查看图片元信息：格式/宽高/颜色模式/是否透明/文件大小 + EXIF 摘要。免费(0 credit)。
处理前先调它看清图片尺寸与格式，再决定 resize/compress/crop 参数。
| Name | Required | Description | Default |
|---|---|---|---|
| file_id | No | 已上传到文件中转站的图片 ID（与 data_base64 二选一） | |
| data_base64 | No | 图片内容 base64（与 file_id 二选一） |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It adds useful behavioral context: the tool is free (0 credit) and lists the output contents (format/size/EXIF summary). However, it does not disclose behavior on invalid input, confirm it is read-only, or clarify that only a partial EXIF summary is returned rather than full EXIF data.
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 two sentences with zero waste. The first sentence front-loads the core purpose and cost; the second delivers actionable usage guidance. Every sentence earns its place.
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 simple read-only inspection tool with 100% schema coverage and no output schema, the description is nearly complete: it states what fields are returned, that it is free, and when to call it. The main gap is not clarifying the relationship to the img_exif sibling tool, which could leave the agent unsure which to invoke for EXIF needs.
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 description coverage is 100% — both file_id and data_base64 have clear descriptions including the mutual-exclusivity rule ('二选一'). Since the schema does the heavy lifting and the tool description adds no extra parameter semantics, the baseline score of 3 applies.
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 uses a specific verb (查看/view) with a clear resource (图片元信息/image metadata) and enumerates exact fields returned (format, dimensions, color mode, transparency, file size, EXIF summary). However, it does not differentiate from the sibling tool img_exif, which likely overlaps on the EXIF portion, so it falls short of a full 5.
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?
The second sentence gives explicit context: 'Call it before processing to see image dimensions and format, then decide resize/compress/crop parameters.' This clearly communicates when to use the tool, but it does not provide exclusions or name alternatives (e.g., when to use img_exif instead), so it misses the full 5 criteria.
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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Most tools are clearly distinct, but img_compress and img_convert both support format changes, and img_info and img_exif both read metadata, creating minor overlap. The descriptions help clarify the primary purposes, so ambiguity is low.
All tools share the img_ prefix and mostly use verb-based names like img_compress and img_resize. However, img_info and img_exif are noun-based, which is a slight deviation from the pattern, though still predictable and readable.
With 8 tools, the server is well-scoped for an image toolbox. Each tool addresses a common operation without unnecessary additions, making the count appropriate for the stated purpose.
The toolset covers the core image lifecycle: inspecting info, reading EXIF, compressing, converting, resizing, cropping, rotating, and watermarking. There are no glaring gaps for a practical image toolbox, so agents can handle typical workflows end-to-end.