image_compare

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

The description discloses the return format (structured difference report with type, severity, and description), adding value beyond the schema. However, it does not mention whether the tool is read-only, potential limitations, or edge cases. Since no annotations are provided, the description carries the full burden but only partially fulfills it.

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 concise sentences, front-loaded with the core action, followed by use cases and output summary. Every sentence adds value with no redundancy or fluff.

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 description covers the tool's purpose, appropriate scenarios, and output structure, which is adequate for basic understanding. However, it lacks details about edge cases, limitation, or how to interpret the report fields beyond their names. With no annotations or output schema, more context could be expected for a complete picture.

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?

The input schema has 100% description coverage for all three parameters, so the description does not need to add parameter semantics. The description does not elaborate on parameters beyond what the schema already provides, which is acceptable given the high schema coverage.

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's function: '对比两张图片的差异' (compare differences between two images). The specific scenarios (design vs implementation, before/after, spot-the-difference) help distinguish it from sibling tools like image_understand and image_ocr.

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 use cases ('设计稿vs实现、修改前后对比、找不同') that indicate when to use this tool. It does not explicitly mention exclusions or alternatives, but the sibling tool names give implicit context for differentiation.

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