set_watermarkEmbed an invisible watermark code into an image. 원본 이미지에 보이지 않는 워터마크 코드를 삽입한 PNG 이미지를 반환합니다. 이미지가 일부 변형되어도 높은 확률로 워터마크를 확인할 수 있습니다. PNG, JPEG 등 일반 이미지 포맷을 지원합니다. [호출당 10포인트]
| Name | Required | Description | Default |
|---|---|---|---|
| code | Yes | 삽입할 워터마크 코드 (1 ~ 21,767,823,359 사이의 숫자) | |
| image_url | Yes | 다운로드 가능한 https URL (허용 형식: image/png, image/jpeg, image/webp, image/bmp) (최대 50MB) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds useful behavioral traits beyond the annotations: it returns a PNG, supports common formats, and claims robustness to image modifications. It also discloses the per-call cost. The readOnlyHint annotation is not contradicted since the tool processes input and returns a new image without altering the source. The description enriches the agent's understanding of what to expect.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is fairly concise but redundant: the English and Korean sentences convey nearly identical information about embedding the code and returning a PNG. The cost note is a useful addition, but the repetition adds noise. It is not egregiously long, but it could be tighter.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with only two parameters and a fully described schema, the description covers the core functionality, return format, supported input formats, robustness, and cost. It does not mention error cases or prerequisites, but these are not critical given the simple scope. The absence of an output schema is mitigated by the explicit statement that a PNG is returned. Overall, it is sufficiently complete for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for both parameters, so the baseline is 3. The description does not add extra meaning about the parameters; it merely repeats that a 'code' is embedded and mentions format support already present in the schema. It provides no additional constraints or examples beyond what the schema already documents.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Embed an invisible watermark code') and a clear resource (an image), and mentions the output is a PNG. It distinguishes from sibling tools like get_watermark (which would retrieve) and draw_watermark_image (likely visible), though not explicitly. The purpose is unambiguous and the verb is specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives like draw_watermark_image or get_watermark. The description does not mention prerequisites, exclusions, or when not to use it. The only context is the cost note, which is not usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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 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.
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.
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.