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by app.apick

동영상 미리보기 이미지 추출

extract_video_thumbnail
Read-only

Extract preview thumbnail images from a video at regular intervals and return them as a ZIP file. 동영상에서 일정 구간마다 미리보기 이미지를 추출해 ZIP 파일로 반환합니다. [호출당 10포인트]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNo추출할 이미지 개수 (범위: 0 ~ 200, 기본값 100)
widthNo이미지 가로 길이 (범위: 100 ~ 2000, 기본값 480). 세로 길이는 가로 비율에 따라 자동 계산
video_urlYes다운로드 가능한 https URL (허용 형식: video/mp4, video/quicktime, video/x-msvideo, video/webm, video/x-matroska) (최대 200MB)

TDQS

A3.8/5.0
Behavior3/5

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

Annotations declare readOnlyHint=true, and the description aligns with that by describing a non-mutating operation. It adds behavioral context about regular interval extraction and ZIP return format, plus a point cost, but does not detail error handling or processing limits beyond the schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, with two sentences (English and Korean mirroring) plus a point cost, all relevant to the tool's function. It front-loads the core action and earns its length.

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?

Given the schema covers parameters and the description explains the output as a ZIP file, the tool is adequately characterized. No output schema exists, but the description's mention of ZIP return covers the essential output. Minor gaps like processing time are not critical.

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 schema has rich descriptions for all three parameters (count range, width range, video_url constraints), so the description doesn't need to add parameter semantics. Baseline 3 applies.

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 a specific verb-resource pair: 'Extract preview thumbnail images from a video at regular intervals and return them as a ZIP file.' This distinguishes from siblings like video_to_mp3 or download_youtube_video by focusing on thumbnail extraction.

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 provides clear context for when to use the tool (extract preview thumbnails) but does not mention alternatives or exclusions, nor does it give guidance on choosing between this and similar video tools. The point cost is noted but not framed as usage guidance.

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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