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

Annotations only include openWorldHint: true. The description adds that it returns aggregated counts in text form, not a list, and notes what is not included (other classifications, list details). It does not mention any side effects, data limits, or performance characteristics, but for a read-only query tool, this 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 informative, using bullet points for clarity. It front-loads the core functionality and provides examples. It includes pricing info, which may be extra but useful for agents considering cost.

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 output schema exists and parameters are well-documented, the description is sufficient for an agent to understand the tool's scope. It clearly defines what is included and excluded, and provides example queries. The pricing info adds context for resource usage.

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 coverage is 100% with descriptions for each parameter. The description adds value by explaining the combination of region and chain_name, and gives examples of valid inputs. It does not add new information beyond the schema but reinforces the semantics.

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 count of discredited companies in a specific region and industry chain, with distinct result breakdowns (total/production/sales/dependent). It distinguishes from sibling tools by explicitly noting it returns counts, not lists, and excludes other categories. The example questions reinforce its purpose.

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 typical usage examples and clarifies that this is for count queries, not lists or other company types. However, it does not explicitly state when not to use this tool or compare it to alternative tools like chain_company_num, but the context implies it for discredited company counts.

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