Batch delete habits. Each dict should have "id".
AI agents call dida365_delete_habit to permanently remove resources in Dida365 Agent — typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
Deletion of habits is an irreversible destructive action that cannot be undone. Batch deletion amplifies the blast radius by allowing multiple habits to be removed in a single operation. An AI agent with misuse potential could delete all user habits, causing data loss. This is categorized as Destructive rather than Write because the operation cannot be reversed.
From the tool's definition Tool name is 'dida365_delete_habit' and description states 'Batch delete habits'. The verb 'delete' combined with 'batch' indicates irreversible removal of data records.
Risk signalsBulk/mass operation — affects multiple targets
Attacks that exploit this kind of access
Batch delete habits. Each dict should have "id". It is categorised as a Destructive tool in the Dida365 Agent MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the Dida365 Agent MCP server in PolicyLayer and add a rule for dida365_delete_habit: 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 Dida365 Agent. Nothing to install.
dida365_delete_habit is a Destructive tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.
Yes. Add a rate_limit block to the dida365_delete_habit 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 dida365_delete_habit. 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.
dida365_delete_habit is provided by the Dida365 Agent MCP server (linhai0872/dida365-agent). 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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