predict_corporate_demand

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

Annotations indicate readOnlyHint=true and destructiveHint=false, but the description adds limited behavioral context. It does not clarify if it returns a single score or multiple, or the scope of prediction (e.g., one prefecture vs all). 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 succinct sentences (English and Japanese) convey the core purpose without extraneous text. Could be structured with bullet points for clarity but is acceptably concise.

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?

No output schema is provided, and the description does not explain the return format (e.g., score range, units). The mention of '10 prefectures' conflicts with the single prefecture parameter, suggesting incomplete context.

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 high (80%), so the description adds marginal value. It mentions 'manufacturing, office, retail demand scores' but propertyType enum includes office, logistics, commercial, mixed – retail is not directly listed, creating minor ambiguity.

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 predicts corporate demand scores for manufacturing, office, and retail across 10 prefectures. This distinguishes it from sibling tools like compare_prefectures 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 guidance is provided on when to use this tool versus alternatives. The description does not specify use cases or exclusions, leaving the agent to infer.

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