cluster_stats

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

No annotations are provided, so the description carries the full behavioral burden. It does disclose some return content (GPU usage and services up) and implies an aggregate read-only snapshot, but it omits important traits such as freshness, auth requirements, and exact return shape, leaving meaningful gaps for an unannotated tool.

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 definition is a single front-loaded sentence with no wasted words. It quickly conveys the verb, resource, scope, and example metrics, which is appropriately sized for a parameterless stats 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?

Given a zero-parameter stats tool with no output schema, the description should explain the return value more completely. It names a few metrics but does not indicate whether the response includes other cluster health fields, formatting, or freshness, so an agent has only a partial picture of what to expect.

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 tool has zero parameters, so there are no parameter semantics to document; the baseline for a parameterless tool is 4. The description appropriately does not speculate about parameters that don't exist.

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 uses a specific verb and resource ("Get aggregate cluster metrics") and names example metrics ("GPUs in use/total, services up"), which is clearer than a tautology. It implies an aggregate/cluster-level view rather than per-resource listing, but does not explicitly distinguish itself from siblings like service_stats, list_gpus, or list_services.

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 states what the tool returns but gives no guidance on when to use it versus alternatives such as service_stats or list_gpus. There are no exclusions, prerequisites, or situational cues to help an agent choose among the many sibling diagnostic/listing tools.

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