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local_delegate

Read-only

Delegates any text-to-text transformation to a local model as a fallback. Automatically divides long inputs to preserve entire content during translation, rewriting, or reformatting.

Instructions

Tool genérica de escape: delega una tarea texto->texto a un modelo local.

Úsala cuando ninguna tool específica encaje. Arma el prompt con guardrails y devuelve texto.

Con entradas largas parte el input por límites naturales (headers Markdown, párrafos),
aplica la MISMA tarea a cada trozo y concatena las salidas en orden. Eso es lo correcto
para transformar todo el texto (traducir, reescribir, reformatear) pero NO para tareas de
reducción sobre el conjunto (contar, elegir el máximo, un único resumen global): para esas
pasa `chunk='off'` o usa `local_summarize`.

Args:
    task: Instrucción de la tarea (una frase con formato de salida explícito).
    input: Contenido sobre el que operar.
    output_format: Formato exacto de salida esperado.
    model: Modelo a usar; uno de los ids configurados en el catálogo. Por defecto el mecánico.
    chunk: 'auto' (parte solo si el input es largo), 'on' (parte siempre que se pueda),
        'off' (una sola llamada; el input largo puede volver truncado).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskYes
chunkNoauto
inputYes
modelNo
output_formatYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Description reveals detailed behavioral traits: chunking strategy (splits by natural boundaries, applies same task, concatenates), and limitations for reduction tasks. Annotations provide readOnlyHint, and description adds non-contradictory, useful context.

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?

The description is well-structured with purpose first, then chunking explanation, then parameter list. Slightly verbose but every sentence adds value. Could be more concise by merging some lines.

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?

Given the tool's complexity (5 params, 3 required, no schema descriptions, has output schema but not explained), the description covers usage, chunking, parameter details, and alternatives completely. It is self-sufficient for correct invocation.

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

Parameters5/5

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

All five parameters are described in the description (task, input, output_format, model, chunk) with clear semantics and default behaviors. This fully compensates for the 0% schema description coverage.

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 it is a generic escape tool that delegates text-to-text tasks to a local model. It distinguishes itself from siblings by specifying 'úsala cuando ninguna tool específica encaje' (use when no specific tool fits) and contrasts with local_summarize.

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?

Explicit guidance on when to use ('cuando ninguna tool específica encaje') and when not to use (reduction tasks: use local_summarize or set chunk='off'). Also mentions alternatives like local_summarize.

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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