openmeter_usage_by_org

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 not state that this is a read-only query, whether any scoping/permission constraints apply, or how the time window affects results. Only the output dimensions are implied.

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?

A single front-loaded sentence fragment with no filler; the metric list is efficiently packed. It is appropriately sized for a simple two-parameter 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?

For a read-only aggregation tool with no annotations and no output schema, the description names the returned metrics but omits the time-window behavior (hours, capped at 720) and any usage context. It is minimally adequate but leaves real gaps.

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 50%: orgId is documented in the schema, while hours is not described in the description at all. The schema itself supplies default (24), min (1) and max (720) for hours, which conveys most of its meaning, so the description neither compensates nor misleads.

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?

States a specific resource (per-org usage breakdown) and enumerates the metrics returned (tokens, tool calls, costs by provider and model), so the agent knows what the tool produces. It does not explicitly distinguish itself from the sibling openmeter_usage_anomaly, so it falls short of a 5.

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 when-to-use guidance, no prerequisites, and no mention of alternatives such as openmeter_usage_anomaly or openmeter_outbox_health. The agent must infer purpose from the name alone.

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