list_courses

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

No annotations are provided, so the description carries the burden. It's a list/read operation and nothing in the description suggests mutation, which is consistent. However, it doesn't disclose return format or pagination behavior, and the description is essentially just parameter documentation without richer behavioral context.

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 compact and organized in an Args list format that's easy to scan. Every sentence contributes value. Could arguably be slightly tighter, but the parameter examples earn their place.

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's an output schema present, so return values needn't be explained. With 4 params at 0% schema coverage, the description handles all of them well with examples and defaults. For a straightforward list operation with a present output schema, this is reasonably complete. Given the schema covers the output, the description is adequate for a tool at this complexity.

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 0%, so the description must fully compensate. It does this well: each parameter gets an explanatory note with examples (faculty 'EE', course_type 'BC'/'GS', year format '2025-2026'), and enumerates the values for course_type. The default behaviors for year and institution are also documented. This adds real meaning beyond the bare schema.

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 states it lists course codes for a faculty and course type, with a specific verb (list) and resource (courses). It distinguishes from siblings like search_courses and get_course by focusing on codes for a faculty+course_type combination. However, it doesn't explicitly contrast with search_courses, so it's not a perfect 5.

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 Args section provides implicit guidance on what parameters mean, and the faculty+course_type scoping implies when to use it. However, there's no explicit statement of when NOT to use it versus search_courses or get_course, which are natural alternatives, so guidance is implied rather than explicit.

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