batch_course_details

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

Without annotations, the description carries the burden. It discloses that the tool performs parallel fetches and is faster. It also clarifies default behavior for empty semester and year parameters. It does not mention error handling or limits, but those are less critical given the output schema.

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 succinct and well-structured: an intro sentence, a comparative sentence, and a clear Args block. Every sentence adds value without redundancy.

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?

The description covers the tool's purpose, usage context, parameters, and performance benefit. The output schema handles return format. It could mention potential limitations like maximum codes, but for a batch fetch tool this is adequate.

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 schema has no descriptions, but the description's Args section adds critical meaning: it provides example codes, enumerates valid semester values, and explains that empty strings default to the current term/year. This fully compensates for the schema's lack of descriptions.

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 the tool's function: 'Get details for multiple courses at once (parallel fetch).' It uses a specific verb and resource, and distinguishes itself from sibling course_detail by emphasizing batch operation and speed.

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 explicitly mentions the alternative 'calling course_detail repeatedly' and positions this tool as faster for batch operations. However, it does not explicitly state when not to use it (e.g., for single course requests), though it is implied.

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