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음성 변조

voice_change
Read-only

Modulate the voice in a video or audio file to a lower or higher pitch. 동영상 또는 오디오 파일의 음성을 저음 또는 고음으로 변조합니다. MP3, WAV 등 오디오와 MP4, MOV 등 동영상 포맷을 지원하며, 변조된 파일을 반환합니다. [호출당 10포인트]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYes변조음 타입 (1: 저음, 2: 고음)
media_urlYes다운로드 가능한 https URL (허용 형식: audio/mpeg, audio/mp3, audio/wav, audio/x-wav, audio/mp4, audio/aac, audio/ogg, video/mp4, video/quicktime, video/x-msvideo, video/x-matroska, video/webm) (최대 200MB)

TDQS

A4.1/5.0
Behavior4/5

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

The description adds the cost per call ('[호출당 10포인트]') and confirms the tool returns a modulated file, complementing the readOnlyHint annotation. This provides useful behavioral context beyond the annotation, which already signals safety.

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 bilingual, adding length but remaining efficient. Every sentence provides value: pitch modulation, supported formats, return value, and cost. No unnecessary filler.

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 clarifies that a modulated file is returned and lists supported input formats. For a simple two-parameter tool, this is adequate, though it does not specify the output format precisely.

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?

The input schema already describes both parameters (type and media_url) with 100% coverage. The description mentions audio/video formats but does not add new semantic detail beyond the schema, such as the meaning of type values 1 and 2.

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 tool modulates voice pitch in audio/video files, specifying 'lower or higher pitch'. This defines the function precisely and distinguishes it from sibling tools like stt/tts, which handle speech recognition and synthesis.

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 provides clear context of the tool's function and supported formats, implying when to use it. It does not mention explicit exclusions or alternatives, but given the distinct sibling set, such guidance is not essential.

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.