jupyter_stop_kernel

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

With no annotations, the description carries full burden but only says 'Stop a running kernel.' It fails to disclose whether stopping is safe or disruptive, if it requires permissions, or what happens to the kernel's state (e.g., unsaved data). The lack of behavioral context leaves the agent uncertain about side effects.

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 sentence that gets straight to the point with no fluff. However, it might be too brief; a bit more context could improve it. Still, it is well-structured and front-loaded.

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 the tool's simplicity (one parameter, output schema exists), the description is minimally complete. However, it lacks context about the kernel lifecycle, error conditions, and relationship with other kernel tools. For a tool that can have side effects, more completeness is expected.

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 already defines the kernel_id parameter with a clear description. The tool description adds no additional meaning beyond what the schema provides. Since schema coverage is 100%, a baseline score of 3 is appropriate.

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 action (stop) and the resource (running kernel). It distinguishes from sibling tools like jupyter_restart_kernel and jupyter_interrupt_kernel by focusing on termination. The specific verb ensures the agent knows exactly 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 description provides no guidance on when to use this tool instead of alternatives. It does not mention differences from jupyter_interrupt_kernel or jupyter_restart_kernel, nor does it indicate prerequisites (e.g., the kernel must exist and be running).

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