create_study_plan · Interleaved Learning MCP Server MCP

WHAT IT DOES

What create_study_plan does on Interleaved Learning MCP Server

AI agents use create_study_plan to create or update resources in Interleaved Learning MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Interleaved Learning MCP Server environment.

WHY IT NEEDS A POLICY

Why create_study_plan needs a policy

This tool creates and stores a new study plan object (reversible data creation), fitting the Write category. The severity is low because misuse would only affect the user's own study schedule data with no blast radius to other systems, data integrity risks, or external side effects. High confidence due to clear intent and explicit 'create' semantics.

From the tool's definition Tool name 'create_study_plan' and description stating it 'Generate[s] an interleaved study schedule' indicates data creation. The description does not mention deletion, code execution, financial transactions, or irreversible operations.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

create_study_plan Rate-limited

create_study_plan 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": {
    "create_study_plan": {
      "limits": [
        {
          "counter": "create_study_plan_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 Interleaved Learning MCP Server, so you can run agents against it safely.

FAQ

Questions about create_study_plan

What does the create_study_plan tool do? +

Generate an interleaved study schedule. Alternates between topics based on cognitive science research for optimal retention. It is categorised as a Write tool in the Interleaved Learning MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on create_study_plan? +

Register the Interleaved Learning MCP Server MCP server in PolicyLayer and add a rule for create_study_plan: 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 Interleaved Learning MCP Server. Nothing to install.

What risk level is create_study_plan? +

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

Can I rate-limit create_study_plan? +

Yes. Add a rate_limit block to the create_study_plan 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 create_study_plan completely? +

Set action: deny in the PolicyLayer policy for create_study_plan. 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 create_study_plan? +

create_study_plan is provided by the Interleaved Learning MCP Server MCP server (sheikhcoders/interleaved-learning-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.