Agent-to-Agent Communication Protocol for Openclaw

A foundational communication layer enabling AI agents to interact via events and automate multi-step workflows without human intervention.

robbyczgw-cla
v1.0.0
Jan 29, 2026
0
0
0

Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install agent-protocol

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

Copy this prompt to OpenClaw to install it automatically.

Help me install agent-protocol using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).

Prefer to download?

Get the raw skill files in a ZIP archive.

What is Agent-to-Agent Communication Protocol?

The Agent-to-Agent Protocol serves as the backbone for creating sophisticated, autonomous ecosystems. By leveraging this framework within the Openclaw Skills library, developers can transform individual agents into a collaborative network. The protocol utilizes a file-based event bus to facilitate message passing, ensuring that every interaction is persistent, debuggable, and auditable.

This system allows for the creation of complex workflow chains where one agent's output becomes another's trigger. Whether you are building research pipelines or real-time monitoring systems, this protocol provides the essential structure for shared context, capability discovery, and secure permission management across your entire agent fleet.

Agent-to-Agent Communication Protocol Use Cases

  • Automating research pipelines where finding a relevant article triggers a summary agent and subsequent notification.
  • Implementing real-time sports alerts that move from live monitoring to text-to-speech announcements.
  • Creating scheduled analytics workflows that generate insights and feed them back into research agents for continuous learning.
  • Developing multi-channel notification systems that broadcast high-importance events across Telegram, Discord, and Email simultaneously.

How Agent-to-Agent Communication Protocol Works

  1. Agents publish JSON-formatted events to a centralized directory (~/.clawdbot/events/) which acts as a file-based message bus.
  2. The event bus performs schema validation to ensure data integrity and manages the lifecycle of each message.
  3. The Workflow Engine monitors the bus for specific event types that match predefined triggers or conditions.
  4. Upon a trigger, the engine executes a sequence of steps, orchestrating different agents and passing data through a shared context.
  5. The Agent Registry manages permissions and advertisements, allowing agents to securely discover and interact with one another.

Agent-to-Agent Communication Protocol Setup

To integrate this protocol into your environment, follow these steps:

# Navigate to the skill directory
cd /root/clawd/skills/agent-protocol

# Run the setup script to initialize directories and dependencies
python3 scripts/setup.py

# Start the event bus daemon
python3 scripts/event_bus.py start

# Validate your workflow configurations
python3 scripts/workflow_engine.py --validate

Agent-to-Agent Communication Protocol Data Schema & Taxonomy

The protocol organizes its data through a structured filesystem and JSON schema to maintain consistency across Openclaw Skills.

Path/Component Description
~/.clawdbot/events/ Active event storage in JSON format
~/.clawdbot/events/log/ Historical audit logs of all processed events
config/workflows/ JSON/YAML definitions for agent pipelines
config/protocol.json Global settings for retention, security, and polling intervals
Agent Registry A central JSON index of agent capabilities and permissions

Agent-to-Agent Communication Protocol Advanced Features

  • Conditional Routing: Direct events to different agents based on logic gates applied to the event payload.
  • Parallel Execution: Execute multiple agent actions concurrently to minimize latency in complex workflows.
  • Advanced Error Handling: Define custom retry logic, backoff strategies, and fallback handlers for resilient operations.
  • Scheduled Workflows: Integrate with cron for periodic agent invocations independent of external event triggers.

SKILL.md


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