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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is well covered. The description adds the list of returned metrics, which is useful, but does not disclose behavioral details such as data source, update frequency, or handling of missing metrics.

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, well-structured sentence that front-loads the tool's purpose ('Cost and outcome metrics for one school') and then lists the specific metrics. There is no redundant or filler content.

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 simple one-parameter lookup with rich annotations and no output schema, the description works as a de facto output contract by naming every metric returned. It lacks caveats around data availability, but nothing essential seems missing for correct invocation.

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 100%, with unit_id documented as the IPEDS UNITID (Scorecard 'id'). The tool description does not need to add parameter semantics, and it does not attempt to; the schema adequately carries this information.

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 as returning cost and outcome metrics for a single school, and enumerates the specific metrics included. It differentiates from broader sibling tools like college_trends and college_compare by scoping to 'one school,' though it does not name those alternatives explicitly.

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 intended use is implied: call this when you need tuition, graduation, earnings, admission, or SAT/ACT metrics for one institution. However, there is no explicit guidance on when to prefer it over related sibling tools such as college_compare, college_demographics, or college_value_score.

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