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

With no annotations provided, the description carries the full burden of behavioral disclosure, and it does so well. It clarifies whose balance is returned (the API key's creator), notes that purchased top-ups never expire, and discloses the required authorization scope (read:ai). These details go beyond the empty schema and give an agent actionable expectations about the operation's nature and requirements.

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 tight two-sentence block with no filler. The first sentence front-loads the resource and its key attributes, while the second efficiently adds the usage directive and authorization requirement. Every sentence earns its place, and the structure is highly scannable.

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 (zero parameters, no output schema, no annotations), the description is complete. It covers what the tool returns, whose data it reflects, when it should be called, and what authorization is needed. Nothing an agent needs to decide whether and how to invoke this tool is missing.

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 with 100% schema coverage, so the baseline for parameter semantics is 4. There are no parameters to document, and the description adds value by outlining exactly what the response contains (allowance, top-ups, total, reset date, enabled flag), which helps an agent interpret the return value despite the lack of an 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 the tool returns the AI credit balance for the API key's creator, explicitly listing the components: monthly allowance remaining, purchased top-ups, total available, reset date, and the AI Course Builder enabled flag. This specific verb+resource distinguishes it from all sibling get_* tools, particularly hivelearn_get_ai_job and the generation 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 instruction 'Check this before generating' provides a clear and explicit usage context, signaling the tool is a pre-flight check before AI generation. It also states the required scope (read:ai), acting as a prerequisite. However, it does not explicitly name the sibling generation tool or state when not to use it, so it stops short of full exclusion guidance.

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