schedule_todo · Huly MCP: Risk & Policy

WHAT IT DOES

What schedule_todo does on Huly

AI agents use schedule_todo to create or update resources in Huly — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Huly environment.

WHY IT NEEDS A POLICY

Why schedule_todo needs a policy

An AI agent can call schedule_todo faster than any human can review — one bad instruction and it creates or modifies resources in Huly by the hundred, each call as confident as the last.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

schedule_todo Rate-limited

schedule_todo 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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "schedule_todo": {
      "limits": [
        {
          "counter": "schedule_todo_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches Huly, so you can run agents against it safely.

FAQ

Questions about schedule_todo

What does the schedule_todo tool do? +

Schedule a Planner ToDo by raw todoId or human locator, creating a work slot with ToDo title, description, and visibility metadata. It is categorised as a Write tool in the Huly MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on schedule_todo? +

Register the Huly MCP server in PolicyLayer and add a rule for schedule_todo: 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 Huly. Nothing to install.

What risk level is schedule_todo? +

schedule_todo is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit schedule_todo? +

Yes. Add a rate_limit block to the schedule_todo 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.

How do I block schedule_todo completely? +

Set action: deny in the PolicyLayer policy for schedule_todo. 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.

What MCP server provides schedule_todo? +

schedule_todo is provided by the Huly MCP server (@firfi/huly-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.