metering__usage_summary

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

No annotations are provided, so the description carries full burden. It states the tool returns totals (event count, total quantity, accrued minor units) but does not disclose side effects, authorization needs, or whether it is read-only. This is insufficient for safe agent decision-making.

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 concise and to the point, providing the tool's purpose in a single sentence plus a parenthetical. However, the parenthetical '(x402 meter)' may be ambiguous and could be clarified. Overall, it is efficient without unnecessary verbosity.

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 simple tool with one parameter and no output schema, the description adequately covers what the tool returns (event count, total quantity, accrued minor units). It does not mention related context like periods or filters, but given the tool's simplicity, it is mostly complete. The lack of differentiation from metering__sla_report is a minor gap.

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%, meaning the schema only provides the parameter name and type (string). The description adds context by stating 'Totals for a meter,' which clarifies that meter_id identifies the meter. However, it does not explicitly describe the parameter format or constraints, so it only partially compensates for the lack of schema detail.

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 states the tool provides totals for a meter (event count, total quantity, accrued minor units), which is a specific verb-resource combination. It distinguishes from sibling tools like record_usage (records individual events) and list_meters (lists meters) by focusing on aggregated summary data.

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?

No explicit guidance on when to use this tool versus alternatives like metering__sla_report or metering__list_meters. Usage is implied (when you need totals) but lacks exclusions or context for proper selection among sibling tools.

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