Cancel DataLens Spark application

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

Annotations already declare readOnlyHint=false, destructiveHint=false, idempotentHint=false and openWorldHint=true, so the safety profile is covered. The description adds genuinely useful context the annotations cannot: the call returns an async operation handle, and the caveat that the endpoint is experimental and 'never called: not measured' — a meaningful reliability disclosure.

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 short sentences, the action and return value front-loaded, followed by the caveat. No filler, though the second sentence's phrasing ('written from its document and never called: not measured') is slightly stilted.

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 two-parameter mutation with annotations covering safety and no output schema (the return is described as an operation), this is adequate. It omits prerequisites and any statement of what happens to the application or its in-flight work after cancellation, which an agent would want for a cancel operation.

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% with two documented required parameters (cluster_id, application_id), so the schema carries the parameter semantics. The description adds nothing about parameter format or semantics, which is the expected baseline when the schema is complete.

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 names a specific verb and resource ('Stop a Spark application') and states what is returned ('the operation that cancels it'), which distinguishes it from siblings like datalens_sparkapplications_get/list/create/log_list. It stops short of explicitly differentiating from adjacent lifecycle tools such as datalens_sparkclusters_stop.

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?

There is no explicit when-to-use guidance, no preconditions (e.g. the application must be running), and no named alternative. The only implied usage comes from the verb 'Stop', which a caller must infer.

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