get_usageHow many requests the calling account has used this month, the plan limit, the per-minute limit and when the counter resets — and, on an owner-granted trial, when the trial ends (trial_ends_at).
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish that this is a read-only, idempotent, non-destructive, closed-world operation, so the description does not need to repeat those traits. It adds meaningful behavioral context by specifying the fields returned, including conditional trial_ends_at information on owner-granted trials. It does not describe response format or pagination, but for a zero-parameter usage snapshot that is a minor omission.
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 efficient sentence that front-loads the core usage metrics before adding the trial-related conditional. It is appropriately sized for a simple read tool, though the em-dash construction makes it slightly denser than necessary.
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?
This is a simple zero-parameter read tool with rich annotations and no output schema, so the description carries the main burden of explaining what is returned. It enumerates the key returned values and notes the conditional trial field, which is sufficient for an agent to understand the tool's output at a high level.
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?
The tool has zero parameters, so the schema carries no parameter semantics and the baseline is 4. The description appropriately adds no parameter detail, as there is nothing to document.
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 API request usage for the calling account, including monthly consumption, plan limits, per-minute limits, reset timing, and trial expiration. It is specific about the data returned, though it does not explicitly contrast itself with sibling tools, most of which are fight-data lookups rather than account-usage endpoints.
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 explains what information the tool provides but gives no explicit guidance on when to call it, when not to call it, or which alternatives exist. The trial-related note is useful context, but it is not usage guidance in the sense of routing an agent between tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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