AI agents use update_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.
An AI agent can call update_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
Update a Planner ToDo by human locator or raw todoId. Supports title, markdown description, owner, dueDate including null to clear, priority, and visibility. 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.
Register the Huly MCP server in PolicyLayer and add a rule for update_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.
update_todo 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 update_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.
Set action: deny in the PolicyLayer policy for update_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.
update_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.