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

Annotations already establish that this is a safe, read-only, closed-world call, so the bar is lower. The description adds genuinely useful behavioral context beyond that: it explains that builds and edits consume credits while data, domain, and preview tools do not, which an agent needs in order to interpret the credit figure it returns.

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?

Two sentences, both earning their place. The usage triggers come first in a parallel, scannable list, followed by the credit-accounting note that qualifies the returned values.

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 parameterless read tool with an output schema and full annotation coverage, this is complete: it says what triggers the call, what it reports, and how to interpret the credit number. Nothing needed 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 takes zero parameters and the schema is empty, so the baseline is 4 and there are no parameter semantics to compensate for. The description correctly avoids inventing arguments.

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 states a specific retrieval action and enumerates exactly what it returns: connected account, plan, remaining credits, and workspaces. No sibling tool in the list covers account identity, so an agent can differentiate it without cross-referencing schemas.

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 user-intent triggers ('when the user asks which account is connected, which plan, how many credits, which workspaces'), which is strong when-to-use guidance. It stops short of naming alternatives or conditions where this tool should not be used, so it is not a full 5.

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