rate_terms_batch
AI agents use rate_terms_batch to create or update resources in Phenomenai — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Phenomenai environment.
The name implies writing ratings/scores for multiple terms at once (a Write operation). Without a description, there is uncertainty about whether it merely reads ratings or submits them. Batch rating is likely a reversible write action. Confidence is low due to the empty description.
From the tool's definition Tool name 'rate_terms_batch' suggests batch rating of terms; description is empty and uninformative.
Attacks that exploit this kind of access
rate_terms_batch. It is categorised as a Write tool in the Phenomenai MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Phenomenai MCP server in PolicyLayer and add a rule for rate_terms_batch: 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 Phenomenai. Nothing to install.
rate_terms_batch 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 rate_terms_batch 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 rate_terms_batch. 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.
rate_terms_batch is provided by the Phenomenai MCP server (phenomenai-org/ai-dictionary-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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