Report progress on an agent task. Call this as you make progress.
AI agents use agent_update to create or update resources in Conductor — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Conductor environment.
The tool writes progress information to a task record, which is a reversible operation. It does not execute code, delete data, move money, or trigger external side effects; it simply records progress metadata. The low severity reflects that misuse would only result in incorrect progress reporting without affecting task execution or data integrity.
From the tool's definition Tool description states 'Report progress on an agent task' — this is a status/progress update operation that modifies task state reversibly without destructive or executable effects.
Documented attack patterns abuse exactly the kind of access agent_update gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Conductor, and nothing reaches the server without passing your rules. This is the rule we recommend for agent_update:
{
"version": "1",
"default": "deny",
"tools": {
"agent_update": {
"limits": [
{
"counter": "agent_update_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
} agent_update stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
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Report progress on an agent task. Call this as you make progress. It is categorised as a Write tool in the Conductor MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Conductor MCP server in PolicyLayer and add a rule for agent_update: 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 Conductor. Nothing to install.
agent_update is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the agent_update 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 agent_update. 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.
agent_update is provided by the Conductor MCP server (shannonbay/conductor). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Conductor, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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16 Conductor tools catalogued and risk-classified — across an index of 43,000+ MCP servers.