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

The annotations already declare this as a read-only, idempotent, open-world operation, so safety behavior is covered. The description adds useful context about the returned fields (kind, unit, last-seen time), but it does not mention pagination, filtering behavior, or result ordering.

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?

It is a single efficient sentence that front-loads the resource and packs the returned fields without waste. Every clause contributes directly to understanding what the tool returns.

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?

With no output schema, the description needs to carry the return-value burden, and it does mention the key fields returned. However, it omits pagination, filtering semantics for limit/search, and when to choose this over get_metric_series, leaving meaningful gaps for a four-parameter list tool.

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 only 50%, with the app and environment parameters documented but limit and search left undescribed. The description does not compensate by explaining what limit or search do or how they affect the returned metric list.

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 identifies the resource as metric names reported by an application and lists the metadata returned: kind, unit, and last-seen time. It implicitly contrasts with series-level tools like get_metric_series by focusing on names and definitions, but it does not explicitly name or differentiate from that sibling.

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 guidance on when to use this tool versus alternatives such as get_metric_series or list_event_names. The description implies discovery usage by saying it returns metric names, but no exclusions, prerequisites, or alternative routing are stated.

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