wait_for_training_tool · Qiskit Documentation MCP Server MCP

WHAT IT DOES

What wait_for_training_tool does on Qiskit Documentation MCP Server

AI agents invoke wait_for_training_tool to trigger actions in Qiskit Documentation MCP Server. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.

WHY IT NEEDS A POLICY

Why wait_for_training_tool needs a policy

Despite the empty description, the name pattern 'wait_for_*' combined with the training-focused context suggests this tool initiates or monitors execution of a training process. This is Execute (not Read) because it likely triggers or waits for an external operation whose effects depend on the training environment/arguments.

From the tool's definition Tool name contains 'wait_for_training' which suggests blocking or waiting for an external process (training) to complete. Sibling tools include batch_train_environments_tool, indicating this server manages training operations.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

wait_for_training_tool Rate-limited

wait_for_training_tool stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "wait_for_training_tool": {
      "limits": [
        {
          "counter": "wait_for_training_tool_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL →

Instant setup, no code required.

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

FAQ

Questions about wait_for_training_tool

What does the wait_for_training_tool tool do? +

wait_for_training_tool. It is categorised as a Execute tool in the Qiskit Documentation MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on wait_for_training_tool? +

Register the Qiskit Documentation MCP Server MCP server in PolicyLayer and add a rule for wait_for_training_tool: 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 Qiskit Documentation MCP Server. Nothing to install.

What risk level is wait_for_training_tool? +

wait_for_training_tool is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit wait_for_training_tool? +

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

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

wait_for_training_tool is provided by the Qiskit Documentation MCP Server MCP server (pypi:qiskit-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.