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

Annotations provide openWorldHint: true, but the description adds behavioral context: it returns only a list of names (not counts) and excludes other categories. It does not reveal internal logic or privacy constraints, but adds value beyond annotations.

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 and front-loaded, stating the core purpose first, then exclusions and examples. The pricing info is not part of the description and could be considered extraneous but is separate. The text is efficient with no 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?

Given the simplicity of the tool (2 params, no nested objects, output schema present), the description covers the essential behavioral aspects: what is returned (list of companies), what is not included, and usage examples. It doesn't explain return structure but output schema fills that gap.

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 both fields. The description reinforces the semantic meaning of park_name with examples, and mentions year is optional implicitly in the schema. It adds example values that help agents understand expected formats.

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 for lists of discredited companies in a specific park, explicitly delimiting scope and what is excluded. It distinguishes from sibling tools by targeting 'park' and 'discredited' specifically, and even provides examples.

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?

It explicitly states what is not included (other company categories, only returns count not names), and provides typical query examples, guiding the agent on when to use this tool. The distinction between list vs. num tools is implied but clear.

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