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by app.apick

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 behavioral context beyond annotations by specifying supported formats (MP3, WAV, MP4, MOV), that it returns the modulated file, and the cost per call. It doesn't contradict the readOnlyHint and provides useful operational details.

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 and front-loaded with the primary purpose. However, the bilingual repetition duplicates the same information in Korean and English, which adds length without adding semantic value for an AI agent.

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 simple two-parameter tool with full schema descriptions, the description covers the core purpose, supported inputs, output behavior, and cost. It lacks edge-case details like failure modes or processing time, but is reasonably complete for its complexity.

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 description coverage is 100%, so the schema already explains both parameters in detail. The description reinforces the meaning (lower/higher pitch) but adds no new parameter-specific semantics beyond 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?

The description clearly states the verb 'Modulate' with a specific resource (voice in video/audio file) and the specific outcome (lower or higher pitch). It distinguishes itself from sibling tools like video_to_mp3 or extract_video_thumbnail by focusing on pitch modulation.

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 gives clear context for when to use the tool: to modulate voice pitch in audio/video files. It doesn't explicitly mention alternatives or when-not-to-use, but the purpose is unambiguous and differentiates from siblings without needing exclusions.

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
Disambiguation4/5

Most tools have clearly distinct purposes; even within families like identi_card1-5 vs identi_card_image1-5, the text-input vs image-input distinction is clear. However, the sheer number of tools and some near-synonyms (e.g., ocr_identi1 vs identi_card_image1) could cause occasional misselection, but descriptions mitigate this.

Naming Consistency3/5

Naming follows a loose verb-first pattern (check_, crawl_, download_, draw_, etc.) but includes significant deviations: bare nouns (bank_code, location, whois), numbered variants (identi_card1, identi_card_image1), and mixed prefixes (ocr_, identity_, etc.). The inconsistency is noticeable but still readable and predictable within functional clusters.

Tool Count3/5

80 tools is far above the typical 3-15, but the server is a broad API aggregator covering many independent domains (banking, ID verification, media conversion, search, LLM, etc.), so the high count is somewhat justified. Still, the sheer number makes the toolkit feel unwieldy and hard to navigate, placing it at the high end of acceptable.

Completeness4/5

Within its stated purpose as a general-purpose utility API, the toolset covers a wide array of common task families: identity document verification (text and image), OCR field extraction, media conversion, web/search, domain/IP lookup, and LLM chat. Most operations have both get and act variants (e.g., set/get watermark, parcel_tracking/auto), with few obvious dead ends for typical use cases.

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