AI agents use stop_task to create or update resources in Task — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Task environment.
This tool pauses an active timer on a task but keeps the claim intact. It modifies the task's state (from active/started to stopped/paused) in a reversible way — the task can be restarted. No data is deleted, no code is executed, and no financial operations are involved. This is a Write operation with low severity since it only affects task timing state.
From the tool's definition Stop working on a task (pauses active timer, keeps claim)
Attacks that exploit this kind of access
Stop working on a task (pauses active timer, keeps claim). It is categorised as a Write tool in the Task MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Task MCP server in PolicyLayer and add a rule for stop_task: 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 Task. Nothing to install.
stop_task 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 stop_task 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 stop_task. 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.
stop_task is provided by the Task MCP server (maxronner/taskwarrior-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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