scale_to_zero

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

With no annotations, the description fully discloses the write operation, high risk, reversibility (prior count stored), and side effects (cold-start latency, ingress stranding). The dry_run option is also mentioned for safe preview. This provides strong behavioral transparency.

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 very concise: a one-line purpose, a risk note, a sentence of trade-offs, and a bulleted arg list. It is well-structured and front-loaded with key information, no redundant words.

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 complexity of a write operation with no output schema, the description covers input behavior and reversibility. However, it does not explain what the tool returns or how to interpret the result (e.g., confirmation, prior count). This minor gap prevents a perfect 5.

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 description provides clear, concise descriptions for all 4 parameters: application, deployment, dry_run, and target. It compensates for the 0% schema coverage by explaining each parameter's role. However, the target parameter description is a bit vague ('omit for the default'), so not a 5.

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 clearly states the tool's purpose: 'Park a deployment at 0 replicas (reversible → prior count).' The verb 'park' and resource 'deployment' are specific, and it distinguishes from siblings like scale_replicas_up/down by focusing on scaling to zero with reversibility.

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 explains when to use: 'Stops the cost bleed' and notes trade-offs: cold-start latency and ingress stranding. It suggests using dry_run for preview. However, it does not explicitly exclude scenarios or compare to alternatives like scale_replicas_down, so not a perfect 5.

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