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

The description does not contradict annotations (openWorldHint=true), and it adds concrete details about the metrics and exclusions. However, it does not disclose broader behavioral aspects such as date range coverage, pagination, or the meaning of 'periodic change', but with the openWorldHint annotation and a clear scope, the transparency is adequate.

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 concise but rich in content, using bullets for metrics and typical questions. It is slightly verbose in listing all metrics, but each item is useful for understanding scope. Overall, it is well-structured and front-loaded with the primary purpose.

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 an output schema (not provided here), the description need not explain return values. The description covers purpose, parameters, exclusions, and examples, which is sufficient for a moderately complex query tool with two parameters and high schema coverage. Missing details like date ranges or aggregation levels are not critical given the output 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?

The input schema has 100% coverage with descriptions for both parameters (company_name and country_name). The description adds context about the company name format and includes examples (e.g., '比亚迪股份有限公司', 'Tesla, Inc.'), but does not provide additional meaning beyond the schema's own descriptions. Baseline 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 queries reputation-awareness related periodic changes for a specific enterprise, and explicitly lists the metrics/types included (media reports, research reports, network heat, official media visits and average browsing time). It also distinguishes from reputation favorability and other non-classified metrics, which differentiates it from sibling tools like enterprise_change_reputation_favorability.

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 explicitly states it is not for award reputation or non-negative proportion evaluations, and not for batch filtering by park/industry chain. It provides typical question examples in multiple languages and lists what metrics are included and excluded, giving clear guidance when to use this tool vs alternatives.

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