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

Adds real context beyond annotations: external database comparison across 15 offices, YOLO detection plus visual similarity, consistent with openWorldHint=true. It says nothing about latency/cost of external queries, what enableRadar monitoring actually does after the call, or what result structure (bounding boxes, similarity scores) comes back — notable given no output schema.

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 sentences, front-loaded with the capability and followed by trigger routing. The trailing 'even if the user does not explicitly say...' clause earns its place by widening recall for an implicit-need tool.

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?

Adequate for invocation: required inputs (imageUrl, topNumber) plus region scoping are covered, and the description explains the comparison target. But with 7 parameters, no output schema, and no explanation of the return shape or cost of an external trademark-database sweep, an agent still cannot anticipate results.

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%, so the baseline is 3; every parameter including regions, topNumber, enableRadar and enableLocalizing is already documented in the schema. The description adds no syntax, format, or interaction detail beyond that (e.g., how trademarkName narrows results, or what enableLocalizing changes in the output).

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?

States a specific verb+resource: detecting *graphic* trademarks in product images against registered trademark databases across 15 offices, with the method (YOLO object detection + visual similarity) named. The 'graphic' qualifier implicitly separates it from text-mark tools like nexscope_ruiguan_text_trademark_detection and from logo removal utilities.

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?

Lists concrete trigger conditions (logo infringement check, trademark similarity analysis, image trademark risk assessment) and explicitly covers the implicit case where the user never says 'trademark detection'. It gives no when-not-to-use guidance or named alternatives, so the agent must infer that word-mark checks belong to the text-trademark sibling.

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