scale_to_zero

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

Annotations only declare write/destructive/non-idempotent, but the description goes further: it states the operation is reversible to the prior replica count, warns of cold-start latency and possible ingress stranding, and offers dry_run as a safe preview. That is exactly the extra behavioral context the annotations cannot carry.

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?

Front-loaded with the risk tag and core action, followed by consequences and then the argument list — a sensible ordering with little waste. The Args entries for application/deployment are near-tautological, but given 0% schema coverage they still earn their place.

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 high-risk mutation with no output schema and 0% schema coverage, the description covers reversibility, side effects, preview, and all parameters. It stops short of mentioning how to restore replicas afterward (wake/scale-up path) or any permission requirements, but nothing essential to correct invocation is missing.

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 0%, so the description must compensate, and it does via the Args block: it clarifies application is the serve application name, deployment the deployment name, dry_run previews the change, and target comes from config with a default if omitted. The entries are brief but cover all four parameters meaningfully.

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 states a specific verb and resource — park a deployment at 0 replicas — and the 'at 0 replicas' scope inherently distinguishes it from sibling scaling tools such as scale_replicas_down or scale_replicas_up. The [WRITE][risk=high] tag further signals the operation class without ambiguity.

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?

Motivation is implied ('Stops the cost bleed') and the dry_run preview is suggested, but there is no explicit when-to-use/when-not guidance and no named alternative such as model_sleep, model_undeploy, or scale_replicas_down. An agent must infer the appropriate scenario.

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