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

Annotations already declare readOnly, idempotent, and non-destructive, so the safety profile is covered. The description adds value beyond annotations by noting the tool is free and returns distinct machine-readable schemas for two different targets, which clarifies access and output nature.

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?

One front-loaded sentence conveys purpose, cost, target tools, and output format with no filler. Every phrase ('Free', 'distinct', 'machine-readable') contributes useful information.

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?

For a zero-parameter, annotation-backed tool, the description is complete: it names the exact resources whose schemas are returned and the output nature. No output schema exists, but the description adequately explains what the caller will receive.

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?

The tool has zero parameters, so there is no parameter burden for the description to carry. The empty schema fully covers the parameter surface, and the baseline of 4 applies.

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?

States a specific verb (get), resource (machine-readable schemas), and target (preview_company tool and verify_company evidence result), so an agent knows what it returns. It is clear, but does not explicitly contrast with the sibling describe_service, so differentiation rests mostly on the 'machine-readable' qualifier.

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 implies use when an agent needs schemas for preview_company or verify_company, and it provides useful context (free, limited vs paid). However, it does not state when to choose get_schema over describe_service or any alternative, leaving routing partly to inference.

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