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Another language

another_language
Destructive

Make one finished video again in another language, into a new video beside it, as the app's Another language does: a UGC video with its own script and presenter, a product video with its voiceover said again over the same picture. This spends the team's credits: the price get_video or get_product_video lists in after_steps as another_language, or its voiced price for a voiced language, refunded if it fails. Only in a language that after_steps lists for it. Answers an id at once: call get_video with it, or get_product_video for a product video's, about once a minute until its status is ready or failed.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "id": "<id>",
      "language": "<language>",
      "credits": "<credits>",
      "idempotency_key": "<idempotency_key>"
    },
    "name": "another_language"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYesThe id of a finished video, from make_video, list_videos or make_product_video.
partNoWhich of its videos, as get_video names it: v1, the default, v2 and on.
creditsYesThe credits after_steps lists for this language, its voiced price for a voiced language; a different figure is refused.
languageYesThe language to make it in, one after_steps lists.
idempotency_keyYesAny string unique to this video. Calling again with the same key and the same arguments answers as the first call did and spends nothing more.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / language / enum
      Previous value: -[
      -  "en-us",
      -  "ar-eg",
      -  "ar-ae",
      -  "ar-lb",
      -  "ar",
      -  "ar-ma",
      -  "cs",
      -  "da",
      -  "nl-be",
      -  "nl",
      -  "en-au",
      -  "en-gb",
      -  "fi",
      -  "fr-ca",
      -  "fr",
      -  "de-at",
      -  "de",
      -  "de-ch",
      -  "id",
      -  "it",
      -  "no",
      -  "pl",
      -  "pt-br",
      -  "pt",
      -  "ro",
      -  "es-ar",
      -  "es-419",
      -  "es-mx",
      -  "es",
      -  "sv",
      -  "tr"
      -]New value: +[
      +  "en-us",
      +  "ar-eg",
      +  "ar-ae",
      +  "ar-lb",
      +  "ar",
      +  "ar-ma",
      +  "cs",
      +  "da",
      +  "nl-be",
      +  "nl",
      +  "en-au",
      +  "en-gb",
      +  "fi",
      +  "fr-ca",
      +  "fr",
      +  "de-at",
      +  "de",
      +  "de-ch",
      +  "hu",
      +  "id",
      +  "it",
      +  "ja",
      +  "no",
      +  "pl",
      +  "pt-br",
      +  "pt",
      +  "ro",
      +  "es-ar",
      +  "es-cl",
      +  "es-co",
      +  "es-419",
      +  "es-mx",
      +  "es",
      +  "sv",
      +  "tr"
      +]
  2. Changed1 schema field changed
    • changedInput schema / properties / id / description
      Previous value: -"The id of a finished video, from make_video or list_videos."New value: +"The id of a finished video, from make_video, list_videos or make_product_video."
  3. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Annotations only say it is destructive, non-idempotent, and open-world; the description adds the materially useful facts an agent cannot get from those flags — it spends team credits, the price is the one after_steps lists (voiced price for a voiced language), a mismatched figure is refused, and credits are refunded if it fails. It also discloses the asynchronous job pattern and the polling interval, which is exactly the behavioral context the hints do not carry.

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?

Four sentences, front-loaded with the action and the two variant behaviors before cost and follow-up. Some phrasing is compressed to the point of awkwardness ('Answers an id at once'), but no sentence is filler — each introduces pricing, eligibility, or the polling loop.

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?

With no output schema, the description correctly takes on the return contract (an id plus how to poll it) and covers cost, refund, and language eligibility for a credit-spending mutation. The only soft spot is that 'part' — which sub-video is transformed — is never touched on, leaving the agent to rely on the schema alone.

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 coverage is 100%, so the baseline is 3, but the description adds real meaning: credits must equal the after_steps figure (a different number is refused) and language must be one after_steps offers, both cross-tool constraints the enum and integer schema cannot express. The polling sentence also tells the agent what the returned id is for, though 'part' is left entirely to the 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?

States a specific verb and resource ('make one finished video again in another language, into a new video beside it') and immediately distinguishes the two output modes: a UGC video gets its own script and presenter, a product video keeps its picture and re-records the voiceover. That is enough for an agent to separate it from make_video, change_video, make_longer, or other_sizes without opening any 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?

Gives a hard precondition ('Only in a language that after_steps lists for it') and clear next-step guidance: the call answers an id at once, then poll get_video (or get_product_video) about once a minute until status is ready or failed. It does not explicitly compare itself to sibling tools that also transform an existing video, so the when-not side is inferred rather than stated.

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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