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AbbottDevelopments

Shopmonkey MCP Server

update_vehicle

Modify vehicle details like year, make, model, VIN, license plate, color, and mileage in the Shopmonkey system to keep customer records current.

Instructions

Update an existing vehicle's information.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesThe vehicle ID to update
customerIdNoCustomer ID to associate with the vehicle
yearNoVehicle model year
makeNoVehicle make
modelNoVehicle model
vinNoVehicle Identification Number
licensePlateNoLicense plate number
colorNoVehicle color
mileageNoCurrent mileage

Implementation Reference

  • The implementation of the update_vehicle tool handler, which uses shopmonkeyRequest to perform a PATCH request to the vehicle endpoint.
    async update_vehicle(args) {
      if (!args.id) return { content: [{ type: 'text', text: 'Error: id is required' }], isError: true };
      const body = pickFields(args, ALLOWED_FIELDS);
      const data = await shopmonkeyRequest<Vehicle>('PATCH', `/vehicle/${sanitizePathParam(String(args.id))}`, body);
      return { content: [{ type: 'text', text: JSON.stringify(data, null, 2) }] };
    },
  • The definition and input schema for the update_vehicle tool.
    {
      name: 'update_vehicle',
      description: 'Update an existing vehicle\'s information.',
      inputSchema: {
        type: 'object' as const,
        properties: {
          id: { type: 'string', description: 'The vehicle ID to update' },
          customerId: { type: 'string', description: 'Customer ID to associate with the vehicle' },
          year: { type: 'number', description: 'Vehicle model year' },
          make: { type: 'string', description: 'Vehicle make' },
          model: { type: 'string', description: 'Vehicle model' },
          vin: { type: 'string', description: 'Vehicle Identification Number' },
          licensePlate: { type: 'string', description: 'License plate number' },
          color: { type: 'string', description: 'Vehicle color' },
          mileage: { type: 'number', description: 'Current mileage' },
        },
        required: ['id'],
      },
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 states 'Update' but fails to specify critical mutation semantics: whether this is a partial update (PATCH) or full replacement (PUT), what happens to omitted fields, error behavior when the ID is invalid, or whether the operation is idempotent. This lack of transparency is risky for a mutating operation.

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

Conciseness3/5

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

At five words, the description is severely under-specified for a 9-parameter mutation tool lacking an output schema. While it avoids redundancy with the structured fields, it sacrifices necessary context regarding behavioral traits and usage constraints. The brevity here represents under-documentation rather than efficient conciseness.

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?

For a mutation tool with no annotations and no output schema, the description inadequately prepares the agent for invocation. It omits: error handling details (404 vs 400 scenarios), side effects (cascading updates to related records), return value structure, and partial vs full update semantics. The 100% schema coverage handles inputs, but behavioral completeness is absent.

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?

With 100% schema description coverage, the structured schema adequately documents all 9 parameters. The description adds minimal semantic value beyond the schema itself, merely implying the 'id' parameter through 'existing vehicle' without elaborating on business rules (e.g., whether changing customerId triggers ownership transfer logic). Baseline 3 is appropriate given the schema's completeness.

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

Purpose3/5

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

The description uses a specific verb ('Update') and resource ('vehicle'), clearly indicating this is a mutation operation on existing records (distinguishing it from create_vehicle). However, 'information' is vague regarding scope, and it fails to differentiate from sibling update tools like update_customer or update_order, leaving the agent to infer the resource context solely from the name.

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 prefer this over alternatives (e.g., whether to use this versus create_vehicle for new entries), nor are prerequisites mentioned (such as requiring the vehicle to exist). The phrase 'existing vehicle' implies usage constraints but does not explicitly state them.

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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