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

Annotations include openWorldHint=true, which the description doesn't contradict. The description adds context on the tool's scope (international vs domestic) and indicator categories, which is beyond the annotations. It doesn't disclose return format or pagination, but with an output schema present, the description carries less burden here. No contradictions found.

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 fairly long but informative, with a clear purpose statement, explicit inclusions/exclusions, and examples. The pricing information is appended but might be redundant if annotations already provide it. It's structured with bullets and examples, earning its space, though it could be tightened.

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?

With a rich description covering purpose, scope, indicators, exclusions, and examples, plus an output schema and 100% schema coverage, the tool is well-documented. The description compensates for the open-world assumption by clarifying what is included. This is complete for a query tool with moderate complexity.

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 both parameters (company_name, country_name) are already documented with examples. The description adds typical query phrasing and clarifies that queries must be company-specific, which reinforces but doesn't significantly extend the schema. 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 changes in reputation/brand aspects for a specific company, listing concrete indicators (international media coverage, research reports, social media heat, credit ratings, awards, public sentiment health). It distinguishes itself from sibling tools like enterprise_change_reputation_awareness and enterprise_change_reputation_favorability by scoping to international aspects. The verb '查询' is generic, but the resource and scope are specific.

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 what it is not for (domestic-only awareness/favorability) and lists what it does not include (non-category indicators, batch screening). It provides typical query examples. However, it doesn't explicitly name alternative sibling tools for domestic reputation metrics, though the exclusion is clear.

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