Skip to main content
Glama

local_translate

Translate text or file content with a local language model, preserving original formatting and saving Claude's context for large files.

Instructions

PREFIERE esta tool en vez de leer el archivo con Read cuando el archivo es grande (>200 líneas / >10 KB) y solo necesitas la traducción, no el contenido literal.

Traduce texto o el contenido de un archivo con un modelo local, sin gastar contexto de Claude.

Pasa 'path' para leer el archivo server-side (el original no entra al contexto de Claude) o
'text'. Conserva el formato del original y devuelve SOLO la traducción. Enruta al modelo
mecánico (corto) o al de contexto largo (largo) automáticamente.

Args:
    target_lang: Idioma destino (p. ej. 'español', 'inglés', 'francés').
    text: Texto a traducir (usa esto o 'path').
    path: Ruta a un archivo cuyo contenido se traduce (leído server-side).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNo
textNo
target_langYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description covers key behavioral traits: uses a local model, does not consume Claude context, preserves format, returns only translation, and auto-routes to short or long context model. Missing details like error handling or rate limits, but sufficient for a read-only translation tool.

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 front-loaded with a clear preference statement, structured in paragraphs and bullet-like args. It is informative yet concise, with no wasted words. Slight improvement possible in structuring the args section.

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?

Given the tool's complexity (translation, two input modes, auto-routing), the description is fairly complete. It covers purpose, usage, parameters, and behavioral aspects. Does not explain return values, but an output schema exists. Minor ambiguity about simultaneous use of text and path.

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 description coverage is 0%, but the description adds meaning: target_lang is required, path reads server-side to keep original out of Claude context, text is direct input. Examples are given. It could be clearer that exactly one of text or path should be used.

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 the tool translates text or file content using a local model. It specifies when to prefer it over alternatives (large files >200 lines or >10 KB) and distinguishes from the sibling tool 'Read'. The verb 'traduce' and resource 'texto/contenido de archivo' are specific.

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?

The description explicitly says when to use this tool instead of Read (large files needing translation) and explains the two input methods (path or text) and that target_lang is required. It does not explicitly state when not to use it, but the context is clear.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/ZahiriNatZuke/local-delegate'

If you have feedback or need assistance with the MCP directory API, please join our Discord server