get_school

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

No annotations are provided, so the description carries full burden. It states it 'Returns school details' but doesn't disclose behavioral traits like whether it's a read-only operation (implied by 'Get'), authentication requirements, rate limits, error conditions, or what happens with invalid public_id. For a tool with no annotation coverage, this leaves significant gaps in understanding how it behaves.

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 appropriately sized and front-loaded: the first sentence states the core purpose, followed by parameter and return information. No wasted sentences. However, the 'Args:' and 'Returns:' formatting could be more integrated, and it's slightly verbose for a single-parameter tool.

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's low complexity (single parameter, no nested objects) and the presence of an output schema (which handles return value documentation), the description is reasonably complete. It covers purpose, parameter meaning, and return content at a high level. The main gap is lack of behavioral context, but with output schema existing, it doesn't need to detail return values.

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 schema provides no parameter documentation. The description adds value by explaining 'public_id: School's public identifier (URL slug)', giving semantic meaning beyond the bare schema. However, it doesn't provide examples, format details, or constraints, and there's only one parameter, so baseline 3 is appropriate with marginal improvement over schema alone.

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's purpose: 'Get school/university information' with specific verb ('Get') and resource ('school/university information'). It distinguishes itself from sibling tools like 'get_company' or 'get_profile' by focusing on educational institutions. However, it doesn't explicitly differentiate from potential similar tools (none exist in the sibling list), so it's not a perfect 5.

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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context for usage, or comparison with other data retrieval tools in the sibling list (e.g., when to use get_school vs get_company). The agent must infer usage solely from the tool name and description.

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