Get Quota

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

With no annotations, the description carries the full behavioral burden and does so well: read-only, no quota consumption, worst-utilised model ordered first, rolling-window models mixed with monthly caps, and a warning that the route is undocumented and may change without notice. This is exactly the extra context an agent needs before relying on the result.

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?

Front-loads the purpose, then layers in return shape, the rolling-window caveat, and the volatility warning in three tight sentences. Every clause earns its place with no filler.

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?

With no output schema, no annotations, and no parameters, the description alone must supply the result semantics — and it does, naming the fields returned and their ordering. An agent has everything needed to call it and interpret the response.

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 takes zero parameters, so per the baseline there is nothing for the description to disambiguate. The description accurately implies a parameterless query against a fixed endpoint, though it adds no parameter-level meaning because none exists.

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 verb+resource ('Report the account's token quota per model') and enumerates exactly what is returned (used, cap, remaining, reset date). It is trivially distinguishable from every sibling, which are all inference/utility tools rather than account-quota reporting.

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?

Gives clear context for when this is the right call: read-only, free, does not consume quota, and sourced from the dashboard backend. There are no real alternatives among the siblings to route against, so no explicit exclusion is needed, but it stops short of stating a concrete trigger condition.

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