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

Annotations only include openWorldHint=true. The description does mention it returns a combined text of total/production/sales/dependent counts and excludes certain data, adding some behavioral detail beyond the schema. However, it does not disclose handling of edge cases, exact output format beyond 'text', or any side effects. With openWorldHint present, one might expect a note about possible extra fields, but it's absent. Given the low annotation coverage, the description carries partial burden but is not fully transparent.

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 compact, front-loads the main function, and includes examples and exclusions. It also contains a pricing note, though that is arguably extraneous. Overall, every sentence contributes to understanding the tool's scope, with minimal fluff.

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?

The tool is moderately complex with multiple metrics returned and an output schema exists. The description covers the main use case, metrics, and exclusions, and provides examples. It does not explain prerequisites like valid region names or error behavior, but given the schema and examples, it is fairly complete for an agent to use. Slightly higher than basic due to the typical questions.

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 all parameters have descriptions (year, region, chain_name). The tool description does not add parameter-specific meaning beyond the schema; it only reinforces with typical questions. This meets the baseline of 3; it does not go further to explain any nuances like region name matching or chain name variants.

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 it queries the number of companies by region and industry chain, and specifies the exact metrics returned (total, production, sales, dependent). It distinguishes itself from sibling list tools (like chain_company_list) and other category-specific count tools by explicitly listing what it includes and excludes (excluding other categories and detailed lists). This is a specific verb+resource+scope.

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 gives clear context on when to use (region + chain name count queries) and provides typical question examples. It explicitly states what it does not include (other category statistics, list details), but does not name specific alternative tools or explicitly say 'use this instead of that'. This is clear usage context without explicit exclusions to alternatives, so a 4 is appropriate.

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