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Extraer datos de INE

extraer_ine

Extract personal data from INE/IFE voting credential photos. Provide front (and optional back) image paths to retrieve name, CURP, address, and more.

Instructions

Extrae los datos de una credencial para votar INE/IFE a partir de fotos guardadas en esta computadora: nombre, apellidos, CURP, clave de elector, fecha de nacimiento, sexo, domicilio, sección, vigencia y más. front_path es la ruta del frente (JPEG, PNG o WebP, máximo 10 MB); back_path (reverso) es opcional. Consume 1 token de tu saldo; si la imagen es ilegible (LOW_IMAGE_QUALITY) o falla la extracción, el token se reembolsa. Los datos personales extraídos quedan en esta conversación.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
back_pathNoRuta local de la foto del reverso (opcional)
front_pathYesRuta local de la foto del frente de la INE

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=false, openWorldHint=true, idempotentHint=false. The description adds important non-schema behavior: it consumes 1 token, refunds on LOW_IMAGE_QUALITY or extraction failure, and keeps personal data in the conversation. It does not cover auth or idempotency, but the added cost/refund/privacy context is strong.

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?

A single dense paragraph that front-loads what is extracted, then input details, cost/refund, and privacy. Every sentence carries necessary information; no filler.

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

Completeness4/5

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

For a 2-parameter extraction tool with no output schema, the description is nearly complete: it lists return fields, input formats, cost, refund policy, and data handling. It could be slightly richer about output structure (e.g., JSON shape) or error modes, but is adequate for correct invocation.

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 already documents both parameters, but the description adds accepted image formats (JPEG, PNG, WebP), a 10 MB size cap, and clarifies back_path is optional—meaningful constraints beyond the schema text.

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 and resource ('Extrae los datos de una credencial para votar INE/IFE') and enumerates the extracted fields, making it unmistakable versus siblings like consultar_saldo or crear_enlace_captura.

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

Usage Guidelines4/5

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

Provides clear context (photos stored on this computer, optional back_path) and operational constraints (file types, size limit), but does not explicitly state when not to use it or name alternatives—though none of the siblings overlap.

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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