UI 截图对比

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

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It only states that the tool '逐条列出视觉与实现差异及可能的回归' (lists differences and regressions) but omits any details about how images are processed, stored, or whether the operation has side effects. This lack of transparency is a significant gap.

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, focused sentence that conveys the core purpose and usage context. It is concise and front-loaded, but could potentially include a bit more detail without being verbose.

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 has 7 parameters, a required pair, and an output schema, the description is minimal. It relies heavily on the schema for parameter details but does not elaborate on output format or typical scenarios. This is adequate but not thorough.

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?

With 100% schema description coverage, the schema already documents all 7 parameters. The description does not add any additional meaning or context beyond what the schema provides, so a baseline score of 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 clearly states the tool's purpose: comparing two UI screenshots to list visual differences and possible regressions. The title 'UI 截图对比' and the phrase '做视觉回归/前后对比时使用' explicitly indicate its use for visual regression or before/after comparison. This distinctively separates it from sibling tools like image_analysis or diagnose_error_screenshot.

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 by stating '做视觉回归/前后对比时使用' (use for visual regression/before-after comparison). However, it does not explicitly mention when not to use the tool or suggest specific alternatives, leaving some room for interpretation.

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