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

Beyond the annotations (readOnly, idempotent, non-destructive), the description discloses an important behavioral trait: calling the tool can start the sign-in flow. It also explains the connection requirement, providing useful context that annotations do not capture.

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?

Three short sentences, each earning its place: what the tool returns, when to use it, and the auth prerequisite/side effect. It is front-loaded with the core purpose and contains 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?

For a zero-parameter, read-only account lookup with no output schema, the description is complete: it states the resource, the returned fields, when to call it, and the sign-in side effect. Nothing an agent needs to invoke it correctly 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, so there is no parameter semantic burden on the description. The input schema already covers the argument space completely and the description sensibly omits parameter details. This matches the 0-params baseline of 4.

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 uses a specific verb and resource: 'Get the connected Photo AI Studio account' and enumerates the exact returned information (credit balance, total predictions, membership date). This clearly differentiates it from sibling tools like generate_photo or get_prediction.

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 explicitly tells the agent when to call this tool: 'Check this before generating, because every photo costs credits.' It also gives prerequisites and a side effect ('Requires a connected Photo AI Studio account. Calling this tool starts the sign-in flow.'), though it does not discuss when not to use it or name alternatives.

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