Multi-Agent Coordination Specification

Document ID: AGENT-008 File Path: docs/04-agent-framework/multi-agent-coordination.md Version: 1.0.0 Status: Draft Owner: AI Platform Team Last Updated: 2026-06-26

1. Purpose

The Multi-Agent Coordination subsystem enables multiple autonomous AI agents to collaborate toward shared objectives while maintaining isolation, governance, observability, and deterministic workflow execution.

Instead of relying on a single large agent to perform every task, Wovyr distributes work among specialized agents capable of planning, executing, reviewing, validating, and communicating with one another.

The coordination framework transforms the platform into a distributed AI operating system.

2. Objectives

The Multi-Agent Coordination subsystem shall provide:

Agent discovery
Agent registry
Agent-to-Agent (A2A) messaging
Dynamic task delegation
Hierarchical execution
Swarm intelligence
Distributed planning
Shared memory synchronization
Consensus algorithms
Conflict resolution
Human participation
Event-driven collaboration

3. Design Principles

Agents are independent execution units.
Every interaction is authenticated.
Communication is asynchronous by default.
Coordination is event-driven.
Shared state is minimized.
Every delegation is auditable.
Agent failures never compromise the overall workflow.

4. High-Level Architecture

                     Workflow Runtime
                            │
                            ▼
                  Coordination Manager
                            │
       ┌────────────────────┼────────────────────┐
       ▼                    ▼                    ▼
  Agent Registry      Message Bus       Task Scheduler
       │                    │                    │
       └────────────────────┼────────────────────┘
                            ▼
                  Specialized Agents
       ┌────────────┬────────────┬────────────┐
       ▼            ▼            ▼            ▼
  Planner      Developer      QA Agent   Documentation

5. Core Components

Component	Responsibility
Agent Registry	Discover available agents
Coordination Manager	Manage collaboration
Task Scheduler	Assign work
Message Bus	Deliver inter-agent messages
Consensus Engine	Resolve disagreements
Conflict Resolver	Handle execution conflicts
Shared Memory Adapter	Synchronize knowledge
Observability Layer	Metrics and tracing

6. Agent Roles

Example specialized agents:

Planner Agent
Developer Agent
QA Agent
Documentation Agent
Security Agent
Compliance Agent
DevOps Agent
Database Agent
Blockchain Agent
Infrastructure Agent
Reviewer Agent
Deployment Agent

Each role is independently deployable.

7. Agent Registry

The registry stores:

Agent ID
Version
Capabilities
Skills
Status
Health
Supported models
Tool access
Owner
Tenant

The registry enables runtime discovery.

8. Agent Discovery

Discovery methods:

By capability
By role
By tags
By labels
By tenant
By version
By workload
By health status

Discovery occurs before delegation.

9. Coordination Models

Supported coordination patterns:

Pattern	Description
Supervisor	One coordinator manages all agents
Peer-to-Peer	Agents collaborate directly
Hierarchical	Parent-child delegation
Swarm	Dynamic decentralized execution
Pipeline	Sequential specialization
Market-Based	Agents bid for work

10. Task Delegation

Delegation flow:

Planner Agent

↓

Identify Task

↓

Select Agent

↓

Assign Work

↓

Receive Result

↓

Continue Plan

Delegation decisions consider capability, availability, cost, and policies.

11. Agent-to-Agent Messaging

Supported message types:

Command
Event
Request
Response
Broadcast
Notification
Status Update
Approval Request

Messages are delivered via the Event Bus.

12. Message Structure

messageId:
senderAgent:
receiverAgent:
workflowId:
conversationId:
messageType:
payload:
priority:
timestamp:
correlationId:

Messages are immutable once published.

13. Shared Memory

Agents may exchange knowledge through Shared Memory.

Supported scopes:

Workflow
Project
Organization
Global

Access is governed by the Policy Engine.

14. Consensus Engine

Consensus strategies:

Majority Vote
Weighted Vote
Supervisor Override
Confidence Score
Human Approval
Deterministic Rule

Consensus resolves conflicting recommendations.

15. Conflict Resolution

Conflict sources:

Conflicting plans
Contradictory outputs
Resource contention
Policy violations
Version mismatches

Resolution strategies are configurable.

16. Parallel Collaboration

Example:

Planner

↓

───────────────

│      │      │

▼      ▼      ▼

Dev    QA   Docs

│      │      │

───────────────

↓

Merge Results

Parallel execution minimizes workflow latency.

17. Failure Handling

Failures include:

Agent crash
Timeout
Network failure
Tool failure
Permission denial

Recovery options:

Retry
Delegate to another agent
Human intervention
Workflow compensation

18. Human Participation

Humans participate as first-class actors.

Examples:

Approval
Review
Editing
Escalation
Decision override

Human actions are represented as workflow activities.

19. Security

Security measures include:

Mutual authentication
Message signing
Encryption in transit
RBAC
ABAC
Tenant isolation
Audit logging

Every message is authenticated.

20. Observability

Metrics:

Delegation latency
Message throughput
Agent utilization
Task completion rate
Consensus duration
Collaboration efficiency
Failure rate

Distributed tracing spans all participating agents.

21. Rust Interface

pub trait CoordinationManager {

    fn delegate(
        &self,
        task: Task,
    ) -> Result<Assignment>;

    fn send(
        &self,
        message: AgentMessage,
    ) -> Result<()>;

    fn discover(
        &self,
        query: AgentQuery,
    ) -> Result<Vec<AgentMetadata>>;
}

22. Module Organization

engine-coordination/
├── registry/
├── scheduler/
├── messaging/
├── delegation/
├── consensus/
├── conflict/
├── discovery/
├── shared-memory/
├── metrics/
└── mod.rs

23. Testing Strategy

Unit Tests

Agent discovery
Delegation logic
Message routing
Consensus algorithms

Integration Tests

Workflow Runtime
Event Bus
Shared Memory
Policy Engine

Performance Tests

10,000 concurrent agents
Million-message workloads
Distributed clusters
Large workflow graphs

24. Non-Functional Requirements

Requirement	Target
Agent discovery	< 5 ms
Message delivery	< 20 ms
Delegation	< 10 ms
Consensus	< 100 ms
Availability	99.99%

25. Dependencies

docs/03-workflow-engine/event-bus.md
docs/03-workflow-engine/distributed-execution.md
docs/04-agent-framework/planning-engine.md
docs/04-agent-framework/memory-system.md
docs/04-agent-framework/policy-engine.md

docs/04-agent-framework/agent-definition.md
docs/04-agent-framework/context-manager.md
docs/04-agent-framework/provider-sdk.md
docs/04-agent-framework/tool-framework.md

27. Future Enhancements

Self-organizing agent swarms
Reinforcement-learning coordination
Federated agent clusters
Marketplace-driven delegation
Autonomous agent lifecycle management
Cross-platform A2A federation
AI-generated coordination strategies

28. Revision History

Version	Date	Description
1.0.0	2026-06-26	Initial Multi-Agent Coordination Specification