Detect the callee's language

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

Annotations already declare readOnlyHint=true and openWorldHint=false, and the description adds genuinely new context: the result is an inference from country code and/or sample text rather than an authoritative answer, and it must be confirmed with the user. This heuristic/uncertainty disclosure is exactly the kind of trait annotations cannot express.

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 sentences with the core capability front-loaded and the confirmation caveat appended where it matters. Nothing is wasted, though the second sentence could be folded more economically.

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, so the description should ideally indicate what comes back (language name vs. code, confidence). It also does not address the notable fact that both parameters are optional — an agent has no guidance on what happens if neither is supplied.

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?

Schema description coverage is 0%, so the description carries the burden and does map both parameters ('destination number's country' to `to`, 'a sample of text the person wrote' to `sampleText`). It adds no format details such as expected number format (E.164) or what an adequate sample text looks like, so it only partially compensates.

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 verb and resource ('Suggest the call language') and names the two inputs that drive the inference, so an agent knows exactly what the tool produces. It does not explicitly differentiate itself from the sibling list_languages, which is the most likely confusion, so it stops short of a 5.

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 an important usage cue — results are suggestions and must be confirmed with the user — which implies this belongs early in a call-preparation flow. However, it never says when to prefer this over list_languages or what to do when neither input is available, so routing guidance is only implied.

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