Re-roll the last roll with identical parameters.
AI agents invoke reroll to trigger actions in Dice MCP Server. 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 executes a dice rolling operation by re-triggering the previous roll with the same parameters. It performs a computation/action (simulating dice) rather than simply reading stored data or writing persistent data. The blast radius is minimal as it only affects ephemeral dice roll results with no real-world side effects.
From the tool's definition Re-roll the last roll with identical parameters
Attacks that exploit this kind of access
Re-roll the last roll with identical parameters. It is categorised as a Execute tool in the Dice MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Dice MCP Server MCP server in PolicyLayer and add a rule for reroll: 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 Dice MCP Server. Nothing to install.
reroll 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 reroll 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 reroll. 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.
reroll is provided by the Dice MCP Server MCP server (patissiermongs/roleplayingmcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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