vision_image_metadata

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

No annotations are provided, so the description carries full burden. It clearly discloses the tool is local, non-cloud, and reads specific metadata types. It lacks details on error handling or behavior with unsupported formats, but overall transparency is good for a read-only tool.

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 a single, well-formed sentence that front-loads the key action and results. Every word is necessary; there is no redundancy or verbosity.

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?

Given the tool's simplicity (one parameter, no output schema), the description fully covers the tool's purpose, what it reads, and its local nature. It provides sufficient context for an AI agent to understand the tool's capabilities and constraints.

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% for the single parameter 'image', which already details the supported input formats. The tool description adds no additional parameter-level meaning beyond what the schema provides, so baseline 3 is appropriate.

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 explicitly states the tool reads metadata (dimensions, format, color mode, EXIF), specifies local Pillow parsing with no cloud calls, and distinguishes itself from sibling tools like vision_analyze_image (likely more complex) and vision_analyze_video (video). The verb '读取' (read) and resource '元信息' (metadata) are 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?

The description implies usage when local metadata extraction is needed ('本地 Pillow 解析，不调用云端'), but does not explicitly state when to use this tool versus alternatives like vision_analyze_image, nor does it provide when-not-to-use guidance. Usage context is implied but not explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.