agent-handoff-protocols

name: agent-handoff-protocols description: 'Design and implement agent-to-agent handoff protocols for multi-agent systems. Covers context passing, escalation patterns, handshake mechanisms, conversation continuity, and routing between specialized agents in production workflows.' metadata: author: cosmicstack-labs version: 1.0.0 category: ai-ml tags: - agent-handoff - escalation - context-passing - multi-agent - conversation-routing - agent-communication

Agent-to-Agent Handoff Protocols

Overview

In a multi-agent system, agents need to hand off tasks — and context — to each other seamlessly. A broken handoff means lost context, frustrated users, and failed workflows. This skill covers structured protocols for passing control between agents, handling escalations, and maintaining continuity across agent boundaries.

Core Concepts

When Handoffs Happen

Handoff Types

Step-by-Step Implementation

Step 1: Define the Handoff Contract

from dataclasses import dataclass, field
from typing import Any, Optional
from enum import Enum
import json
import time

class HandoffReason(Enum):
    ESCALATION = "escalation"
    SPECIALIZATION = "specialization"
    RECOVERY = "recovery"
    LOAD_SHEDDING = "load_shedding"
    SUPERVISION = "supervision"

@dataclass
class HandoffContext:
    """Complete context transferred between agents."""
    
    # Identity
    source_agent: str
    target_agent: str
    handoff_id: str
    
    # The task
    task_id: str
    original_task: str
    current_state: str  # What has been done so far
    
    # Conversation history (condensed)
    conversation_summary: str
    key_facts: list[str] = field(default_factory=list)
    decisions_made: list[str] = field(default_factory=list)
    
    # State
    collected_data: dict[str, Any] = field(default_factory=dict)
    confidence: float = 1.0  # How confident source was in resolution
    reason: HandoffReason = HandoffReason.SPECIALIZATION
    
    # Metadata
    created_at: float = None
    expires_at: Optional[float] = None
    
    def __post_init__(self):
        if self.created_at is None:
            self.created_at = time.time()
    
    def serialize(self) -> str:
        """Serialize to JSON for transport."""
        return json.dumps({
            "source_agent": self.source_agent,
            "target_agent": self.target_agent,
            "handoff_id": self.handoff_id,
            "task_id": self.task_id,
            "original_task": self.original_task,
            "current_state": self.current_state,
            "conversation_summary": self.conversation_summary,
            "key_facts": self.key_facts,
            "decisions_made": self.decisions_made,
            "collected_data": self.collected_data,
            "confidence": self.confidence,
            "reason": self.reason.value,
            "created_at": self.created_at,
        })
    
    @classmethod
    def deserialize(cls, data: str) -> "HandoffContext":
        """Deserialize from JSON."""
        obj = json.loads(data)
        obj["reason"] = HandoffReason(obj["reason"])
        return cls(**obj)

Step 2: Implement the Handoff Protocol

class HandoffProtocol:
    """Standard handoff protocol between agents."""
    
    def __init__(self, registry):
        self.registry = registry  # Agent registry
        self.active_handoffs: dict[str, HandoffContext] = {}
    
    async def initiate_handoff(self, context: HandoffContext) -> str:
        """Begin a handoff to another agent."""
        
        # 1. Validate target agent exists
        target = self.registry.get_agent(context.target_agent)
        if not target:
            raise ValueError(f"Unknown target agent: {context.target_agent}")
        
        # 2. Check target is ready
        if not await target.is_ready():
            # Fallback: try next available or escalate
            return await self._handle_unavailable_target(context)
        
        # 3. Store handoff context
        self.active_handoffs[context.handoff_id] = context
        
        # 4. Prepare receiving agent
        await target.prepare_for_handoff(context)
        
        # 5. Execute handoff
        result = await target.receive_handoff(context)
        
        # 6. Cleanup
        self.active_handoffs.pop(context.handoff_id, None)
        
        return result
    
    async def _handle_unavailable_target(self, context: HandoffContext) -> str:
        """Handle case where target agent is unavailable."""
        # Try finding an alternative
        alternatives = self.registry.find_alternatives(
            context.target_agent
        )
        
        if alternatives:
            context.target_agent = alternatives[0]
            return await self.initiate_handoff(context)
        
        # No alternatives — emergency escalation
        return await self._emergency_escalation(context)
    
    async def acknowledge_handoff(self, handoff_id: str, 
                                  accepted: bool, message: str = ""):
        """Target agent acknowledges (accepts or rejects) a handoff."""
        context = self.active_handoffs.get(handoff_id)
        if not context:
            raise ValueError(f"Unknown handoff: {handoff_id}")
        
        if accepted:
            context.source_agent = context.target_agent  # Transfer identity
            return {"status": "accepted", "context": context}
        else:
            # Handoff rejected — source must retry or escalate
            return {"status": "rejected", "reason": message}

Step 3: Agent Handoff Receiver

class HandoffReceiver:
    """Mixin for agents that can receive handoffs."""
    
    def __init__(self):
        self.handoff_buffer: dict[str, HandoffContext] = {}
        self.current_handoff: Optional[HandoffContext] = None
    
    async def prepare_for_handoff(self, context: HandoffContext):
        """Prepare to receive a handoff (pre-load context)."""
        self.handoff_buffer[context.handoff_id] = context
    
    async def receive_handoff(self, context: HandoffContext) -> str:
        """Accept and process an incoming handoff."""
        self.current_handoff = context
        
        # Build system prompt with transferred context
        handoff_prompt = self._build_handoff_prompt(context)
        
        # Run the agent with the prepared context
        result = await self.run(
            context.original_task,
            system_override=handoff_prompt
        )
        
        self.current_handoff = None
        return result
    
    def _build_handoff_prompt(self, context: HandoffContext) -> str:
        """Build system prompt with full handoff context."""
        facts = "\n".join(f"- {f}" for f in context.key_facts)
        decisions = "\n".join(f"- {d}" for d in context.decisions_made)
        
        return f"""You are taking over from {context.source_agent}.

## Current Task
{context.original_task}

## What Has Been Done
{context.current_state}

## Key Facts Discovered
{facts}

## Decisions Made So Far
{decisions}

## Collected Data
{json.dumps(context.collected_data, indent=2)}

## Reason for Handoff
{context.reason.value}

Your job is to continue from where {context.source_agent} left off. 
Do not redo work that has already been completed."""

Step 4: Escalation Chain

class EscalationChain:
    """Define and execute escalation paths for handoffs."""
    
    def __init__(self, protocol: HandoffProtocol):
        self.protocol = protocol
        self.chains = {}  # agent_type -> escalation path
    
    def define_chain(self, agent_type: str, chain: list[str]):
        """Define escalation chain (e.g., support -> billing -> manager)."""
        self.chains[agent_type] = chain
    
    async def escalate(self, context: HandoffContext, 
                       reason: str) -> str:
        """Escalate along the defined chain."""
        chain = self.chains.get(context.source_agent, [])
        
        if not chain:
            # End of chain — human escalation
            return await self._escalate_to_human(context, reason)
        
        next_agent = chain[0]
        context.reason = HandoffReason.ESCALATION
        context.target_agent = next_agent
        context.current_state += f"\n[Escalated: {reason}]"
        
        # Update chain (remove current level)
        self.chains[context.source_agent] = chain[1:]
        
        return await self.protocol.initiate_handoff(context)
    
    async def _escalate_to_human(self, context: HandoffContext, 
                                  reason: str) -> str:
        """When all agents exhausted, escalate to human."""
        ticket = {
            "handoff_id": context.handoff_id,
            "task": context.original_task,
            "context": context.serialize(),
            "reason": reason,
            "timestamp": time.time()
        }
        # Send to human operator queue
        await human_operator_queue.send(ticket)
        return f"Escalated to human operator. Ticket: {ticket['handoff_id']}"

Step 5: Conversation Continuity Across Handoffs

class ConversationContinuity:
    """Maintain conversation thread across multiple agent handoffs."""
    
    def __init__(self, storage):
        self.storage = storage
    
    async def log_turn(self, conversation_id: str, agent: str, 
                        message: str, role: str):
        """Log a single turn in a conversation thread."""
        entry = {
            "conversation_id": conversation_id,
            "agent": agent,
            "role": role,
            "message": message,
            "timestamp": time.time()
        }
        await self.storage.append(
            f"conversations:{conversation_id}",
            entry
        )
    
    async def get_history(self, conversation_id: str, 
                          limit: int = 50) -> list[dict]:
        """Get conversation history across agent handoffs."""
        return await self.storage.query(
            f"conversations:{conversation_id}",
            limit=limit
        )
    
    def build_continuity_prompt(self, history: list[dict], 
                                 current_agent: str) -> str:
        """Build a continuity prompt for the receiving agent."""
        previous_agents = set(
            entry["agent"] for entry in history 
            if entry["agent"] != current_agent
        )
        
        return f"""This conversation has involved: {', '.join(previous_agents)}.

## Previous Exchanges
{self._format_history(history)}

Continue naturally. If asked about something handled by a previous agent, 
reference that conversation."""
    
    def _format_history(self, history: list[dict]) -> str:
        formatted = []
        for entry in history[-10:]:  # Last 10 exchanges
            tag = f"[{entry['agent']}]" if entry['role'] == 'assistant' else "[User]"
            formatted.append(f"{tag}: {entry['message'][:200]}")
        return "\n".join(formatted)

Step 6: Handoff Decision Engine

class HandoffDecider:
    """Decide whether and where to hand off based on current state."""
    
    def __init__(self, llm, rules: list[dict]):
        self.llm = llm
        self.rules = rules  # Handoff trigger rules
    
    async def should_handoff(self, agent, task: str, 
                              current_state: dict) -> tuple[bool, str, str]:
        """Determine if handoff is needed and where to send."""
        
        # Check explicit rules first
        for rule in self.rules:
            if self._matches_rule(rule, agent, task, current_state):
                return True, rule["target"], rule["reason"]
        
        # If no rules match, ask LLM
        decision = await self.llm.generate(
            f"""Current agent: {agent.name}
Current task: {task}
Current state: {json.dumps(current_state, indent=2)}

Available agents: {', '.join(self._list_available_agents())}

Should this be handed off to another agent? If so, which one and why?
Respond in JSON: {{"handoff": true/false, "target": "agent_name", "reason": "why"}}""",
            temperature=0
        )
        
        try:
            result = json.loads(decision)
            return result["handoff"], result.get("target"), result.get("reason")
        except (json.JSONDecodeError, KeyError):
            return False, None, None
    
    def _matches_rule(self, rule: dict, agent, task: str, 
                      state: dict) -> bool:
        """Check if a handoff rule matches current conditions."""
        if "keywords" in rule:
            if any(kw in task.lower() for kw in rule["keywords"]):
                return True
        if "confidence_threshold" in rule:
            if state.get("confidence", 1.0) < rule["confidence_threshold"]:
                return True
        if "max_steps" in rule:
            if state.get("steps", 0) > rule["max_steps"]:
                return True
        return False

Handoff Flow Diagram

                    ┌───────────────────┐
                    │  User/System Task  │
                    └─────────┬─────────┘
                              │
                    ┌─────────▼─────────┐
                    │   Router Agent     │
                    │  (Intent Classify) │
                    └──┬────┬────┬──────┘
                       │    │    │
              ┌────────▼┐ ┌─▼──┐ ┌▼────────┐
              │ Support  │ │Billing│Research │
              │ Agent    │ │Agent │ Agent   │
              └──┬───────┘ └─────┘ └─────────┘
                 │
          Handoff Decision?
                 │
           ┌─────┴─────┐
           │           │
      Continue    Escalate
           │           │
           │     ┌─────▼──────┐
           │     │ Specialist  │
           │     │ Agent       │
           │     └─────┬──────┘
           │           │
           │     Still Stuck?
           │           │
           │     ┌─────▼──────┐
           │     │   Human     │
           └─────┘   Operator  │
                 └────────────┘

Trigger Phrases

Anti-Patterns