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kshayk

AviBase MCP Server

by kshayk

get_bird_stats

Retrieve comprehensive statistics from the AviBase bird dataset including total records, species counts, taxonomic classifications, and conservation categories.

Instructions

Get comprehensive statistics about the bird dataset including total records, species count, families, orders, and conservation categories.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The primary handler function that executes the get_bird_stats tool logic. It fetches dataset statistics from the backend API endpoint '/stats' and returns a formatted markdown text response containing total records, species count, families, orders, extinct species, and IUCN categories.
      async handleGetBirdStats() {
        const response = await this.makeAPIRequest('/stats');
        
        return {
          content: [
            {
              type: 'text',
              text: `# Bird Dataset Statistics
    
    📊 **Dataset Overview:**
    - **Total Records:** ${response.data.totalRecords.toLocaleString()}
    - **Species:** ${response.data.totalSpecies.toLocaleString()}
    - **Families:** ${response.data.totalFamilies}
    - **Orders:** ${response.data.totalOrders}
    - **Extinct Species:** ${response.data.extinctSpecies}
    
    🚨 **IUCN Conservation Categories:** ${response.data.iucnCategories.join(', ')}
    
    This comprehensive dataset contains information about birds worldwide, including taxonomic classification, conservation status, geographic distribution, and historical data.`,
            },
          ],
        };
      }
  • mcp-server.js:71-79 (registration)
    Tool registration in the ListToolsRequestSchema handler, defining the tool name, description, and input schema (no parameters required).
    {
      name: 'get_bird_stats',
      description: 'Get comprehensive statistics about the bird dataset including total records, species count, families, orders, and conservation categories.',
      inputSchema: {
        type: 'object',
        properties: {},
        required: [],
      },
    },
  • Input schema definition for the get_bird_stats tool, specifying an empty object (no input parameters required).
    inputSchema: {
      type: 'object',
      properties: {},
      required: [],
    },
  • mcp-server.js:288-289 (registration)
    Dispatch case in the CallToolRequestSchema handler that routes tool calls named 'get_bird_stats' to the handleGetBirdStats method.
    case 'get_bird_stats':
      return await this.handleGetBirdStats();
Behavior3/5

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

With no annotations provided, the description carries full burden. It clearly indicates this is a read operation ('Get') and specifies what data is returned, but doesn't disclose behavioral aspects like performance characteristics, rate limits, authentication requirements, or whether the statistics are real-time or cached. The description adds value by specifying the scope of statistics but lacks operational context.

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, well-structured sentence that efficiently communicates the tool's purpose and output scope. Every word earns its place - 'comprehensive statistics' sets expectations, and the list of specific metrics provides complete information without redundancy or unnecessary elaboration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter tool with no output schema, the description adequately covers what statistics are returned. However, without annotations or output schema, it doesn't provide information about return format, data freshness, or error conditions. The description is complete for basic understanding but lacks operational details that would be helpful for an AI agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0 parameters and 100% schema description coverage, the baseline would be 4. The description appropriately doesn't discuss parameters since none exist, and instead focuses on what the tool returns. It adds semantic value by detailing the specific statistical categories included in the output.

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

Purpose5/5

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

The description clearly states the specific action ('Get comprehensive statistics') and resource ('bird dataset'), listing exactly what statistics are included (total records, species count, families, orders, conservation categories). It distinguishes this from siblings like get_birds_by_region or search_birds by focusing on aggregated dataset metrics rather than filtered queries.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for obtaining high-level dataset metrics, but doesn't explicitly state when to use this versus alternatives like custom_bird_query or get_bird_report. It provides context about what statistics are available but lacks explicit guidance on when this tool is preferred over other statistical or query tools.

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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