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

The description adds meaningful behavioral context beyond the annotations: it is page-paginated, costs 10 Zooq credits, and returns professional records plus the education link. Since readOnlyHint, idempotentHint, and destructiveHint are already provided, this additional operational detail is valuable. It does not contradict any annotation and gives the agent useful information about cost and pagination.

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 three short sentences with no filler. It front-loads the core resource and purpose, then adds pagination, use case, and cost. Every sentence contributes useful selection and invocation 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?

Given the rich input schema, explicit annotations, and presence of an output schema, the description covers the essential selection criteria and key operational facts such as pagination and credit cost. It does not explicitly contrast with alternatives like search_people, but the institutional scope and use case provide enough context for safe selection. Overall it is complete for most agent decision-making needs.

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 schema already covers all parameters with descriptions, including normalized_name and how to discover it via search_schools. The tool description itself adds little parameter-specific meaning, which is acceptable given the 100% schema coverage. No parameter information in the description is missing enough to reduce the score below the baseline.

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 tool's resource: alumni and current students of an institution, with professional records plus the education link. It also states the intended use case of recruiting and warm-intro sourcing, which helps distinguish it from general people search. However, it lacks an explicit verb like 'search' and does not directly name a sibling alternative, so it falls short of full differentiation.

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 gives clear context: use this when you need alumni or current students of a specific institution, particularly for recruiting and warm-intro sourcing. It does not explicitly state when not to use it or mention alternatives such as search_people, though the institutional focus strongly implies the boundary. The guidance is clear enough for an agent to select it appropriately in most cases.

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