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

With no annotations, the description carries the full burden of behavioral disclosure. It reveals that the output includes rank and attendance data, which is useful, but it does not explain how 'near' is determined, what data source is used, or what other behavior to expect.

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 a single efficient sentence with no filler. It front-loads the main purpose and lists the key output data, though the ambiguous slash construction slightly weakens the clarity-per-word ratio.

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 simple, has an output schema, and the description names its core output data. However, for a school-related tool among many similar siblings, the lack of differentiation and parameter guidance leaves the description minimally viable rather than complete.

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 0%, so the description must compensate for the single suburb_name parameter. It confirms the parameter refers to a suburb but gives no format guidance, examples, or clarification of how names should be supplied.

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 identifies the resource (schools) and the location scope (serving/near the suburb), and specifies the included data (rank + attendance). It is understandable on its own, though the slash between 'serving' and 'near' introduces mild ambiguity and it does not explicitly distinguish itself from sibling school tools.

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?

No guidance is given about when to use this tool instead of closely related siblings like suburbs_schools_all, suburbs_schools_catchment, or properties_schools_nearby. The description implies a school-lookup use case but provides no selection criteria or exclusions.

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