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execute_robot_task

Control robots using natural language commands to perform tasks like movement and object manipulation. Send Vision-Language-Action instructions to automate robotic operations.

Instructions

Send a Vision-Language-Action command to a robot

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
robot_idYesID of the robot to control
instructionYesNatural language instruction (e.g., "Move to loading dock")
coordinatesNoOptional target coordinates

Implementation Reference

  • The handler function `executeRobotTask` which sends a POST request to the robotics API to execute a task.
    async executeRobotTask(args) {
      const response = await axios.post(
        `${API_BASE}/api-robotics.php`,
        {
          action: 'execute_task',
          robot_id: args.robot_id,
          instruction: args.instruction,
          coordinates: args.coordinates,
        },
        { headers: { 'X-API-Key': API_KEY } }
      );
      
      return {
        content: [
          {
            type: 'text',
            text: `Task executed: ${response.data.status || 'success'}`,
          },
        ],
      };
    }
  • The schema definition for `execute_robot_task` which defines required inputs (robot_id, instruction).
    name: 'execute_robot_task',
    description: 'Send a Vision-Language-Action command to a robot',
    inputSchema: {
      type: 'object',
      properties: {
        robot_id: {
          type: 'string',
          description: 'ID of the robot to control',
        },
        instruction: {
          type: 'string',
          description: 'Natural language instruction (e.g., "Move to loading dock")',
        },
        coordinates: {
          type: 'object',
          properties: {
            x: { type: 'number' },
            y: { type: 'number' },
          },
          description: 'Optional target coordinates',
        },
      },
      required: ['robot_id', 'instruction'],
    },
  • server.js:185-186 (registration)
    The tool registration logic where the `execute_robot_task` call is routed to the handler.
    case 'execute_robot_task':
      return await this.executeRobotTask(args);
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'Vision-Language-Action command' but doesn't explain what that entails (e.g., is it a complex AI-driven task, does it involve movement or sensing, are there safety or permission requirements?). This leaves critical behavioral traits unspecified for a robot control 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 waste—it directly states the tool's function without unnecessary words, making it highly concise and well-structured.

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 robot control (a potentially high-stakes operation), no annotations, no output schema, and the description's lack of behavioral details, it's incomplete. The agent lacks information on what happens after execution (e.g., success/failure, response format) or any constraints, making this inadequate for safe and effective use.

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 all parameters (robot_id, instruction, coordinates). The description adds no additional meaning beyond what's in the schema, such as examples of valid instructions or coordinate usage, resulting in the baseline score.

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 ('Send a Vision-Language-Action command') and the target ('to a robot'), making the purpose understandable. However, it doesn't differentiate this tool from potential siblings like 'stop_robot' or 'get_robot_status' that also involve robot interaction, missing explicit distinction.

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. For example, it doesn't specify if this is for high-level commands versus direct control, or how it differs from 'stop_robot' or 'get_robot_status', leaving the agent without context for selection.

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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