Execute a task using a previously created expert agent
AI agents invoke execute_expert to trigger actions in Nexus Agents. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
This tool runs tasks through expert agents (which are AI models like Claude, Codex, Gemini, OpenCode per server description). Execution of arbitrary tasks by AI agents poses high risk if misused—agents could be directed to harmful activities, though the blast radius is constrained by the expertise scope of individual agents and any built-in safeguards.
From the tool's definition Tool name 'execute_expert' and description 'Execute a task using a previously created expert agent' explicitly indicate code/task execution via an agent system.
Documented attack patterns abuse exactly the kind of access execute_expert gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Nexus Agents, and nothing reaches the server without passing your rules. This is the rule we recommend for execute_expert:
{
"version": "1",
"default": "deny",
"tools": {
"execute_expert": {
"limits": [
{
"counter": "execute_expert_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}execute_expert stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
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Execute a task using a previously created expert agent. It is categorised as a Execute tool in the Nexus Agents MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Nexus Agents MCP server in PolicyLayer and add a rule for execute_expert: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Nexus Agents. Nothing to install.
execute_expert is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the execute_expert rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for execute_expert. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
execute_expert is provided by the Nexus Agents MCP server (nexus-substrate/nexus-agents). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Nexus Agents, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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9 Nexus Agents tools catalogued and risk-classified — across an index of 43,000+ MCP servers.