colab_stop_training

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

The description discloses the core behavior: it interrupts a running training job and changes its state to 'cancelled'. With no annotations provided, the description carries the full burden, but it does not mention side effects, irreversibility, or error behavior; these gaps are moderate for a cancellation operation.

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 concise sentence with no filler. It front-loads the action and states the outcome efficiently, making it easy for an agent 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?

The tool is simple, with one parameter and no output schema, so the description covers the essential action. However, given the ambiguous sibling tool set, the absence of usage guidance and any detail about return values or errors makes the description merely adequate rather than complete.

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%, and the description does not explain the job_id parameter beyond the schema's property name. Since there is only one string parameter, its purpose is inferable, but the description adds no explicit guidance such as how to obtain the job_id or that it should correspond to a training job returned by colab_run_training.

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, 'Interrupt', with a specific resource, 'a running training job', and states the outcome, 'mark it cancelled'. However, it does not explicitly differentiate itself from sibling tools like colab_cancel_job or colab_stop_execution, relying on the phrase 'training job' to imply the distinction.

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 gives no guidance on when to use this tool versus alternatives such as colab_cancel_job or colab_stop_execution. It does not mention prerequisites, whether the job must be currently running, or what to do if the job has already completed.

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