cancel_job

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

Annotations already indicate destructive and idempotent behavior. The description adds important context: it kills simulator processes and marks the job as cancelled, which goes beyond the annotations. It does not mention error handling or side effects, but the core behavior is well communicated.

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 with a parenthetical clarification. It is front-loaded with the action and resource, and every word adds value. No wasted or redundant content.

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, no output schema), the description adequately covers what the tool does and its effect. It is missing information about the return status or behavior on already-cancelled jobs, but these are minor for such a straightforward action.

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 parameter 'job_id' has a schema description ('Job ID of the running simulation to cancel') that is clear and covers 100% of the parameter. The tool description does not add additional information about the parameter, so 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 uses a specific verb ('cancel') and clearly identifies the resource ('running simulation job'). It distinguishes between single runs and batch types (sweep/Monte-Carlo), and explains the effect ('kills processes, marks cancelled'). No sibling tool has a similar purpose.

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 explicitly states when to use the tool (to cancel a running simulation). It does not mention when not to use it (e.g., if job already completed) or alternatives, but the purpose is clear enough for an AI agent to infer typical usage.

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