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

The readOnlyHint annotation already marks this as a safe read, so the bar is lower. The description still adds value by naming the returned fields (name, role, teams, locale) and framing it as a credential/subdomain validation call, though it says nothing about auth failure behavior or errors.

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, front-loaded with the core purpose before the practical use case and the raw endpoint. Every sentence carries distinct information with 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 tool with no output schema, the description supplies both what comes back (name, role, teams, locale) and why you would call it. 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 takes zero parameters, so parameter semantics default to the baseline of 4. The description correctly does not invent or discuss inputs, and nothing is left ambiguous on the calling side.

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 (Fetch) and resource (the Kayako user these credentials belong to), and the phrase 'these credentials belong to' cleanly separates it from kayako_get_user, which targets an arbitrary user. An agent can distinguish the two siblings without opening either 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?

Gives a concrete use case — 'a cheap way to confirm the subdomain and credentials work' — which tells the agent when this tool is the right call. It implies the alternative (get_user for other users) but never states an explicit when-not or exclusion.

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