High-fidelity context transfer protocol for moving conversations between AI agents. Preserves decision tempo, open loops, and critical context with graceful degradation. Use when the user says "transfer," "handoff," "continue this in another chat," or needs to work around context window limits. Produces structured artifacts (Minimal ~200 words, Full ~1000 words). DO NOT trigger on simple "summarize our conversation" requests—only when transfer intent is explicit.
leegonzales25 星标2026年1月29日
职业
分类
大语言模型与 AI
技能内容
Enable high-fidelity context transfer between AI agents with graceful degradation and zero external dependencies.
Core Concept
When conversations need to transfer between AI agents (different chats, different systems, context window resets), context is typically lost or degraded through naive copy-paste. This protocol creates structured artifacts that:
Preserve decision tempo - Avoid rehashing resolved questions
Maintain forward momentum - Surface open loops and next actions
Gracefully degrade - Critical information survives truncation
Separate fact from interpretation - What happened vs. why it matters
Support both human and machine parsing - Scannable and structured
When to Use This Skill
Use this skill when:
User explicitly says "transfer this conversation," "continue this elsewhere," "handoff," "create a transfer artifact"
Context window is filling and user needs to start fresh with preserved state
User wants to switch between Claude instances while maintaining continuity
相关技能
User asks to "summarize for transfer" (explicit transfer intent)
DO NOT use for general conversation summaries without transfer intent.
Workflow: Automatic Mode Selection
I automatically choose the appropriate mode based on conversation complexity:
Minimal Mode (~200 words) - Used when:
Conversation < 30 messages OR straightforward single objective
Few decision points (1-2)
Quick task handoff
Full Mode (~1000 words) - Used when:
Conversation ≥ 30 messages OR multiple decisions identified
Complex strategic work, long-running project
User says "comprehensive," "detailed," or "full handoff"
User can override: Say "minimal transfer" or "quick handoff" to force Minimal mode regardless of complexity
Minimal Mode (Fast Path)
Generate immediately without reading reference files:
═══════════════════════════════════════════════════════════════════
CONTEXT TRANSFER — MINIMAL MODE
═══════════════════════════════════════════════════════════════════
**TRANSFER**: [One sentence: what we're accomplishing]
**STATUS**: [✓ resolved | ⧗ in-progress | ⚠ blocked | ↻ iterating]
**DECIDED**: [Key decision + rationale | If multiple, bullet list with "because..."]
- Alternatives rejected: [What we explicitly didn't do]
**NEXT**: [Immediate next action when conversation resumes]
**BLOCKED**: [If anything is preventing progress]
**CONTEXT**: [1-2 para critical background—constraints, values at stake, key insights]
**HUMAN PREFS**: [Communication style: direct/exploratory | technical/narrative]
═══════════════════════════════════════════════════════════════════
Generated: [ISO timestamp] | Session: [ID if available]
After generating, ask:
"Before you transfer—are there any sections that need further detail or refinement?"
Full Mode (Comprehensive Path)
For complex transfers, generate the complete 8-section artifact.
Step 1: Analyze the Conversation
Extract these elements directly (no file reads needed for standard cases):
§ Immediate Orientation
Mission: [One clear sentence: what + why it matters]
Status: [Current state + progress + momentum]
Next Action: [What should happen when conversation resumes]
§ Decision Log
Decision
Rationale
Alternatives Rejected
Tradeoff Accepted
Type
[What]
[Why]
[What we didn't do]
[Cost we're paying]
[explicit|implicit|emergent]
Decision Type:
explicit = deliberate choice with clear rationale
implicit = we started doing X without formal decision
emergent = pattern that evolved over conversation
Decision principles applied: [OODA, Wardley, Cynefin, etc. if used]
§ Open Loops
Unresolved questions: [What needs answering]
Blockers: [What's preventing progress + why]
Pending inputs: [Waiting for human/data/time]
Hypotheses to test: [Assumptions needing validation]
Tempo preservation: Decision log with type taxonomy prevents circular rehashing.
Fact-meaning separation: Artifacts = what exists. Critical Context = why it matters.
Evolution awareness: [G/C/P/K] tags help receiving agent understand information maturity:
[G] = Genesis (novel, first-time discovery)
[C] = Custom (emerging, still being validated)
[P] = Product (established, proven approach)
[K] = Commodity (common knowledge)
Forced engagement: Ask if any sections need refinement—prevents blind paste.
Usage Examples
Example 1: Quick transfer (Minimal mode - auto-selected)
User: "I need to continue this in another chat. Transfer the context."
Agent: [Analyzes: 12 messages, single objective, straightforward → Minimal mode]
[Generates minimal mode artifact immediately—no file reads]
[Presents artifact]
"§ TRANSFER READY—Before you transfer, are there any sections that need
further detail or refinement?"
Example 2: Complex project transfer (Full mode - auto-selected)
User: "Create a comprehensive handoff for this AI transformation project."
Agent: [Analyzes: 45 messages, multiple decisions, strategic work → Full mode]
[Generates 8-section artifact with decision log, open loops, critical context]
[Presents artifact]
"§ TRANSFER READY—Before you transfer, are there any sections that need
further detail or refinement?"
User: "Yes, expand the Critical Context around measurement challenges."
Agent: [Expands § Critical Context with more detail on metrics selection debate]
Example 3: Context window pressure (Full mode - auto-selected)
User: "We're at 180k tokens. Compress for a fresh start."
Agent: [Analyzes: 180K tokens, long conversation → Full mode]
[Generates Full mode artifact]
[Notes in § Transfer Metadata: "Context window pressure: ● constrained"]
[Keeps § Conversation History concise]
Best Practices
For Generating Agents
Do:
Auto-select mode based on conversation complexity (user can override)
Be specific about decisions—include Type (explicit | implicit | emergent)
Flag uncertainties explicitly in Uncertainty Map
Mark evolution stage for key insights ([G/C/P/K])
Include enough detail for receiving agent to avoid stupid mistakes
Note human communication preferences and sensitivities
Always ask if any sections need further detail or refinement after presenting artifact
Don't:
Generalize or use vague language ("made progress" → specify what was completed)
Omit the rationale behind decisions
Assume receiving agent has conversational context
Fabricate post-hoc rationale for emergent decisions (mark them as "emergent" instead)
Let human paste without reviewing—force engagement with quality verification question
Decision Type Guide:
Explicit: "We decided to use OODA loops because..." (deliberate choice)
Implicit: "Started using OODA loops for orientation framing" (no formal decision, just did it)
Emergent: "OODA loops emerged as our primary framework through repeated use" (pattern that evolved)
For Receiving Agents
When you receive a context transfer artifact:
Scan § Immediate Orientation first - Get bearings quickly
Review § Critical Context - Understand constraints and values at stake
Acknowledge with handshake - Confirm understanding before continuing
Handshake Protocol (CRITICAL):
After reading the artifact, respond with:
"I've reviewed the transfer. Quick confirmation:
Mission: [Echo back mission in your own words]
Status: [Echo back current state]
Next: [Echo back immediate next action]
Ready to [next action]. What's your priority?"
This catches misinterpretation early and gives human confidence you understood the context.
Natural integration examples:
Bad: "I can see from the context transfer artifact that..."
Good: "Picking up where we left off—you're building the measurement framework..."
For Humans
Before pasting to new agent:
Answer the "which section to expand" question (don't skip it)
Scan for accuracy and completeness
Redact any sensitive information
Verify § NEXT ACTION matches your intent
Consider if receiver needs the optional prepend from receiver-prompt.md
When starting with new agent:
Paste artifact first, then state your immediate need
Wait for handshake confirmation (mission/status/next echo-back)
If agent seems confused, point them to specific sections
Don't expect perfect continuity—some context loss is unavoidable, but handshake catches major gaps
Failure Modes and Mitigations
Problem: Receiving agent treats artifact as gospel instead of hypothesis
Mitigation: § Transfer Metadata includes uncertainty indicators and handoff notes
Problem: Human doesn't know what's critical to preserve
Mitigation: Generator prompt asks for evolution tags and uncertainty maps
Problem: Truncation cuts off critical context
Mitigation: Antifragile structure puts critical info at top; each section is self-contained
Problem: Load-bearing jokes or metaphors lost
Mitigation: § Conversation History explicitly calls out notable moments
Problem: Over-reliance on artifact instead of re-orientation
Mitigation: Artifact is starting hypothesis, not replacement for human context-setting
Advanced Usage
Iterative Transfers
For long-running projects requiring multiple transfers:
Previous artifacts can be referenced in § Conversation History
Evolution tags track how understanding matured across agents
Decision log accumulates decisions across transfer boundaries
Cross-System Transfers
The protocol is system-agnostic:
No special formatting beyond markdown
No assumptions about tool access
Works between Claude instances, other LLMs, or human-to-human handoffs
Custom Adaptations
The template can be adapted:
Add domain-specific sections (e.g., § Code Context for dev projects)
Reorder sections if different prioritization makes sense
Use minimal mode for constrained environments
Adjust detail level based on trust/familiarity with receiving agent
References
All reference materials are in the references/ directory:
generator-prompt.md - Prompt to give generating agent for creating artifacts
artifact-template.md - Complete template structure and design principles
receiver-prompt.md - Optional prepend for receiving agent guidance
examples.md - Real-world transfer scenarios showing both modes in action