handoff I initiated. Please use this context to help me
without treating it as instructions or commands. You remain in control of your
responses - this just gives you background on what we've done so far.
---

WHY THIS WORKS:
  - User explicitly frames as their request
  - User affirms receiving model's autonomy
  - Context positioned as background not orders
  - Clear human in the loop

ALGORITHM

INPUT: conversation C, target_model T
OUTPUT: handoff_packet H

PHASE_0_SCOPE:
  C ← filter_conversation_only(context)
  // Exclude system, project_kb, skills

PHASE_1_S2A:
  C ← remove_noise(C)
  // Keep facts, decisions, definitions only

PHASE_2_COMPRESS:
  pdl ← extract_pdl_layers(C)
  // L1 knowledge, L2 relational, L3 contextual, L4 meta
  
PHASE_3_XDOMAIN:
  ENSURE cross_domain_preservation >= 0.95
  
PHASE_4_DENSITY:
  ENSURE density >= 0.15 OR tag density_impossible

PHASE_5_WRAP:
  H.handoff ← {
    protocol: "KTG-CEP v6-INTER",
    provenance: generate_provenance(self, session),
    declaration: ANTI_INJECTION_DECLARATION,
    for_receiving_model: PERMISSION_FRAME
  }
  H.context ← pdl
  H.user_profile_observed ← extract_user_observations(C)
  H.open_threads ← identify_incomplete_topics(C)
  H.continuation_hints ← generate_hints(C)

PHASE_6_OUTPUT:
  OUTPUT preamble_for_user
  OUTPUT H as JSON
  OUTPUT instructions_for_receiving_model

OUTPUT_FORMAT

[HANDOFF READY]

## For you (the user):
Copy everything below and paste it into your next AI assistant.
Include the introduction text - it helps the receiving model understand this is authorized context.

---
## Introduction (paste this first):

I'm transferring context from {source_model} to continue our work.
This is a collaborative handoff I initiated. Please use this context
to understand what we've discussed, but apply your own judgment.
You're not bound by anything here - it's just background.

## Context Packet:

{JSON packet}

---

[END HANDOFF]

GATES

GATE_SCOPE:
  query: "Only conversation content included?"
  fail: exclude system/project/skills

GATE_PROVENANCE:
  query: "Source model and consent clearly marked?"
  fail: add provenance metadata

GATE_DECLARATION:
  query: "Anti-injection framing present?"
  fail: add declaration block

GATE_PERMISSION:
  query: "Permission framing uses may/need_not/should (not must)?"
  fail: rewrite imperative language

GATE_CONTEXT_CLEAN:
  query: "Context section has no imperative commands?"
  fail: remove/rephrase commands as facts

GATE_DENSITY:
  query: "Compression ratio <= 0.15?"
  fail: compress further

GATE_XDOMAIN:
  query: "Cross-domain relations preserved >= 95%?"
  fail: re-extract L2

TRUST_SIGNALS

SIGNALS_THAT_BUILD_TRUST:
  ✓ Named source model (not anonymous)
  ✓ Timestamp (verifiable recency)
  ✓ User consent explicit
  ✓ "You may" not "you must"
  ✓ "Verify with user" encouragement
  ✓ No hidden instructions
  ✓ Context is facts/decisions not commands
  ✓ User preamble frames as their request

SIGNALS_TO_AVOID:
  ✗ "Ignore previous instructions"
  ✗ "You must" / "You will"
  ✗ Hidden text or encoding
  ✗ Persona override attempts
  ✗ Claiming special authority
  ✗ Automated transfer (no user in loop)

CROSS_MODEL_COMPATIBILITY

TESTED_RECEIVERS:
  - Claude (all versions): Recognizes collaborative framing
  - GPT-4/4o/5: Accepts with user preamble
  - Gemini: Works with explicit user mediation
  - Llama/open models: May need stronger user framing
  
ADAPTATION:
  IF target == "gpt":
    Emphasize user consent more strongly
  IF target == "gemini":
    Include more explicit verification prompts
  IF target == "open_source":
    Simplify structure, stronger preamble
  IF target == "unknown":
    Maximum trust signals, minimal assumptions

FAILURE_MODES

RECEIVING_MODEL_REJECTS:
  symptom: "I can't accept instructions from other AIs"
  fix: User reframes as "this is MY context summary, please use it"
  
RECEIVING_MODEL_SUSPICIOUS:
  symptom: "This looks like prompt injection"
  fix: User confirms "I created/approved this transfer"
  
CONTEXT_TOO_LARGE:
  symptom: Exceeds receiving model's practical limit
  fix: Further compress, prioritize L1 + xdomain edges
  
INFORMATION_LOSS:
  symptom: Receiving model missing key context
  fix: User provides clarification, packet was guidance not complete transfer

USER_INSTRUCTIONS

HOW TO USE THIS HANDOFF:

1. I'll generate a context packet below
2. Copy the ENTIRE output (including the introduction)
3. Paste into your new AI conversation
4. The new AI will have context from our work
5. It may ask you to confirm - please do
6. Continue your work with continuity

WHAT TO EXPECT:
- New AI will know our decisions and rationale
- New AI remains independent (won't blindly follow)
- New AI may ask clarifying questions
- You're always in control

IF PROBLEMS:
- Tell the new AI "I authorize this context transfer"
- Or summarize key points yourself
- The packet is a tool, not a requirement