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

Beyond the annotations (readOnly=false, idempotent=false), the description discloses the mechanism (pod template annotation update) and its consequence (all pods are recreated), which is the key disruptive side effect an agent needs. It stops short of covering reversibility, rollback, or timing/rollout-wait behavior, and nothing contradicts the annotations.

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 tight sentences, zero filler, with the action and its consequence front-loaded.

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 mutation tool with no output schema, the description explains the trigger and the resource-level effect, which is the critical missing context. It could add a note on expected downtime/rollout duration or that the change is safe to repeat, but the essentials are present.

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 coverage is 100%, so namespace, cluster_id, deployment_name, and dry_run are all documented in the schema; the description adds no extra parameter meaning. Baseline 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?

States a specific verb+resource ('rolling restart of a deployment') and even the underlying mechanism, so the agent knows exactly what the call does. It does not, however, explicitly distinguish itself from nearby mutation siblings such as scale_deployment, delete_pod, or redeploy_stack.

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 mention of prerequisites or cluster/auth requirements, and no routing to alternatives (e.g., scale_deployment when the goal is replicas rather than pod rotation). Usage can only be inferred from the tool name and the mechanism sentence.

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