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TTS 작업 접수

tts_jobs_create

Create an asynchronous Korean narration job with one of 17 voices. 17개 한국어 내레이션 목소리 중 하나로 비동기 TTS 작업을 접수합니다. text는 최대 800자이며 접수 성공 시 과금되고 이후 취소해도 환불되지 않습니다. [100자당 10포인트]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYes합성할 한국어 텍스트 (최대 800자)
voice_idYes지원 voice_id

TDQS

A4.3/5.0
Behavior5/5

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

Annotations only indicate readOnly=false, idempotent=false, and destructive=false; the description adds materially important behavior: the job is asynchronous, charges on successful submission, and is non-refundable even if canceled later. This is valuable beyond the structured annotations and does not contradict them.

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 short and front-loads the core purpose before key constraints. The English and Korean sentences are near-duplicates, which adds a little redundancy, but the combined length is still compact and scannable.

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?

For a two-parameter creation tool, the description covers purpose, async behavior, limits, and cost consequences. It does not describe the return value or how to retrieve job results, but sibling tools (tts_jobs_status, tts_jobs_result) fill that gap, and no output schema exists to require it.

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 coverage is 100%, and the description largely restates what the schema already provides (max 800 chars, voice_id enum of 17 values). It adds billing context but does not deepen parameter meaning such as voice characteristics or text format, so the baseline 3 is appropriate.

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 verb and resource: 'Create an asynchronous Korean narration job.' It also states the choice of 17 voices and the asynchronous nature, which distinguishes it from sibling tools like tts_jobs_status, tts_jobs_cancel, and tts_jobs_result.

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 makes the intended use clear: Korean narration TTS with one of 17 voices and a 800-character limit. It does not explicitly name alternatives or exclusion criteria, but the async creation context is strong enough to guide an agent away from status/cancel/result tools.

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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TDQS

A3.6/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose, including the watermark pair: draw_watermark_image is visible text while set_watermark embeds an invisible code. The TTS job lifecycle tools are also cleanly separated by action and output type.

Naming Consistency3/5

The set mixes conventions: conversion tools use input_to_output, watermark tools use verb_noun, TTS jobs use a tts_jobs_ prefix, and stt is a bare acronym. The names are readable but do not follow one predictable pattern.

Tool Count3/5

At 19 tools, the server sits in the borderline 16-25 range and spans document conversion, image processing, watermarking, audio/video, and async TTS. Most tools earn their place, but the overall surface feels somewhat heavy for a single conversion-focused server.

Completeness4/5

The server covers its core domains well: document conversions, watermarking with both visible and invisible methods, PDF operations, and a full async TTS workflow. Minor gaps exist, such as missing image-to-PDF or Excel-to-JSON inverse conversions, but agents can generally complete workflows without dead ends.