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

Annotations already declare read-only/idempotent behavior; the description adds beyond that by disclosing the response format, the data source (andmed.stat.ee), no-auth requirement, and license. It does not go into response pagination or error behavior, but combined with annotations this gives ample transparency.

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 tight sentences cover purpose, output format, prerequisite, and licensing, with a compact example. Every sentence earns its place and the most important 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?

For a two-parameter read-only query tool with a full input schema and output schema, the description covers the necessary workflow (metadata-first), key parameter semantics, output format, and access/licensing. 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?

Schema coverage is complete and its individual field descriptions already explain code/selection/filter/values. The tool description supplements this with a concrete births/deaths/natural-increase example and the 'top' filter pattern for most recent years, which clarifies how to combine dimensions in practice.

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 opens with a specific verb and resource ('Run a statistical query against an Estonia statistics table') and states what the operation produces (JSON-stat2 with labeled dimensions and numeric values). It differentiates itself from sibling metadata tools by explicitly instructing that table_metadata must be called first.

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 clear context by naming table_metadata as a required preliminary call and explains that valid codes must be discovered before querying. It doesn't explicitly state when not to use the tool relative to similar country table_query siblings, but the prerequisite and example make selection straightforward.

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