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

The annotations confirm the tool is safe and read-only, but the description adds vital behavioral context by mentioning 'when the data last changed.' This informs the user about data freshness and the temporal nature of the returned information.

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?

The tool definition is maximally dense and efficient. It is a single, well-constructed sentence that provides all necessary information (what it does, what it returns, and the scope) without any wasted words.

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?

Since there is no output schema provided, the description must fully explain the tool's result. It is completely complete by explicitly listing all five data points (three counts and one timestamp) that the user can expect.

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?

Since the input schema contains zero parameters and 100% coverage, the description does not need to elaborate on parameter meanings. The baseline score is appropriate.

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 is highly specific, detailing not only that it retrieves statistics but precisely which metrics are returned: vendor counts, place counts, category counts, and the data last changed date. This makes the purpose unambiguous and clearly separates it from listing or searching.

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?

While it doesn't explicitly state 'when to use this vs alternatives,' the explicit definition of its resource scope (aggregate counts) implies a clear usage pattern: use this for overview/health checks, whereas sibling tools handle individual resources or searches.

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