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

Annotations already declare read-only, idempotent, open-world, and non-destructive behavior. The description adds meaningful context beyond those: the call is a cheap diagnostic preflight, it returns vendor numbers, and it returns no listening data. This helps the agent set expectations without contradicting the annotations.

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 concise sentences, with the core purpose first, the diagnostic guidance second, and the key limitation last. Every sentence adds value and the structure is easy for an agent to scan.

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 diagnostic tool with no output schema, the description is complete: it states what the tool does, what it returns, what it does not return, and when to invoke it. Nothing essential is missing for correct selection and invocation.

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 and the schema fully covers that fact, so the description bears little parameter burden. It still clarifies that the operation depends on already-stored credentials/token state, which is useful context for why no parameters are needed.

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 action (verify credentials) and a specific result (list vendor numbers readable by the token), then explicitly distinguishes itself from data-returning analytics tools by stating it returns no listening data. This makes its role unmistakable even among many analytics siblings.

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 placement guidance: 'Call this first' because it is the cheapest way to diagnose whether a problem is a wrong token, a wrong vendor number, or a show with no data. This gives an agent a clear decision procedure rather than leaving the choice to inference.

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