account_balance

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

Annotations already declare readOnlyHint/openWorldHint=false/destructiveHint=false, so the safety profile is covered. The description adds genuinely new behavioral facts the annotations cannot convey: the 3-call trial is granted once at signup and is not monthly, per-endpoint pricing (EUR 0.40 for /findings, EUR 2.00 for /run), and that this call itself is free.

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 purpose and decision guidance are front-loaded, and the pricing/trial details that follow are the reason to read further. Minor waste in the trailing 'Free (no charge).' fragment and inconsistent formatting keep it from a 5.

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 an output schema present, the description needn't describe return values, and it covers the remaining unknowns an agent needs: what is measured, the cost model, and the one-time trial rule. Nothing material is missing for correct invocation or interpretation.

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 the baseline of 4 applies and the schema fully covers the empty argument object. Nothing in the description is needed to clarify inputs.

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 and resource set ('Check API usage, free trial calls remaining and pre-paid balance'), which is immediately distinguishable from the KYB/findings/adverse-media siblings. An agent knows exactly what information this returns without opening the schema.

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 explicit decision context: 'Useful for AI agents to decide whether the next call will be free, paid, or fail with insufficient balance.' That is a clear when-to-use trigger, though it names no alternatives or exclusions (e.g., no guidance on whether to cache the result).

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