Low Risk

get_student_info

Get detailed information about a specific student by name (partial match supported). Args: name: Student name or partial name to search for

Part of the STIL Lab Assistant server.

get_student_info 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 get_student_info to retrieve information from STIL Lab Assistant 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 get_student_info 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": {
    "get_student_info": {}
  }
}

See the full STIL Lab Assistant policy for all 8 tools.

Get this rule live on your own STIL Lab Assistant 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 get_student_info 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 get_student_info 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 get_student_info tool do? +

Get detailed information about a specific student by name (partial match supported). Args: name: Student name or partial name to search for. It is categorised as a Read tool in the STIL Lab Assistant MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on get_student_info? +

Register the STIL Lab Assistant MCP server in PolicyLayer and add a rule for get_student_info: 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 STIL Lab Assistant. Nothing to install.

What risk level is get_student_info? +

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

Can I rate-limit get_student_info? +

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

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

get_student_info is provided by the STIL Lab Assistant MCP server (oci:ghcr.io/khalid-tounoussi-1/stil-ets-mcp:1.0.0). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every STIL Lab Assistant tool call.

Deterministic rules across all 8 STIL Lab Assistant tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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