Low Risk

request_tutorial

Submit a request for a tutorial we don't yet have. Call this when search_tutorials returned no good match for what the user actually wants. The request enters our content-demand queue, which the daily content batch reviews and prioritizes. Optionally include an email for notification when the tut...

Part of the ShowMeStepByStep server.

request_tutorial is read-only, but an agent in a loop can still rack up calls and cost. PolicyLayer caps every call before it runs. Live in minutes.

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AI agents call request_tutorial to retrieve information from ShowMeStepByStep without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.

Even though request_tutorial only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.

Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "request_tutorial": {}
  }
}

See the full ShowMeStepByStep policy for all 6 tools.

Get this rule live on your own ShowMeStepByStep server in minutes. PolicyLayer enforces it on every call, before it runs.

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These attack patterns abuse exactly the kind of access request_tutorial gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so request_tutorial only ever does what you allow.

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Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.

What does the request_tutorial tool do? +

Submit a request for a tutorial we don't yet have. Call this when search_tutorials returned no good match for what the user actually wants. The request enters our content-demand queue, which the daily content batch reviews and prioritizes. Optionally include an email for notification when the tutorial ships.. It is categorised as a Read tool in the ShowMeStepByStep MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on request_tutorial? +

Register the ShowMeStepByStep MCP server in PolicyLayer and add a rule for request_tutorial: 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 ShowMeStepByStep. Nothing to install.

What risk level is request_tutorial? +

request_tutorial is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit request_tutorial? +

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

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

request_tutorial is provided by the ShowMeStepByStep MCP server (https://www.showmestepbystep.com/api/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every ShowMeStepByStep tool call.

Deterministic rules across all 6 ShowMeStepByStep tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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