get_api_usageUse to inspect request usage and current plan limits for the supplied X-API-Key. This is account/API-quota metadata, not vehicle data.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| data | No |
Changes observed during successful MCP inspections.
Output schema / (root)Previous value: -nullNew value: +{
+ "additionalProperties": true,
+ "description": "Structured JSON returned by the canonical Apibara Vehicle Auction Data API. Source-dependent fields may be null or absent.",
+ "properties": {
+ "data": {
+ "additionalProperties": true,
+ "type": "object"
+ }
+ },
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds value by specifying the data type (account/API-quota metadata) and tying it to the X-API-Key, which gives agents a better mental model of what the response will contain without relying solely on the output schema.
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 only two sentences and front-loads the primary use case ('Use to inspect...'). The second sentence proactively prevents category confusion, and every word contributes meaning.
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 the tool's simplicity (no parameters), the presence of a full output schema, and thorough annotations, the description is complete. It clearly explains the resource being queried, disambiguates from siblings, and leaves no operational 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?
The tool has zero parameters, so there is nothing for the description to add beyond what the empty input schema already shows. The baseline for a no-parameter tool is 4, and the description does not introduce any unnecessary parameter-related details.
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 names a specific verb ('inspect'), the resource ('request usage and current plan limits'), and the relevant credential ('supplied X-API-Key'). It also explicitly excludes vehicle data, which clearly distinguishes it from the vehicle-related sibling tools.
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 gives a clear purpose and a negative discriminator ('not vehicle data'), making it obvious when to use this tool instead of the vehicle-focused siblings. However, it does not name specific alternative tools or provide more granular when-not conditions, so it falls short of a 5.
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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