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

Annotations already cover readOnlyHint, idempotentHint, and destructiveHint. The description adds behavioral context beyond these: it promises 'official values only' with no judgment, indicates a single aggregated call ('one call'), and specifies a data range for vacancy. It does not discuss rate limits or pagination, but the output schema covers return structure.

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 concise sentences, each serving a distinct purpose: scope/data categories, behavioral promise, and input format. No filler or redundancy, with key facts 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 an output schema exists and annotations cover safety, the description fully supports tool selection and invocation. It covers what the tool offers, how to specify the municipality, the optional fields concept, and the raw-data nature, making it complete for correct usage.

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% and both parameters are well-described. The description adds useful semantic context by explaining what the data fields mean (e.g., vacancy years 2003–2023, nearest-station ridership trend) and gives input examples, although the examples duplicate the schema description. This enriches parameter understanding beyond the schema.

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 states it provides official Japanese government data for municipalities, listing specific data categories (vacancy, ridership, hazard, land price, livability). It distinguishes itself from sibling station/toilet tools by focusing on municipality-level official data, and the 'No scores, no judgment' note clarifies its non-analytical nature.

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 strong context for when to use it: for official municipal data on multiple topics. It does not explicitly mention alternatives or when not to use it (e.g., for station-specific alerts), but the scope is clear enough given the sibling list.

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