list_billing_utilization

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

No annotations are provided, so the description carries the full burden. It discloses important behaviors: default exclusion of zero-quantity meters, client-side filtering for meter_types and regions, response size management (under 25 KB), and aggregation effects. It does not mention authentication or rate limits, but for a read-only list tool the behavioral coverage is good.

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 a single paragraph of moderate length, front-loaded with the core purpose. Every sentence adds value, and it avoids redundancy. However, it could be slightly more structured (e.g., bullet points for filtering vs aggregation) to improve scanability.

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 7 parameters, no output schema, and no annotations, the description covers behavior extensively: default behavior, filtering, aggregation, performance limits, and response structure for top_n. It is nearly complete, though it does not describe the default response format beyond 'per-resource utilization grouped by datacenter'.

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 100%, but the description adds significant meaning beyond the schema: it explains defaults (include_zero), performance implications (top_n combinations), client-side vs server-side filtering, and aggregation trade-offs. This extra context greatly enhances an agent's ability to use parameters correctly.

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 starts with a clear verb and resource: 'Get per-resource utilization for the current billing period, grouped by datacenter.' It precisely states what the tool does, including scope and grouping. While it does not explicitly differentiate from siblings like list_billing_usage, the purpose is specific enough.

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 provides explicit when-to-use guidance: defaults exclude zero-quantity meters, when to set include_zero, and how to use group_by, top_n, and filters. It also includes performance advice for contracts with many datacenters. However, it does not contrast with alternative billing list tools such as list_billing_usage or list_billing_utilization_by_period.

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