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Convertir definiciones de herramientas

tool-definition-convert
Read-onlyIdempotent

Convierte una definición de herramienta entre los formatos MCP, OpenAI (function calling) y Anthropic (tool use). Cuándo: hay que leer, convertir o revisar una descripción de agente, una lista de herramientas, un documento OpenAPI o un recibo según el formato de su protocolo. No para: traducir la descripción completa de un agente o API entre A2A, MCP, OpenAPI y x402 (onda-traducir). Efectos secundarios: ninguno (solo lectura, sin red, sin estado guardado). Determinista: la misma entrada da la misma salida. Límites: entrada JSON de hasta 64 KB, 1 s por llamada, resultado de hasta 1 MB.

EN: Converts a tool definition (name, description, JSON Schema parameters) between MCP (inputSchema), OpenAI function-calling (function.parameters) and Anthropic tool-use (input_schema) shapes, validating the name. When: an agent description, tool list, OpenAPI document or receipt has to be read, converted or checked against its protocol format. [EN completo / full EN: inputSchema.description]

Input Schema

NameRequiredDescriptionDefault
toYesTarget format (required; one of: mcp, openai, anthropic).
toolYesTool definition in any of the three formats (object; required).

Output Schema

NameRequiredDescriptionDefault
toolNo
warningsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / to / examples
      Added value: +[
      +  "anthropic"
      +]
    • addedInput schema / properties / tool / examples
      Added value: +[
      +  {
      +    "function": {
      +      "name": "f",
      +      "parameters": {
      +        "type": "object"
      +      }
      +    },
      +    "type": "function"
      +  }
      +]
  2. Changed1 schema field changed
    • addedInput schema / description
      Added value: +"EN: Converts a tool definition (name, description, JSON Schema parameters) between MCP (inputSchema), OpenAI function-calling (function.parameters) and Anthropic tool-use (input_schema) shapes, validating the name. When: an agent description, tool list, OpenAPI document or receipt has to be read, converted or checked against its protocol format. Not for: translating a whole agent or API description between A2A, MCP, OpenAPI and x402 (onda-traducir). Side effects: none (read-only, no network access, no stored state). Deterministic: the same input gives the same output. Limits: JSON input up to 64 KB, 1 s per call, result up to 1 MB."
  3. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, closed-world and non-destructive, but the description adds value beyond them: hard limits (64 KB input, 1 s per call, 1 MB result), no network, no stored state, determinism, and that the name is validated. It does not say what happens when validation fails or the limits are exceeded, which is the main remaining gap.

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

Conciseness4/5

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

Front-loaded with the core action, then When/Not-for/Side effects/Determinism/Limits in a scannable order. Slightly heavy because the Spanish and English text largely duplicate each other, but the content is dense and each line carries signal.

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

Completeness5/5

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

For a 2-parameter conversion tool with an output schema (so return values needn't be described) and full annotation coverage, the description covers purpose, routing, safety, determinism and resource limits. Nothing an agent needs before calling it is missing.

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?

Schema coverage is 100% and both parameters are documented, so the baseline is 3. The description adds meaning on top by clarifying what 'tool' actually contains (name, description, JSON Schema parameters) and that 'to' selects among the three protocol shapes, which helps the agent construct the nested object correctly.

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?

States a specific verb+resource (convert a tool definition) and enumerates the three exact target shapes with their field names (MCP inputSchema, OpenAI function.parameters, Anthropic input_schema), plus the extra behavior of validating the name. It also explicitly separates itself from onda-traducir, so an agent can route without opening either schema.

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

Usage Guidelines5/5

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

Gives an explicit 'When:' list of triggering situations (agent description, tool list, OpenAPI document, receipt needing reading/conversion/checking) and an explicit 'No para:' exclusion naming the sibling onda-traducir and the reason (whole agent/API description across A2A/MCP/OpenAPI/x402). No inference required.

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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