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

Annotations already establish read-only, idempotent, open-world, and non-destructive behavior. The description adds the useful caveat that last action date and programmatic accreditations are included only when published by DAPIP, giving the agent awareness that these fields may be absent. This is helpful context but not extensive behavioral disclosure.

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, compact sentence with no filler. It front-loads the core purpose ('Current institutional accreditation status') and packs the additional fields and DAPIP caveat efficiently.

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 lookup with no output schema, the description covers what data will be returned and the key condition under which some fields are available. Nothing needed to invoke the tool correctly is missing.

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 single parameter unit_id is already fully described in the schema as 'IPEDS UNITID' (100% schema description coverage). The description does not add further parameter details, so the baseline score of 3 is appropriate.

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 resource (institutional accreditation) and enumerates the returned data: status, accreditor, last action date, and programmatic accreditations. It does not use an explicit verb like 'gets' or 'returns,' but the intent is unmistakable and it is distinct from sibling college_* tools that focus on search, metrics, or outcomes.

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 related siblings such as college_search, college_metrics, or college_compare. There are no explicit when-to-use conditions, exclusions, or alternative tool names, so an agent must infer suitability from the name alone.

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