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

The annotation openWorldHint:true is present, but the description does not elaborate on behavioral aspects such as potential unexpected data, result format, or side effects. However, the tool is clearly a read-type query (by enterprise name), and the description provides context on what it returns (specific indicators), which adds some value beyond the annotation. No contradiction exists, but richer behavioral disclosure is lacking.

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 structured into purpose, included indicators, exclusions, and typical queries. It is somewhat lengthy but well-organized, with each section adding value. The pricing info is included but not essential for usage guidance, but it does not detract significantly. Overall, it is concise given the need to list multiple indicators.

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's moderate complexity (multiple specific indicators), the description covers the scope well. It lists all relevant indicator categories and exclusions, and provides examples. An output schema exists, so return-format details are not required. No significant gaps are evident, though it could have explicitly mentioned that it returns enterprise-level data only.

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%, with both parameters (company_name and country_name) clearly described in the schema with examples. The description itself also provides typical queries using these parameters, but it does not add new semantic information beyond what the schema already covers. Thus, 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 cyclical changes in business operations for a specific company, focusing on strategic adjustments, business transformation, and main business composition changes. It distinguishes itself from siblings by enumerating specific indicators and explicitly excluding macro-level industry research and batch filtering by park/industrial chain, making the purpose specific and unambiguous.

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 explicit scenarios for use (querying strategic adjustments, business transformation, main business structure changes) and non-use (not for industry-level macro research; excludes non-category metrics and batch filtering). It also provides typical query examples, giving clear guidance on when to use this tool versus alternatives.

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