study_cancel

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

No annotations provided, so description must disclose all behavioral traits. It mentions cancellation and a delay in response, but fails to specify side effects (e.g., whether partial results are preserved), safety of multiple calls, or behavior when no operation is running.

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?

Description is extremely concise with two sentences and a return line, all front-loaded with the primary action. No wasted words.

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?

Given no annotations and no output schema, the description is somewhat complete for a simple action, but lacks detail on the return value structure and missing behavior edge cases like no active solving operation.

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?

Tool has zero parameters and schema coverage is 100%, so description does not need to explain parameters. Baseline score of 4 applies as there is no additional parameter info required.

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?

Description clearly states the tool cancels the current solving operation, with a specific verb 'Cancel' and resource. This distinguishes it from sibling tools like study_solve (starts solving), study_get_progress, and study_wait.

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?

Description implicitly indicates use when there is an ongoing solving operation, but does not explicitly state when not to use or compare with alternatives like study_wait or study_solve_async. The note about solver delay gives some guidance on behavior but not on selection.

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