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

With readOnlyHint=true and openWorldHint=false, the safety profile is already clear. The description adds useful behavioral context by specifying the data scope ('across chat, search, and navigation requests') and the ranking by occurrence count. It does not overclaim side effects or contradict 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?

Two concise sentences: the first defines exactly what the tool returns, and the second gives a practical use case. There is no filler, and the most identifying information is front-loaded.

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?

Given the simple two-parameter schema, rich schema descriptions, output schema, and read-only annotations, the description is nearly complete. It could still strengthen selection accuracy by explicitly differentiating from get_top_languages, but it otherwise provides enough context for correct 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 input schema already covers all parameters with detailed descriptions and defaults, so the description carries no parameter burden. Baseline 3 applies because the description adds no extra parameter detail beyond what the schema provides.

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 clearly names the resource (locales), defines them with BCP-47-style examples, and states they are ranked by occurrence count across chat, search, and navigation requests. This distinguishes the tool from siblings like get_top_languages and get_top_geographies by focusing on combined language/region locale data.

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 an explicit intended use: understanding which languages/regions are served and where content gaps may exist. It does not explicitly mention when not to use it or name alternatives such as get_top_languages, so it falls short of the highest level.

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