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translate_subtitles

Translate episode subtitles into a target language and enable bilingual display. Asynchronous processing charges per use, no prepayment required.

Instructions

把某集字幕翻译成第二语言并开启双语。后台异步,按用量后付不欠费。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langYes目标语言(如 en/ja/ko)
episode_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.57

TDQS

B3.4/5.0
Behavior3/5

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

No annotations are provided, so the description must carry the behavioral disclosure burden. It explicitly mentions 'background async' and 'pay per usage, no arrears', which are useful operational traits. However, it does not disclose requirements (e.g., does the episode need existing subtitles?), side effects (does it overwrite original subtitles?), or how to retrieve results after the async operation, leaving significant behavioral gaps for a mutation tool.

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?

The description is concise, with the core purpose stated first and behavioral notes in a second sentence. There is no redundant or filler content. It is well-structured for quick scanning, though it omits some critical details that would make it more complete.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the absence of output schema and annotations, the description is incomplete for an agent to use correctly. It does not explain what 'bilingual' means in output format, how to check the status of an async operation, or whether the translation replaces or adds subtitles. For a tool with only two parameters, it lacks essential operational context, making it difficult to know the full call lifecycle.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 50% (lang has a description but episode_id does not). The tool description does not clarify the meaning of episode_id beyond the vague '某集' (a certain episode), nor does it add detail about the lang parameter beyond what the schema already gives. It fails to compensate for the undocumented episode_id, leaving an agent to guess its format or constraints.

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 clearly states the action (translate subtitles), the resource (a specific episode's subtitles), and the outcome (enable bilingual display). It uses a specific verb 'translate' and names the target resource, making it unambiguous and distinct from the many generation tools in the sibling list. There is no confusion about what this tool does.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies a use case (translating episode subtitles into a second language) but does not explicitly state when to use this tool over alternatives or provide exclusions. It mentions asynchronous execution and billing but gives no comparative guidance against other tools, though no direct sibling performs a similar function. The lack of explicit 'use when' or 'instead of' makes it adequate but not strongly instructive.

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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