simulate_landscape_impact

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

Annotations indicate readOnlyHint=true and destructiveHint=false. The description adds context by specifying the use of PLATEAU 3D buildings and SunCalc, implying a non-destructive simulation. It does not contradict annotations. The additional detail about data sources enhances transparency beyond the 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?

The description is extremely concise: two sentences (one English, one Japanese) that front-load the core purpose. Every word is necessary; no fluff. The structure is efficient for an AI agent to parse quickly.

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 the complexity of the tool (7 parameters, no output schema), the description adequately states what it does and its data sources. However, it lacks information about the output format or return value. Since there is no output schema, the description could mention whether it returns imagery, data, or a report. Nevertheless, for a simulation tool, the core purpose is clear, so a slight deduction is appropriate.

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 86%, meaning most parameters are already described inline. The tool description does not add further semantics beyond what the schema provides. For example, 'prefecture' is described in the schema, and the description does not clarify its usage. 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's function as a sunlight/shadow simulation using PLATEAU 3D buildings and SunCalc. The dual-language text (English and Japanese) leaves no ambiguity. Among siblings, no other tool explicitly simulates landscape impact, so it is well-differentiated.

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 implies usage for analyzing sunlight/shadow impact of nearby buildings but provides no explicit guidance on when to use it versus similar tools like 'simulate_aichi_future' or 'scenario_what_if'. A statement about typical use cases (e.g., evaluating solar access for real estate) would improve clarity.

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