get_resource_usage

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

With no annotations provided, the description correctly identifies the tool as real-time but does not disclose caching, rate limits, or idempotency. It adds value by stating the dependency on metrics-server, which is essential for the agent to know. Minor omission: no mention of whether the operation is read-only (implied but not stated).

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?

Three sentences, front-loaded with purpose, followed by requirement and use case. No filler or redundancy. Each sentence earns its 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 read-only query tool with no output schema, the description covers purpose, prerequisite, and use cases. It does not describe the return format (e.g., CPU units, memory in MiB), but this is acceptable given the lack of output schema and the tool's simplicity.

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%, so baseline is 3. The description adds no additional meaning beyond the schema: it merely restates that podName is optional and namespace defaults to 'default', which are already in the schema. No new parameter context is provided.

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 explicitly states 'Returns real-time CPU and memory usage for pods, compared against their resource requests and limits.' This specific verb (returns) and resource (pods with resource tracking) clearly distinguishes it from sibling tools like get_pod_status which provide general pod status.

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 includes a prerequisite ('Requires metrics-server to be running in the cluster') and a concrete use case ('identify pods that are throttled, near their memory limit, or OOMKill candidates'). However, it does not explicitly state when not to use this tool or mention alternatives among siblings.

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