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kaeris_translate

Translate UI strings into multiple languages with placeholder-safe output, QA warnings for dropped tokens or overflow, and optional back-translation verification.

Instructions

Translate a set of UI strings into one or more languages.

Format-aware and placeholder-safe: values like "Hello, {name}" keep their placeholders intact. Non-string values are passed through unchanged.

Includes Translation QA so you can trust the output: it flags translations that dropped a placeholder or that grew long enough to risk overflowing the UI. With verify=True it also back-translates each result into back_lang so you can check the meaning is right even in a language you can't read.

Args: strings: key → source-text pairs, e.g. {"greeting": "Hello", "save": "Save"}. target_languages: language codes from kaeris_list_languages, e.g. ["es", "fr", "ja"]. keep: optional list of terms to NEVER translate — kept verbatim in every language (brand/product names), e.g. ["KAERIS", "GitHub"]. context: one line about what the app IS, e.g. "a mobile bank for teenagers" or "a wildlife documentary app". The model uses it to pick the right sense of ambiguous strings — "Bank" becomes Ufer in the second and Bank in the first. You are reading the repo, so you know this: pass it. Max 300 chars. verify: back-translate each result into back_lang to confirm meaning (uses more tokens). back_lang: language for the verify back-translation (default "en"). tone: "formal" or "casual" to steer register; "" (default) is neutral. icu: True if values may contain ICU MessageFormat (plurals/select) so the model preserves the syntax instead of translating it. reuse: optional {lang: {key: previous_translation}} translation-memory map — strings that are unchanged from a prior run are reused verbatim server-side and only new/changed strings are actually translated. api_key: optional KAERIS key (else uses the free tier or KAERIS_API_KEY env). openrouter_key: optional OpenRouter key for Lifetime/BYOK.

Returns: { "translations": { "": { "": "", ... }, ... }, "placeholder_warnings": { "": { "": ["{name}", ...] } }, # if any placeholders were lost "overflow_warnings": { "": [ {"key","src","tr","pct"}, ... ] }, # if UI-overflow risk "back_translations": { "": { "": "" } }, # only if verify=True "failed_languages": [...] # present only if some languages could not be translated }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
icuNo
keepNo
toneNo
reuseNo
verifyNo
api_keyNo
contextNo
stringsYes
back_langNoen
openrouter_keyNo
target_languagesYes
Behavior5/5

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

With no annotations provided, the description carries the full burden and does so excellently. It discloses placeholder-safe handling, pass-through of non-strings, Translation QA with placeholder and overflow warnings, back-translation behavior, translation-memory reuse, and API key fallback logic. It even explains token cost for verify=True.

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?

Although lengthy, the description is meticulously structured: a concise opening, a brief feature-highlight paragraph, a linear Args breakdown with one parameter per line, and a clear Returns block. Every sentence adds necessary information and no words are wasted.

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 11 parameters, nested objects, no output schema, and no annotations, the description is remarkably complete. It explains all parameters, return fields, edge cases (failed_languages), and even provides a direct instruction to the agent ('You are reading the repo, so you know this: pass it.'). It leaves virtually no ambiguity.

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?

Schema description coverage is 0%, but the Arduino-style Args section provides thorough explanations for all 11 parameters, including types, examples, defaults, and nuanced semantics (e.g., what 'context' is for, how 'reuse' works, how 'icu' affects processing). This fully compensates for the sparse schema.

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 opens with a specific action and resource: 'Translate a set of UI strings into one or more languages.' It clearly distinguishes from sibling tools like kaeris_translate_file by specifying it operates on a set of key-value pairs rather than a file.

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 clearly indicates when to use this tool (when you have a set of UI strings) and even references kaeris_list_languages for valid language codes. However, it does not explicitly exclude alternatives like kaeris_translate_file or provide explicit when-not-to-use guidance, so it stops short of a 5.

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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