dida365_update_habit · Dida365 Agent MCP: Risk & Policy

WHAT IT DOES

What dida365_update_habit does on Dida365 Agent

AI agents use dida365_update_habit to create or update resources in Dida365 Agent — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Dida365 Agent environment.

WHY IT NEEDS A POLICY

Why dida365_update_habit needs a policy

The tool creates or modifies data (habits) in a reversible manner without deleting or destroying data, and does not execute arbitrary code or move money. It falls squarely into the Write category. Severity is medium because inadvertent mass updates to habits via batch operation could disrupt a user's productivity system and task organization, but changes are reversible through subsequent updates or restoration.

From the tool's definition Tool name contains 'update' and description explicitly states 'Batch update habits' with required 'id' and 'fields to update'. This modifies existing habit data reversibly.

Risk signalsBulk/mass operation — affects multiple targets

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

dida365_update_habit Rate-limited

dida365_update_habit stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "dida365_update_habit": {
      "limits": [
        {
          "counter": "dida365_update_habit_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches Dida365 Agent, so you can run agents against it safely.

FAQ

Questions about dida365_update_habit

What does the dida365_update_habit tool do? +

Batch update habits. Each dict should have "id" (required) plus fields to update. It is categorised as a Write tool in the Dida365 Agent MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on dida365_update_habit? +

Register the Dida365 Agent MCP server in PolicyLayer and add a rule for dida365_update_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.

What risk level is dida365_update_habit? +

dida365_update_habit is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit dida365_update_habit? +

Yes. Add a rate_limit block to the dida365_update_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.

How do I block dida365_update_habit completely? +

Set action: deny in the PolicyLayer policy for dida365_update_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.

What MCP server provides dida365_update_habit? +

dida365_update_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.