Skip to main content
Glama

extend_experiment

Extend the expiration time of a CloudLab experiment by specifying the number of hours to add, preventing premature termination.

Instructions

Extend the expiration time of an experiment

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
experiment_idYesExperiment UUID (from list_experiments)
hoursYesNumber of hours to extend

Implementation Reference

  • The handler logic for the 'extend_experiment' tool. It extracts experiment_id and hours from arguments, calls cloudlabRequest with PUT /experiments/{id} and body {extend_by: hours}, and returns the result.
    case "extend_experiment": {
      const { experiment_id, hours } = args as {
        experiment_id: string;
        hours: number;
      };
      const result = await cloudlabRequest(
        `/experiments/${experiment_id}`,
        "PUT",
        { extend_by: hours }
      );
      return {
        content: [
          {
            type: "text",
            text: `Extension requested: ${JSON.stringify(result, null, 2)}`,
          },
        ],
      };
    }
  • src/index.ts:221-238 (registration)
    Registration of the 'extend_experiment' tool in the ListTools handler, including description and input schema definition.
    {
      name: "extend_experiment",
      description: "Extend the expiration time of an experiment",
      inputSchema: {
        type: "object",
        properties: {
          experiment_id: {
            type: "string",
            description: "Experiment UUID (from list_experiments)",
          },
          hours: {
            type: "number",
            description: "Number of hours to extend",
          },
        },
        required: ["experiment_id", "hours"],
      },
    },
  • Input schema for the 'extend_experiment' tool, defining required parameters: experiment_id (string) and hours (number).
    {
      name: "extend_experiment",
      description: "Extend the expiration time of an experiment",
      inputSchema: {
        type: "object",
        properties: {
          experiment_id: {
            type: "string",
            description: "Experiment UUID (from list_experiments)",
          },
          hours: {
            type: "number",
            description: "Number of hours to extend",
          },
        },
        required: ["experiment_id", "hours"],
      },
    },
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action ('Extend') but doesn't describe what happens upon execution—e.g., whether it's idempotent, requires specific permissions, has rate limits, returns a confirmation or updated experiment object, or affects experiment status. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.

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 that directly states the tool's purpose without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse. Every word earns its place, and there's no redundancy or fluff.

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 complexity of a mutation tool (extending an experiment's expiration) with no annotations and no output schema, the description is incomplete. It doesn't cover behavioral aspects like side effects, error conditions, or return values, leaving gaps for an AI agent to understand how to use it correctly. The description should do more to compensate for the lack of structured data.

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%, with both parameters ('experiment_id' and 'hours') fully documented in the input schema. The description doesn't add any meaning beyond what the schema provides—it doesn't explain parameter interactions, constraints (e.g., 'hours' must be positive), or default behaviors. Baseline 3 is appropriate when the schema does the heavy lifting.

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 ('Extend') and the target resource ('expiration time of an experiment'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from potential alternatives like 'renew_experiment' or 'update_experiment_expiry', though no such siblings exist in the provided list. The purpose is unambiguous but lacks sibling differentiation.

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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., the experiment must be active or not yet expired), exclusions (e.g., cannot extend beyond a maximum limit), or related tools like 'terminate_experiment' for ending experiments. Usage is implied only by the tool name and description.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/ArdaGurcan/cloudlab-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server