cancel_job

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

Annotations already flag destructiveHint=true and readOnlyHint=false; the description goes further by stating the concrete behavioral effects: stopping active execution and preventing further outputs. This adds context not captured by the annotations and is consistent with them.

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?

Two sentences, the action is front-loaded, and every word adds meaning. No unnecessary detail or redundancy.

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?

For a simple two-parameter mutation with an output schema, the core purpose and behavior are covered. However, the meaning of the reason parameter is missing, and there is no guidance on edge cases like cancelling an already-completed job. This leaves a moderate gap for an AI agent.

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 schema has 0% description coverage, and the description does not explain either parameter. jobId is only implied by 'existing job,' and the optional reason parameter is entirely unexplained. Agents must infer parameter meaning without support.

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 and resource: 'Cancel an existing Jungle Grid job,' which clearly distinguishes it from sibling tools like submit_job, get_job, and list_jobs. It also adds the functional effect of stopping active execution and preventing further outputs, leaving no ambiguity about the tool's 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 provides clear usage context: it applies to an existing job and may affect active execution. It does not explicitly name alternatives or when-not conditions, but no sibling tool offers cancellation, so the context is sufficient for an agent to select this tool.

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