diagnose_deployment

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

Annotations already declare readOnlyHint=true, idempotentHint=true and destructiveHint=false, so the safety profile is covered by structured data. The description adds real value beyond that by naming the classes of faults surfaced (operator errors, pod-level crash/OOM/pull/scheduling states), which tells the agent what a useful result looks like.

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 with no filler: scope first, routing hint second. Every clause earns its place by naming either a diagnostic dimension or an alternative tool.

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?

An output schema exists, so return structure need not be explained, and annotations cover the safety/idempotency profile. What remains for the description — scope, fault coverage, and the boundary against diagnose_job — is fully 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 description coverage is 0%, so the description must carry parameter meaning, and it only implies it via "one FlinkDeployment" — it never says that name/namespace are the addressing keys or what form they take. The parameters are standard Kubernetes identifiers and largely self-evident, which keeps this from being a serious defect, but no compensating detail is added.

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 resource (one FlinkDeployment), a specific scope (Kubernetes/operator-level health), and enumerates the concrete failure modes it inspects (operator errors, JobManager state, CrashLoopBackOff, OOMKilled, image pull errors, unschedulable). It explicitly distinguishes itself from the sibling diagnose_job, so an agent can pick between them without opening the schema.

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?

"Use diagnose_job for problems inside a running job" is an explicit exclusion that defines the boundary between the two diagnostic tools. It does not address other plausible siblings (list_flink_deployments, cluster_overview) when the deployment is missing entirely, so it falls just short of full routing guidance.

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