zeenie-ai Translation Skill
Three tools, several providers behind each. Pick the provider that fits the language pair rather than defaulting to one.
How It Works
Connect Translate, Transliterate and/or Detect Language to the
agent's input-tools handle. Each has a provider parameter, and the
credential for the chosen provider must be configured in the Credentials
modal.
The distinction that matters most
Translation changes the words. Transliteration changes the script.
| Input | Tool | Output |
|---|---|---|
hello |
translate_text → hi |
नमस्ते |
namaste |
transliterate_text → hi |
नमस्ते |
Both produce Devanagari, but only one changed the meaning. Getting this backwards is the most common misuse: if the user wants to read foreign text, they want translation; if they want to type their own language in its native script, or make a foreign name pronounceable, they want transliteration.
translate_text
| Field | Type | Required | Description |
|---|---|---|---|
| text | string | Yes | Text to translate |
| provider | enum | No | deepl, sarvam, openai |
| target_language | string | No | Blank uses the provider default |
| source_language | string | No | Blank auto-detects |
| translate_model | string | No | Blank uses the provider default |
| formality | string | No | Register, where the provider supports it |
| context | string | No | Disambiguating context — not itself translated |
| preserve_formatting | boolean | No | Keep line breaks and punctuation as-is |
| provider_options | object | No | Vendor-specific extras |
Returns translated_text and detected_source_language.
Choosing a provider
- deepl — best quality for European languages, and the only one that
reports exactly how many characters it billed. Language codes are uppercase
(
DE,EN-US,PT-BR). Preferprefer_more/prefer_lessfor formality overmore/less: the strict forms 400 on target languages that do not support the distinction. Does not transliterate or detect. - sarvam — Indian languages: 22 on
sarvam-translate:v1, 11 onmayura:v1. Codes are always-INsuffixed (hi-IN,ta-IN).formalitymaps to its register modes:formal,modern-colloquial,classic-colloquial,code-mixed. - openai — LLM-backed. Covers pairs the others do not, needs no extra credential if a chat key is already configured, and takes free-form context well. Slower, and billed as tokens rather than characters.
transliterate_text
| Field | Type | Required | Description |
|---|---|---|---|
| text | string | Yes | Text to convert |
| provider | enum | No | sarvam, openai |
| target_language | string | No | Language whose script to write in |
| source_language | string | No | Blank auto-detects |
| target_script | string | No | Script style, where the provider offers a choice |
| provider_options | object | No | Vendor-specific extras |
Returns transliterated_text. Sarvam's target_script values are roman,
fully-native and spoken-form-in-native — the last renders numbers and
abbreviations the way they would be spoken, which is what you want when the
output feeds text_to_speech.
detect_language
| Field | Type | Required | Description |
|---|---|---|---|
| text | string | Yes | Text to identify |
| provider | enum | No | sarvam, openai |
Returns language, script and — from providers that report it —
confidence. Use it before translating when the source is unknown, or to
route text by language.
When to Use
- The user asks for a translation, or pastes text in a language they cannot read
- Preparing text for
text_to_speech, which needs a target language - Routing or filtering content by language
When NOT to Use
- Translating an entire document — chunk it first; every provider caps input
- Detecting language from a single word; give it a sentence
- Transliteration when the user actually meant translation (see above)
Setup Requirements
One API key per provider you intend to use. The sarvam and openai keys are
the same ones their chat models use, so if those are configured these tools
work with no extra setup. DeepL needs its own key — free keys end in :fx and
are routed to the free host automatically.