forecast_land_price_trend

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

Annotations already indicate readOnlyHint=true and non-destructive. The description adds value by detailing the analytical methods (linear regression, moving average) and outputs (CAGR, confidence interval, investment signal), which are not captured by annotations. No contradictions.

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 a single compact sentence (plus Japanese translation) that conveys essential information without excess. It is front-loaded and every phrase adds value.

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 7 parameters and no output schema, the description is brief but covers the core purpose. However, it lacks details on return values (e.g., format of CAGR, confidence interval) and does not explain the '10 prefectures' constraint. Adequate but could be more thorough.

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 description coverage is high (86%), so the schema already documents most parameters. The description adds minor context (e.g., '10 prefectures' implicit limitation) but does not elaborate on parameter meaning beyond schema. Baseline 3 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 clearly states the tool forecasts land price trends using linear regression and moving average, and specifies outputs (CAGR, confidence interval, investment signal). It also notes coverage of 10 prefectures, which distinguishes it from siblings like 'forecast_demographic_shift' or 'get_real_estate_macro_snapshot'.

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?

No explicit guidance on when to use this tool vs alternatives. The description does not mention prerequisites, context, or when to choose one method over another. Siblings cover related analyses but no comparative advice.

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