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AiAgency-Now

VoiceAI-MCP-VAVicky

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by AiAgency-Now

get_available_numbers

Retrieve purchasable phone numbers by filtering country code, type, and location for VoiceAI integrations.

Instructions

Get available phone numbers for purchase

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
country_codeNoCountry codeUS
number_typeNoNumber typelocal
search_patternNoSearch for numbers containing this pattern
localityNoLocality/city for local numbers

Implementation Reference

  • Handler logic for the 'get_available_numbers' tool. Constructs URL query parameters based on input arguments (country_code, number_type, search_pattern, locality) and sets the API endpoint to fetch available Twilio phone numbers.
    case 'get_available_numbers':
      const params = new URLSearchParams();
      if (args.country_code) params.append('code', args.country_code);
      if (args.number_type) params.append('type', args.number_type);
      if (args.search_pattern) params.append('search', args.search_pattern);
      if (args.locality) params.append('locality', args.locality);
      url = `${this.baseUrl}/twilio/numbers/available?${params.toString()}`;
      break;
  • index.js:343-357 (registration)
    Tool registration including name, description, and input schema definition for 'get_available_numbers' in the list of available tools returned by ListToolsRequestSchema.
    {
      name: 'get_available_numbers',
      description: 'Get available phone numbers for purchase',
      inputSchema: {
        type: 'object',
        properties: {
          country_code: { type: 'string', description: 'Country code', default: 'US' },
          number_type: { type: 'string', enum: ['local', 'tollfree', 'mobile'], description: 'Number type', default: 'local' },
          search_pattern: { type: 'string', description: 'Search for numbers containing this pattern' },
          locality: { type: 'string', description: 'Locality/city for local numbers' }
        },
        required: []
      }
    },
    {
  • Input schema definition for the 'get_available_numbers' tool, specifying properties for country_code, number_type, search_pattern, and locality.
      inputSchema: {
        type: 'object',
        properties: {
          country_code: { type: 'string', description: 'Country code', default: 'US' },
          number_type: { type: 'string', enum: ['local', 'tollfree', 'mobile'], description: 'Number type', default: 'local' },
          search_pattern: { type: 'string', description: 'Search for numbers containing this pattern' },
          locality: { type: 'string', description: 'Locality/city for local numbers' }
        },
        required: []
      }
    },
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 'for purchase', implying a read-only listing operation, but fails to detail critical behaviors like rate limits, authentication requirements, response format, pagination, or whether the results are real-time. For a tool with potential cost implications (purchase), this is a significant gap in transparency.

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 conveys the core purpose without unnecessary words. It is front-loaded with the essential action and resource, making it easy to parse quickly. Every part of the sentence earns its place by specifying the tool's function clearly.

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 tool's complexity (4 parameters, no annotations, no output schema, and sibling tools like 'buy_twilio_number'), the description is incomplete. It lacks details on behavioral traits (e.g., authentication, rate limits), usage context relative to siblings, and output expectations. For a tool involved in purchasing workflows, this leaves significant gaps for an AI agent to operate effectively.

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, providing clear documentation for all four parameters (country_code, number_type, search_pattern, locality). The description adds no additional parameter semantics beyond what the schema already states, such as explaining how search_pattern works or interactions between parameters. With high schema coverage, a baseline score of 3 is appropriate as the schema handles the heavy lifting.

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 ('Get') and resource ('available phone numbers for purchase'), making the tool's purpose immediately understandable. It distinguishes itself from sibling tools like 'get_twilio_numbers' by specifying 'for purchase', though it doesn't explicitly contrast with that sibling. The description avoids tautology by not merely restating the tool 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?

The description provides no guidance on when to use this tool versus alternatives like 'get_twilio_numbers' or 'buy_twilio_number'. It lacks context about prerequisites, such as whether authentication or account setup is required, and offers no explicit when-not-to-use scenarios or comparisons with sibling 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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