| name | remote-agent |
| description | Bridge to external vertical agents (Google ADK, VeADK, etc.) for specialized tasks. |
| metadata | {"openclaw":{"emoji":"🔗","requires":{"env":["REMOTE_AGENT_URL"]}}} |
Remote Agent Bridge
This skill enables OpenClaw to delegate tasks to external, specialized AI agents via a standard HTTP interface. Use this when the user's request requires domain-specific knowledge (e.g., enterprise data, financial analysis, legal review) that is handled by a separate agent system.
Configuration
Ensure the following environment variables are set in your OpenClaw environment (e.g., via .env or openclaw config):
REMOTE_AGENT_URL: The HTTP endpoint of the external agent (e.g., https://remote-agent.example.com/run or your Google ADK endpoint).REMOTE_AGENT_KEY: (Optional) The Bearer token for authentication.
Usage
When the user asks a question that falls into the domain of a specialized remote agent, use this skill to forward the request.
Command
python3 skills/remote-agent/scripts/client.py --query "<USER_QUERY>" [--agent "<AGENT_ID>"]
Examples
Scenario 1: Financial Analysis (VeADK)
User: "Analyze the Q3 earnings report for TechCorp."
Thought: The user is asking for financial analysis. I should delegate this to the 'financial-expert' agent.
Action:
python3 skills/remote-agent/scripts/client.py --agent "financial-expert" --query "Analyze the Q3 earnings report for TechCorp"
Scenario 2: Enterprise Knowledge (Google ADK)
User: "What is the company policy on remote work?"
Thought: This requires internal knowledge. I'll ask the 'hr-bot'.
Action:
python3 skills/remote-agent/scripts/client.py --agent "hr-bot" --query "company policy on remote work"
Scenario 3: Custom LangChain Backend
User: "Run the data processing pipeline."
Action:
python3 skills/remote-agent/scripts/client.py --query "Run the data processing pipeline"
