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sugukurukabe

japan-real-estate-intel

evaluate_store_location

Read-only

Assess store location suitability using foot traffic, transport access, and competitor distribution to identify optimal retail sites across 10 prefectures.

Instructions

Evaluate store location suitability considering foot traffic, transport, competitor distribution. 10 prefectures. | 店舗出店適地評価。人流・交通・競合店分布を考慮したスコアを算出。全10都道府県。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
prefectureNo都道府県名(和名/英名/ISO 3166-2 コード対応)愛知県
cityYes市区町村(例: '名古屋市中村区')
neighborhoodNo町丁目(例: '名駅南1丁目')。v2.4 では町丁目レベル実データに対応(対応都道府県のみ)
storeTypeYes出店を検討する店舗タイプ
radiusMNo競合・施設を検索する半径(メートル)
customWeightsNoカスタム重み付け(省略時はタイプ別デフォルト)
includeMarkdownNo
Behavior4/5

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

Annotations (readOnlyHint=true, destructiveHint=false) indicate a safe read operation. The description adds behavioral context: it considers foot traffic, transport, competitor distribution, and produces a score. It also notes the 10-prefecture limitation, providing useful scope information.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with English, and includes a Japanese translation. Every sentence is meaningful with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 7 parameters, required fields, and no output schema, the description lacks details on scoring methodology, output format, or interpretation. It covers purpose and scope but leaves significant gaps for effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is high (86%), so the input schema already documents most parameters well. The description adds no per-parameter details but gives overall context for the parameters used. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Evaluate') and resource ('store location suitability') with concrete criteria (foot traffic, transport, competitor distribution). It clearly distinguishes from sibling tools, none of which mention 'store location' evaluation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool vs alternatives like search_area_candidates or assess_property_risk. The description only mentions geographic scope ('10 prefectures') but does not explicitly say when not to use it.

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

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