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

Annotations already cover readOnlyHint=true and destructiveHint=false, so the description's burden is lowered. It adds the behavioral trait of 'multi-source scoring' and hypothesis-card generation, which is genuine context beyond annotations. However, it does not disclose API-key-gated behavior (MLIT/Gemini) or anything about how scoring aggregates sources, leaving some behavioral detail unstated.

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 core info ('scan a prefecture + goal + hypothesis cards') is front-loaded in the first sentence, which is good. But the entire English text is duplicated verbatim in Japanese, roughly doubling the length without adding information. This bilingual redundancy is wasteful, though not egregious.

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?

An output schema exists, so return values are covered. However, with 10 parameters and only 70% schema coverage, the description should clarify the compact-vs-detailed output_mode behavior and the API-key-dependent features (useGeminiNarrative, includeExternalFreshness), neither of which is addressed. The description is adequate for the core use case but under-specifies the tool's optional, conditional behaviors.

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 70% (goal, limit, prefecture, budgetLevel, output_mode, useGeminiNarrative, includeExternalFreshness have descriptions; horizon, riskTolerance, includeMarkdown do not). The description's only param contribution is restating goal values (investment/store/family/office/development), which are already enumerated in the goal enum in the schema. The description adds no meaning for the three undocumented parameters, so it fails to compensate where the schema is silent.

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 a specific verb ('scan') applied to a resource ('prefecture') with explicit goal types (investment/store/family/office/development) and describes the output format ('hypothesis cards with multi-source scoring'), which distinguishes it from area-report and drill-down siblings. However, no sibling is named explicitly, so the distinctiveness relies on the reader inferring the difference from the output type rather than a stated boundary.

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 when-to-use, when-not-to-use, or alternative-tool guidance. The phrase 'scan a prefecture for undervalued areas' implies a discovery use case, but there is no exclusion of cases where search_area_candidates or drill_down_local_analysis would be more appropriate, which matters given 31 siblings including several area-search tools.

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