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ConsignCloud MCP Server

by modellers

get_account_stats

Retrieve account statistics including balance, items, and sales data for consignment business management and analytics.

Instructions

Get statistics for a specific account (balance, items, sales)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesAccount ID

Implementation Reference

  • Input schema for get_account_stats tool requiring account ID
    {
      name: 'get_account_stats',
      description: 'Get statistics for a specific account (balance, items, sales)',
      inputSchema: {
        type: 'object',
        properties: {
          id: { type: 'string', description: 'Account ID' },
        },
        required: ['id'],
      },
    },
  • src/server.ts:418-420 (registration)
    Registration of all tools including get_account_stats via listTools handler using createTools()
    server.setRequestHandler(ListToolsRequestSchema, async () => ({
      tools,
    }));
  • MCP tool handler for get_account_stats that delegates to client.getAccountStats(id)
    case 'get_account_stats':
      return { content: [{ type: 'text', text: JSON.stringify(await client.getAccountStats((args as any).id), null, 2) }] };
  • Client method implementation that calls the ConsignCloud API endpoint /accounts/{id}/stats to fetch account statistics
    async getAccountStats(id: string): Promise<any> {
      const response = await this.client.get(`/accounts/${id}/stats`);
      return response.data;
    }
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 tool retrieves statistics, implying a read-only operation, but doesn't cover aspects like authentication requirements, rate limits, error handling, or the format of returned data. This leaves significant gaps for a tool with no annotation support.

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 front-loads the core purpose without unnecessary details. Every word contributes to understanding the tool's function, making it appropriately 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 lack of annotations and output schema, the description is incomplete for a tool that likely returns complex statistical data. It mentions what statistics are retrieved but doesn't explain the return format, potential limitations, or how the data is structured, which is insufficient for full contextual understanding.

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 single parameter 'id' documented as 'Account ID'. The description adds no additional meaning beyond this, such as format examples or constraints. According to the rules, with high schema coverage, the baseline is 3 when no param info is added in the description.

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 tool's purpose with a specific verb ('Get') and resource ('statistics for a specific account'), and it enumerates the types of statistics (balance, items, sales). However, it doesn't explicitly differentiate from sibling tools like 'get_account' or 'calculate_account_metrics', which keeps it from a perfect score.

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. With siblings like 'get_account', 'calculate_account_metrics', and 'get_sales_trends', there's no indication of context, prerequisites, or exclusions for selecting this tool over others.

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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