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by io.github.Nativ-Technologies
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translate_batch

Translate multiple texts to a single target language.

Use for lists of strings, UI labels, i18n files, subtitle cues, and
voiceover segments. Prefer one batch over separate translate calls.
Texts are translated together using the team's TM and style guides.
A failed or incomplete batch is a tool error; do not synthesize its output.

Args:
    texts: List of texts to translate.
    target_language: Full target language name (e.g. "French").
    target_language_code: Optional ISO language code.
    source_language: Source language name. Defaults to English.
    source_language_code: Source language code. Defaults to "en".
    context: Optional context to guide all translations.
    formality: Tone override for all translations.

Input Schema

NameRequiredDescriptionDefault
textsYes
contextNo
formalityNo
source_languageNoEnglish
target_languageYes
source_language_codeNoen
target_language_codeNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
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 real work: it discloses that the team's translation memory and style guides are applied, that a failed or incomplete batch surfaces as a tool error, and that the agent must not synthesize missing output. It leaves out operational limits such as maximum batch size or output ordering guarantees.

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?

It is front-loaded with the core action, then usage, then parameters, with no filler sentences. The Args block partly duplicates schema titles, but that is justified given 0% schema description coverage.

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?

An output schema exists, so return-format explanation is unnecessary, and the description covers purpose, batching semantics, failure behavior, and all seven parameters. It falls short only on formality value vocabulary and any batch size ceiling for a tool that could be called with very large input.

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 0%, so the Args block is the only parameter documentation and it does cover all seven parameters with defaults and an example value ('French'). However, several entries are near-tautological (context: 'Optional context to guide all translations', formality: 'Tone override for all translations') and give no valid values, even though a get_language_formality_options sibling exists that presumably defines them.

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 first line gives a specific verb and resource with scope: translate multiple texts into a single target language. The line 'Prefer one batch over separate translate calls' implicitly contrasts it with the singular translate sibling, so an agent can distinguish the two without opening a schema.

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?

It names concrete use cases (lists of strings, UI labels, i18n files, subtitle cues, voiceover segments) and states the batch-over-individual-calls preference explicitly. What is missing is a when-not clause, for example routing dialogue content to translate_dialogue or subtitle files to localize_subtitle_file.

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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