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

Discloses the significant token cost of images (~3,000-8,000 per image), which is critical behavioral info in the absence of annotations. It also notes high-quality AI analysis, giving agents a sense of processing overhead.

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?

Two concise Chinese sentences plus a short English title. The core purpose is front-loaded, and the token warning is efficiently integrated. No redundant wording.

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 is simple with no output schema, and the description covers purpose and token cost. However, it does not explain the metadata-returning behavior when include_images is false, which is only partially covered by the schema.

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 50% (include_images has a description, report_id does not). The description indirectly adds context about token usage relevant to include_images, but it does not clarify report_id or directly explain parameter behavior.

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 '取得報告截圖圖片（視覺 Bug 用）' (get report screenshot images for visual bugs), providing a specific verb, resource, and use case. It is distinct from sibling tools like get_console_logs and get_network_errors.

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?

Explicitly recommends use for visual bugs and advises using only when needing to see the screen ('建議只在需要看畫面時使用'). It provides clear context and an implied exclusion, though it does not name alternative tools.

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