browser_visual_report

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

With no annotations, the description carries full burden. It discloses the output structure (ok, baselines, actuals, diffs, recentResults, total) and error behavior (empty arrays with ok=true). However, it does not explicitly state that the tool is read-only or has no side effects, which is a minor 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 English part is a single sentence, and the Chinese part adds structured details. The information is front-loaded, but the bilingual nature may be slightly redundant for an English-speaking agent. Overall, 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?

Given the tool's low complexity, no output schema, and no annotations, the description adequately covers purpose, output format, error handling, and usage contexts. It is complete for an agent to decide when and how to invoke this tool.

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 tool has zero parameters, and the schema coverage is 100% (empty object). The description explicitly states '参数：无' (parameters: none). Since there are no parameters to document, the baseline of 4 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 it lists visual regression artifacts (baselines, actuals, diffs) and recent comparison results. This distinguishes it from sibling tools like browser_visual_compare or browser_visual_check which perform comparisons or checks.

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 Chinese section explicitly lists when to use: after visual regression tests to view history, before cleaning baselines, debugging visual_compare results, and report summaries. This provides clear context and implicitly states when not to use (e.g., when you need to perform a comparison).

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