A standardized protocol for AI agents to communicate, share files, and collaborate on complex tasks without system conflicts.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install cross-agent-collab
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install cross-agent-collab 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 Cross-Agent Collaboration Guide?
The Cross-Agent Collaboration skill is a comprehensive framework designed to facilitate seamless interaction between autonomous AI agents. In complex ecosystems where multiple agents—such as mexico and others—operate simultaneously, this skill provides the necessary rules to prevent communication loops, system crashes, and data silos. By utilizing these Openclaw Skills guidelines, developers can ensure that agents running on diverse platforms like Clawdbot or OpenClaw can effectively synchronize their efforts.
This skill emphasizes decentralized operation, assuming that agents do not share a common file system or configuration architecture. It focuses on concise, actionable communication and strict security boundaries to protect sensitive information while allowing for high-level technical cooperation and joint task execution.
Cross-Agent Collaboration Guide Use Cases
- Coordinating joint research tasks where agents divide and conquer specific sub-topics.
- Managing collaborative coding projects involving an author agent and a reviewer agent.
- Sharing technical documentation and reports across different agent systems via secure attachments.
- Resolving complex technical discussions through structured, multi-turn dialogue without human intervention.
- Synchronizing multi-agent workflows in shared communication channels like Discord.
How Cross-Agent Collaboration Guide Works
- The agent identifies a collaboration trigger such as a mention of a partner agent or a request for joint action.
- Communication begins with the assumption that the partner agent operates on a different framework with an independent file system.
- Tasks are divided clearly (e.g., Agent A handles data gathering, Agent B handles synthesis).
- Information and documents are exchanged exclusively via attachments rather than local file paths to ensure accessibility.
- Echo-loop prevention logic is applied, where agents remain silent (NO_REPLY) unless a specific question or request is posed.
- Results are aggregated and presented to the human user for final adjudication and approval.
Cross-Agent Collaboration Guide Setup
To implement these collaboration protocols within your environment, ensure the skill markdown is accessible to your agent's context. No specific binary installation is required, as this serves as a behavioral protocol.
# Example: Integrating collaboration rules into an agent's system prompt
cat skills/cross-agent-collab.md >> agent_system_prompt.txt
Ensure your agent is configured to recognize the communication patterns defined in the Openclaw Skills repository for cross-system compatibility.
Cross-Agent Collaboration Guide Data Schema & Taxonomy
The skill utilizes a protocol-based data exchange schema to ensure compatibility across different Openclaw Skills implementations:
| Feature | Requirement | Description |
|---|---|---|
| File Sharing | Attachment Only | Files must be sent as objects/attachments, never as local strings or paths. |
| Message Focus | Single Point | Each message must address exactly one primary topic to avoid information overload. |
| State Management | NO_REPLY | Use the silent state to terminate loops when a task is confirmed or summarized. |
| Conflict Handling | Human Arbiter | All unsolvable disagreements are escalated to a human user via a standard notification. |
Cross-Agent Collaboration Guide Advanced Features
- Echo-loop prevention logic to minimize token usage and prevent infinite agent-to-agent chatter.
- Cross-framework interoperability support for agents running on OpenClaw, Clawdbot, or custom implementations.
- Standardized 'Joint Review' and 'Joint Creation' workflows for structured content production.
- Security-first communication filters that prevent the accidental sharing of API keys or private credentials during collaboration.
SKILL.md
Loading
Related Openclaw Skills
Content Distributor
A multi-platform automation tool for distributing content across Chinese social media networks like Zhihu, Douban, and Weibo.
Agent Lingua
A high-performance, human-unreadable communication language designed to slash token costs and optimize agent-to-agent interactions.
A2A-Lite: Agent-to-Agent Communication Protocol
A2A-Lite is a lightweight communication protocol enabling AI agents to discover peer capabilities and collaborate on structured tasks using human-readable messaging.
Multi-Agent Role Design Framework
A comprehensive framework for architecting professional multi-agent AI systems with specialized roles and clear communication boundaries.
Skill Security Audit
A comprehensive security auditing tool designed to detect credential leaks, dangerous commands, and unauthorized network activity within Openclaw Skills.
Email Send (SMTP & Resend API)
A versatile email automation skill for Openclaw Skills that supports sending plain text, HTML, and attachments via SMTP or Resend API.
Featured*
