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

The description adds behavioral context by clarifying that it does not return lists or overseas data, which complements the openWorldHint annotation. It does not contradict annotations. However, it does not disclose any other behavioral traits such as data sources, approximation, or limitations beyond scope, so the transparency is moderate and relies partly on annotations.

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 well-structured: a main sentence, then explicit lists of metrics included/excluded, and example queries. It is concise and front-loaded with the core function. The only minor issue is the appended pricing metadata, but that is not part of the core description and does not detract.

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?

For a simple counting tool, the description is quite complete. It covers purpose, exclusions, parameter examples, and typical queries. Since an output schema exists, return format is not required. It lacks only minor details like handling of invalid region names, but overall it provides sufficient context for correct usage.

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 100% for all three parameters, providing basic definitions. The description enhances this by giving concrete examples (e.g., '全国', '北京市海淀区', '2024', '集成电路') and clarifying that region must be within China. This adds practical value beyond the schema definitions, justifying a score above the baseline of 3.

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 explicitly states the tool counts patents for a specific industry chain within a specific Chinese region, and gives example queries that clearly illustrate the scope. It distinguishes itself from siblings by excluding patent detail lists and company lists, and from other chain_* tools that focus on companies rather than patents.

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 usage context by stating what is included (patent counts) and explicitly excluding patent detail lists, company lists, and overseas regions. It also gives typical question formats, which helps agents decide when to use it. However, it does not name alternative tools, though the exclusions serve as implicit guidance.

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