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Translate text

translate_text

Translate supplied text into one of Poly-Glot's 38 supported languages while aiming to preserve meaning, names, formatting, code, and URLs. Use for translation rather than cultural adaptation; use localize_text when audience, tone, or regional conventions must change. Specify required targetLanguage (language name or code, e.g. 'es'); set sourceLanguage to 'auto' to detect the source automatically. Returns JSON containing translated text, targetLanguage, provider, and model; quality can vary with idiom and context. Requires an active trial or Pro; text is processed by the configured translation provider.

Input Schema

NameRequiredDescriptionDefault
textYesNonempty original text to translate, including any formatting to preserve.
sourceLanguageNoOriginal language name or code, such as 'en' or 'English'; 'auto' (default) asks the provider to detect it.auto
targetLanguageYesRequired desired output language name or code among the 38 supported, e.g. 'Spanish' or 'es'.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • addedInput schema / properties / sourceLanguage / description
      Added value: +"Original language name or code, such as 'en' or 'English'; 'auto' (default) asks the provider to detect it."
    • addedInput schema / properties / targetLanguage / description
      Added value: +"Required desired output language name or code among the 38 supported, e.g. 'Spanish' or 'es'."
    • addedInput schema / properties / text / description
      Added value: +"Nonempty original text to translate, including any formatting to preserve."
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses the subscription requirement (active trial or Pro), that text is sent to an external provider, the return payload shape, and that quality varies with idiom and context. It does not cover rate limits or error/failure behavior, so it falls short of a 5.

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 verb and resource, and each sentence adds distinct value (routing, params, return, constraints). The final sentence bundling return shape, quality caveat, and auth requirements is slightly dense but still efficient.

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?

There is no output schema, and the description compensates by naming the returned fields (translated text, targetLanguage, provider, model). Combined with the auth and privacy notes and the routing to localize_text, an agent has everything needed to select and invoke it correctly.

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 all three parameters are already documented in the schema, establishing a baseline of 3. The description restates targetLanguage and sourceLanguage semantics ('es', 'auto') without adding format or constraint detail beyond the schema, so it does not exceed the baseline.

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 ('Translate supplied text') with explicit scope (38 supported languages) and names the sibling it is not, localize_text. An agent can distinguish this from localize_text 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 routing rule: use for translation rather than cultural adaptation, and use localize_text when audience, tone, or regional conventions must change. It also clarifies the sourceLanguage='auto' detection path, leaving nothing to inference.

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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