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Analizar imagen

analizar_imagen

Transcribe text from local images, generate optional image descriptions, and return results as Markdown, plain text, or JSON. Save output files or copy content directly.

Instructions

Transcribe el texto de una imagen, genera una descripción breve (opcional) y devuelve el contenido en Markdown, texto plano o JSON. Puede guardar el resultado como archivo.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rutaYesRuta local de la imagen a analizar.
idiomaNoCódigo de idioma del texto (por defecto "eng").
formatoNoFormato de salida del contenido generado (por defecto "md").
guardarNoEscribir el resultado como archivo dentro de "carpetaSalida".
carpetaSalidaNoDirectorio donde guardar el archivo si "guardar" es true.
conDescripcionNoGenerar una descripción breve (IA si hay API key, si no, local).
incluirBloquesNoIncluir la transcripción por bloques (por defecto false).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.1/5.0
Behavior3/5

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

With no annotations, the burden falls on the description, and it does surface the main side effect: 'Puede guardar el resultado como archivo.' However, it omits specifics such as file overwrite behavior, the API-key dependency behind the AI description path, and what happens to the output when guardar is false.

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?

Two sentences with no filler, and the core operation is front-loaded in the first clause. The structure is slightly list-like and the second sentence partly restates what the guardar parameter already implies, but overall it is efficient and scannable.

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?

For a 7-parameter tool with no annotations and no output schema, meaningful behaviors are absent: the per-block transcription option (incluirBloques), language handling (idioma), and the AI-vs-local description path are never mentioned. The description also fails to position the tool against the similarly named sibling transcribir_imagen, so an agent cannot fully scope when this tool is appropriate.

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?

Schema description coverage is 100%, so every parameter is already documented individually. The description loosely mirrors the schema (formato maps to 'Markdown, texto plano o JSON; guardar to 'guardar el resultado') but adds no meaning beyond it, so the baseline 3 applies.

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?

States the core action clearly: 'Transcribe el texto de una imagen' with an optional brief description and three output formats (Markdown, texto plano o JSON). The action, resource, and deliverable are specific, though it never distinguishes itself from the near-identically scoped sibling 'transcribir_imagen'.

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?

No guidance on when to use this tool versus its siblings. The description reads as a feature list and never states selection criteria, prerequisites, or exclusions, leaving an agent to guess whether analizar_imagen or transcribir_imagen is the right call.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.