jupyter_interrupt_kernel

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

No annotations are provided, so the description must fully disclose behavioral traits. It states that the tool interrupts and stops current execution but does not clarify if the kernel remains running, whether the operation is safe, if it requires specific permissions, or what side effects occur. The minimal disclosure is insufficient for a mutation tool.

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 unnecessary words. It effectively communicates the core action in a front-loaded manner.

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 has one parameter and an output schema, the description is adequate but lacks context about the kernel's state after interruption (e.g., kernel remains idle) and when to use this tool versus other kernel management tools. It meets minimum viability but has clear gaps.

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 100% for the single parameter, which already describes 'ID of the kernel to interrupt'. The description adds no extra meaning beyond the schema, so the 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 uses a specific verb 'Interrupt' and resource 'a running kernel', clearly indicating the action. It distinguishes from sibling tools like jupyter_stop_kernel or jupyter_restart_kernel by focusing on interrupting current execution rather than stopping or restarting the kernel.

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 such as jupyter_stop_kernel or jupyter_restart_kernel. It does not mention prerequisites, conditions under which interruption is appropriate, or when other tools should be preferred.

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