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

The description adds useful context beyond the openWorldHint annotation: it clarifies the output is a merged text of total/production/sales/dependent lists, and explicitly states it does not return names for other categories. However, it doesn't disclose details like pagination, result limits, or whether the output is a single text blob vs structured data, which would be helpful for a list-returning tool.

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 with clear sections: purpose, included types, exclusions, and examples. It's slightly verbose with the pricing block, but the core content is front-loaded and each sentence adds value. The examples are particularly useful for grounding the agent.

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 and 100% parameter coverage, the description is fairly complete. It covers what the tool does, what it returns, what it excludes, and provides examples. The main gap is lack of detail on output format (e.g., is it a single merged string or a list of objects?), but the output schema likely covers this.

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 the schema already documents all three parameters. The description adds example values for region and chain_name, and clarifies the year is optional, but doesn't add significant new semantics beyond what the schema provides. 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 discredited company lists by specific region and industry chain, and explicitly lists the four types of lists returned (total/production/sales/dependent). It distinguishes from sibling tools like chain_discredited_company_num (which returns counts) and park_discredited_company_list (which is park-scoped).

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: it specifies the required inputs (region and chain name), gives typical query examples, and explicitly states what is NOT included (other company categories, only counts). It doesn't explicitly name alternative tools for other categories, but the exclusions are clear enough for an agent to infer when not to use this tool.

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