读取图片 EXIF 元数据（拍摄参数 / 是否含 GPS 定位）；strip=true 时输出抹除元数据的隐私安全版。免费(0)。
| Name | Required | Description | Default |
|---|---|---|---|
| strip | No | true=同时生成去除 EXIF/GPS 元数据的干净图 | |
| file_id | No | 图片文件 ID（与 data_base64 二选一） | |
| filename | No | 输出文件名（strip 时可选） | |
| data_base64 | No | 图片内容 base64 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It discloses the strip behavior and that it outputs a clean version without modifying the original, adding behavioral context beyond a simple read operation. It does not contradict annotations.
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 extremely concise and front-loaded with the core purpose, using a single sentence with a semicolon to add the strip behavior. No wasted words.
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?
The tool has 4 parameters and no output schema, so the description should explain return values. It does not specify the format of the EXIF metadata output, though it covers the strip behavior. This gap prevents a higher score.
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%, so baseline is 3. The description adds meaning for the strip parameter by explaining its purpose, but does not elaborate on file_id or data_base64 beyond what the schema already provides.
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 clearly states the tool reads image EXIF metadata and optionally strips it for privacy, using a specific verb and resource. It distinguishes from sibling tools like img_info by focusing on EXIF and the strip feature.
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 description provides clear context on using the strip option for privacy-safe output, implying when to use this tool for EXIF tasks. However, it does not explicitly contrast with alternatives like img_info, so it lacks exclusions.
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 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.