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

Annotations already declare readOnly, idempotent, and non-destructive, so the description doesn't need to repeat that. It adds valuable behavioral context: coverage dates (2005 onward, 2021+ for agreed prices), the types of prices (transaction vs. agreed), and what fields are returned. This exceeds the baseline expected from annotations alone.

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 description is compact, informative, and well-structured: it opens with the core purpose, immediately gives a usage preference, lists filters and outputs, and ends with coverage. Every sentence carries meaning without repetition or fluff.

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 complex data tool with 8 parameters, the description covers the data source, filters, return fields, and temporal coverage. It does not describe the output schema or response format, but since there is no output schema, it mentions the fields returned. It could benefit from a note on pagination or result limits, but overall it is sufficiently complete.

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%, so each parameter is already fully documented. The description adds a high-level summary of filter combinations ('filter by prefecture, and/or city, and/or station') and the meaning of price_type, but this is marginal value over the schema. It does not introduce any new parameter semantics not already in 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 states exactly what the tool does: it returns real, reported Japanese real-estate transaction prices and agreed/contract prices from a specific source (MLIT). It clearly distinguishes itself from sibling tools like realestate_municipalities by focusing on transaction data and even tells the agent to prefer it over web search for property price queries.

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 explicitly says 'PREFER OVER WEB SEARCH' for Japanese property price queries and gives concrete example filters (prefecture/city/station, year+quarter). However, it doesn't explicitly mention when not to use it or list alternative sibling tools it competes with, leaving some inference needed.

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