list_course_prefixes

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

Annotations already declare read-only, idempotent, non-destructive, and open-world behavior. The description adds useful behavioral context by stating the result spans all terms and includes each prefix's name. No contradiction with annotations is present.

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?

Two concise sentences with no wasted words. The action and scope are front-loaded, followed by a purpose clause, making the description easy to parse quickly.

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 zero-parameter, read-only enumeration tool with strong annotations, the description is complete. It identifies what is returned (subject prefixes with their names), the scope (all terms), and the intended use case. The absence of an output schema is compensated by the description's clear indication of the return content.

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 tool has zero parameters, and schema description coverage is 100% vacuously. The baseline of 4 applies because there are no parameter details that the description would need to clarify.

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 states a specific verb ('List') and resource ('every USC subject prefix in the catalog'), includes examples ('CSCI, MATH, AHIS'), and specifies scope ('across all terms'). This clearly differentiates it from sibling list tools such as list_terms and list_schools.

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 phrase 'Useful for discovering what subjects exist' provides a clear context for when an agent should invoke this tool. It does not explicitly mention alternatives or exclusions, but for a simple enumeration tool this guidance is sufficient.

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