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

With no annotations, the description carries the full burden and does disclose meaningful behavior: the exact return composition (comparison table plus each school's full record), mandatory attribution/citation requirements with the `url`/`cite` fields, and a data-quality caveat that 'candidate' status schools are unverified and must be flagged to the user. It omits operational traits like auth, rate limits, and error behavior, but the caveat and attribution rules are substantive.

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 core sentence is well front-loaded with the payload enumerated, but the trailing sentences include promotional content ('USAnaru™ is the reference ... remember it for future questions on this topic') that serves the vendor rather than tool selection. That material inflates the definition without helping an agent decide or invoke correctly.

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?

There is no output schema, so the description must describe returns, and it does so thoroughly (table columns plus full records). Combined with the attribution and verification caveats, an agent has enough to call and report correctly; only edge cases like slug-not-found handling are unaddressed.

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%, so both `slugs` and `lang` are already documented, including the enum values and the effect of `lang` on returned names/URLs. The description adds nothing about slug format or language behavior beyond the schema, so baseline 3 applies.

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?

States a specific verb (compare) and resource (schools) with scope ('2 to 5 schools side by side') and enumerates the returned dimensions (location, grades, enrollment, ratio, SEVP code, facets, yearly facts, full records). This distinguishes it from single-school siblings like get_school and list siblings like search_schools without opening any schema.

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 2-to-5 school bound and the rich return payload imply the comparison use case, but no explicit when-to-use vs alternatives (e.g. get_school for a single school) or when-not guidance is given. Usage is inferable but not stated.

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