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

Annotations already declare readOnly, idempotent, openWorld, and non-destructive behavior; the description adds useful context beyond those: the data source (dashboard.e-stat.go.jp), the no-auth requirement, and the concrete nature of the returned metadata (cycle/regional combinations). No contradiction with 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 sentences pack in the action, return fields, usage sequencing, and source/auth note without redundancy. Key operational guidance is front-loaded before supporting details.

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?

With a complete input schema, an output schema, and rich annotations, the description covers everything an agent needs: what the tool returns, when to invoke it, and that no auth is needed. There are no material gaps.

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 100% with both parameters (indicator_code and lang) documented, including an example code and default value. The description adds no new parameter semantics beyond what the schema already provides, which is acceptable under the baseline.

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?

Description uses a specific verb ('Get metadata') with a clear resource ('one e-Stat Statistics Dashboard indicator code') and enumerates the returned fields (name, unit, source survey, valid date range, cycles). It also distinguishes itself from the data-fetching sibling by referencing estat-japan-dashboard.get_data, making its role unambiguous.

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?

Explicitly instructs the agent to call this tool BEFORE estat-japan-dashboard.get_data to confirm units and available cycles, and states the source and auth requirements. This is direct when-to-use guidance with a named alternative.

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