wb_ai_status

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

No annotations are provided, so the description carries the burden; it discloses the important behavioral trait that no model invocation occurs (and thus no credit consumption or side effects), and that local credential/app data is read. It does not spell out auth requirements or side-effect profile beyond that, but for a read-only status probe this is solid disclosure.

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 tight clauses: the first front-loads the purpose and the enumerated data it reports, the second adds the single most important behavioral constraint. No filler, and the crucial restriction is placed last for emphasis.

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?

There is no output schema, and the description explicitly lists the fields an agent will receive (account, token validity, credits, credential file, App version), which is exactly the compensating detail needed. With zero parameters and no annotations, nothing material 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, so the baseline is 4; the schema is empty and there is nothing for the description to compensate for.

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?

States a specific verb+resource (check WorkBuddy AI connection status) and enumerates exactly what is inspected: login account, token expiry, remaining credits, local credential file, App version. The closing note that it starts no model calls distinguishes it from the model/chat siblings, so an agent can route correctly without opening a 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?

The description gives clear context for when this applies (diagnosing connectivity/account state) and an explicit exclusion ('不发起任何模型调用'), steering an agent away from using it as a generation path. It stops short of naming the siblings (wb_ai_models, wb_ai_chat) as alternatives, so it is clear but not fully routing-aware.

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