| 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
