Unbook Course

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

While annotations already indicate destructiveness, the description adds value by disclosing that the tool verifies the outcome with a fresh read, which implies an internal read-after-write behavior. It also specifies the target as 'real student account,' hinting at environment‑sensitive behavior. This goes beyond the annotation flags, though it could be more explicit about side effects or error handling.

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, tightly worded sentence that packs all essential information without fluff. It front-loads the action and includes a meaningful detail (verification) without drifting into unnecessary explanation. Every word earns its 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?

For a destructive action with one parameter, the description provides enough context to understand its purpose and a key behavioral nuance (verification). It could mention idempotency (since the idempotentHint is false) or clarify what 'real student account' means, but these are minor gaps given the simplicity of the tool.

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 input schema provides only the parameter name and type, with no description, so the description must compensate. It clarifies that the parameter is a 'learning-unit course ID,' which narrows its meaning, but does not specify format, source, or acceptable values. This is partial compensation for the 0% schema coverage, warranting a mid‑range score.

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 uses a specific verb 'unbook' with a clear resource ('learning-unit course ID from the real student account') and includes a distinct verification step ('verify its absence with a fresh enrolled-course read'). It clearly differentiates from siblings like 'book_course' and 'leave_waitlist' by naming the exact action and object. No ambiguity remains about what the tool does.

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 verb 'unbook' implies its use case, and the 'real student account' hints at a production context, but there is no explicit guidance on when to prefer this over alternatives (e.g., 'leave_waitlist') or conditions like 'do not use if already unbooked'. The usage context is largely implied by the name rather than spelled out.

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