metering__list_meters

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

With no annotations, the description must disclose behavioral traits. It only states the operation is a read (list) but does not mention safety, authentication requirements, scope (global vs. context-specific), pagination, or side effects. The lack of any behavioral context is a gap.

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 description is short but includes a bracketed prefix that may be extraneous. It is mostly concise, though the prefix adds minor clutter. Every sentence serves a purpose.

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 no parameters and a simple list operation, the description provides sufficient information about what is returned (meters with event/invoice counts). It is reasonably complete for a straightforward list tool, though absence of an output schema limits detail.

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?

There are no parameters (baseline 4). The description does not add parameter information because none exist, so it meets the baseline expectation.

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 ('List') and resource ('all meters') and mentions what is returned ('event/invoice counts'). It clearly distinguishes from sibling tools like metering__create_meter (create) and metering__usage_summary (summarize).

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 implies usage for obtaining a list of meters with counts, but provides no explicit guidance on when to use this tool versus alternatives (e.g., metering__list_events, metering__usage_summary) or any exclusions.

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