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get_user

Retrieve user profile information from WebSim's public API by providing a username to access details and manage user data.

Instructions

Get details for a specific WebSim user

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
userYesUsername

Implementation Reference

  • The handler function for the 'get_user' MCP tool. It validates the input using UserParamsSchema, fetches the user data using apiClient.getUser(user), and returns a structured response containing the JSON-formatted user data.
    handler: async (args) => {
      const { user } = UserParamsSchema.parse(args);
      const result = await apiClient.getUser(user);
      return {
        content: [{
          type: "text",
          text: JSON.stringify({
            success: true,
            data: result,
            message: `Successfully retrieved user ${user}`
          }, null, 2)
        }]
      };
    }
  • Input schema definition for the 'get_user' tool, specifying the required 'user' parameter as a string.
    inputSchema: {
      type: "object",
      properties: {
        user: {
          type: "string",
          description: "Username"
        }
      },
      required: ["user"]
    },
  • Zod validation schema used by the 'get_user' handler to parse and validate the input argument 'user'.
    const UserParamsSchema = z.object({
      user: z.string().describe('Username')
    });
  • Helper method in WebSimAPIClient that performs the HTTP request to fetch user details from the WebSim API endpoint.
    async getUser(user) {
      return this.makeRequest(`/api/v1/users/${user}`);
    }
  • server.js:474-501 (registration)
    Registration of the 'get_user' tool in the tools array, including name, description, input schema, and handler. This array is used by the MCP server request handlers for tool listing and execution.
    {
      name: "get_user",
      description: "Get details for a specific WebSim user",
      inputSchema: {
        type: "object",
        properties: {
          user: {
            type: "string",
            description: "Username"
          }
        },
        required: ["user"]
      },
      handler: async (args) => {
        const { user } = UserParamsSchema.parse(args);
        const result = await apiClient.getUser(user);
        return {
          content: [{
            type: "text",
            text: JSON.stringify({
              success: true,
              data: result,
              message: `Successfully retrieved user ${user}`
            }, null, 2)
          }]
        };
      }
    },
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 ('Get details') but does not cover critical aspects like whether this is a read-only operation, authentication requirements, rate limits, error handling, or the format of returned details. This leaves significant gaps for an agent to understand the tool's behavior.

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 is front-loaded and wastes no space, making it easy to parse quickly.

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 lack of annotations and output schema, the description is incomplete. It does not explain what 'details' are returned, how errors are handled, or any behavioral traits. For a tool that likely involves user data retrieval, more context on response structure and operational constraints is needed.

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?

The input schema has 100% description coverage, with the parameter 'user' documented as 'Username'. The description does not add any additional meaning beyond this, such as format examples or constraints. Since the schema already provides adequate documentation, the baseline score of 3 is appropriate.

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 verb ('Get') and resource ('WebSim user'), making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools like 'get_user_followers' or 'get_user_stats', which also retrieve user-related data but focus on different aspects.

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, such as 'search_users' for broader queries or 'get_user_followers' for social data. It lacks any context on prerequisites, exclusions, or specific scenarios where this tool is preferred.

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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