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

The readOnlyHint, idempotentHint, and destructiveHint annotations already communicate that the call is safe and repeatable, so the description does not need to cover side effects. It adds modest context by naming the comparison dimensions, but it does not disclose return format, output size, or behavior with invalid UNITIDs.

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 entire description is one front-loaded sentence: the verb and object first, then the scope and metric dimensions, then the input instruction. There is no filler or redundant elaboration.

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 one-parameter, read-only tool with a fully documented schema, the description supplies enough context to identify the tool and invoke it correctly. A small gap is that it does not suggest how to discover UNITIDs (e.g., via college_search) or describe the response format, but neither is required to make a safe call.

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 input schema already gives 100% parameter coverage with 'Array of 2-5 IPEDS UNITIDs.' The description only repeats 'Pass UNITIDs' and adds no extra semantics about how to obtain or format those IDs.

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 opens with the specific verb 'comparison', names the resource ('schools'), and constrains the scope to 2-5 schools and three metric categories. This is enough to distinguish it from college_search, college_metrics, and other single-school sibling 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?

Usage is only implied: an agent can infer that this is the right tool when a user asks to compare multiple schools side by side. It does not name any alternative tool or give a when-not-to-use condition, even though siblings like college_metrics or college_value_score could overlap.

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