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reboot_all_nodes

Restart all compute nodes in a CloudLab experiment to resolve issues or apply configuration changes. Specify the experiment ID to initiate the reboot process.

Instructions

Reboot all nodes in an experiment

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
experiment_idYesExperiment UUID (from list_experiments)

Implementation Reference

  • The handler function for the 'reboot_all_nodes' tool. It extracts the experiment_id from arguments, makes a POST request to the CloudLab API endpoint `/experiments/{experiment_id}/nodes/reboot`, and returns the result in a formatted text response.
    case "reboot_all_nodes": {
      const { experiment_id } = args as { experiment_id: string };
      const result = await cloudlabRequest(
        `/experiments/${experiment_id}/nodes/reboot`,
        "POST"
      );
      return {
        content: [
          {
            type: "text",
            text: `Reboot initiated for all nodes: ${JSON.stringify(result, null, 2)}`,
          },
        ],
      };
    }
  • The input schema for the 'reboot_all_nodes' tool, defining an object with a required 'experiment_id' string property.
    inputSchema: {
      type: "object",
      properties: {
        experiment_id: {
          type: "string",
          description: "Experiment UUID (from list_experiments)",
        },
      },
      required: ["experiment_id"],
    },
  • src/index.ts:171-184 (registration)
    The registration of the 'reboot_all_nodes' tool in the ListToolsRequestSchema handler, including name, description, and input schema.
    {
      name: "reboot_all_nodes",
      description: "Reboot all nodes in an experiment",
      inputSchema: {
        type: "object",
        properties: {
          experiment_id: {
            type: "string",
            description: "Experiment UUID (from list_experiments)",
          },
        },
        required: ["experiment_id"],
      },
    },
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden but provides minimal behavioral insight. It mentions 'reboot' but doesn't clarify if this is destructive (e.g., interrupts processes), requires specific permissions, has side effects, or details response behavior (e.g., success/failure indicators). This is inadequate for a mutation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero wasted words. It is front-loaded with the core action and target, making it highly concise and well-structured for quick understanding.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (a mutation affecting multiple nodes), lack of annotations, and no output schema, the description is incomplete. It fails to address critical aspects like safety, permissions, or expected outcomes, leaving significant gaps for an agent to use it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents the 'experiment_id' parameter fully. The description adds no additional meaning beyond implying the parameter's role in targeting nodes, aligning with the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('reboot') and target ('all nodes in an experiment'), making the purpose immediately understandable. It distinguishes from sibling tools like 'reboot_node' (singular) and 'powercycle_node' (different action), though it doesn't explicitly contrast them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives like 'reboot_node' for individual nodes or 'reload_node' for a different action. The description lacks context about prerequisites (e.g., experiment state) or exclusions, leaving usage ambiguous.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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