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

The description adds substantial context beyond the annotations: monthly renewal on the billing date, no rollover, which actions consume credits, per-action rates, the effect of running out, and the meaning of `unlimited`. The annotations already mark it as a safe read, and the description builds on that with rich operational semantics.

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 front-loaded with the core purpose, but it is far too long for a simple quota-checking tool. It enumerates many specific prices, edge cases, and implementation details that could mostly live in linked documentation, making it dense and harder to scan.

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 that there are no parameters and no output schema, the description is unusually complete. It explains what the quota represents, how it is consumed, what happens when it is exhausted, and how to interpret special values like `unlimited`.

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 baseline is 4. The description also clarifies return-related concepts such as `rate` and `unlimited`, which adds some useful meaning even though there is no output schema.

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 states that the tool returns AI credits used and remaining for the month, with organization-level scope. It is specific about what is measured and how the pool works, but it does not explicitly distinguish itself from related usage tools such as get_message_usage, get_x_usage, or get_automation_usage.

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?

It gives a concrete usage scenario: 'Check it before planning a carousel of several images.' It also explains what happens when credits run out, which helps the agent understand why to call it. However, it does not explicitly state when not to use it or name alternative tools.

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