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不動産ダッシュボード

open_dashboard
Read-only

Open visualization dashboard. 2D map or PLATEAU 3D view. MCP Apps UI. | 可視化ダッシュボードを開く。2Dマップ/PLATEAU 3Dビュー。MCP Apps UI対応。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
areaNo初期表示エリア
modeNoダッシュボード表示モード。3dを指定するとPLATEAU 3Dビューアを開く
layerNo初期レイヤー
prefectureNo都道府県名(和名/英名/ISO 3166-2 コード対応)愛知県
initialModeNoデュアルモード切替。investment=不動産投資モード(デフォルト)、store=店舗出店戦略モード
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)
propertyTypeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
areaYes
modeYes
layerYes
prefectureYes
attributionYes
initialModeNo
dashboardUrlNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the tool is clearly non-destructive. The description adds little beyond that, such as mentioning MCP Apps UI, which is a minor UI detail rather than a behavioral trait. No contradiction exists, but value added over annotations is minimal.

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

Conciseness4/5

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

The description is brief and front-loaded with the core action and modes. The Japanese translation is redundant but not harmful, and the whole is under 30 words. Slight waste in duplication prevents a 5.

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

Completeness3/5

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

With an output schema present and the tool being a simple 'open' action, the description is somewhat adequate. However, it does not convey what the dashboard displays, how parameters interact, or what the user will see, leaving the agent to rely on the schema and output schema. Given seven parameters, a bit more context would help.

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 description coverage is 86%, with all parameters except propertyType having descriptions. The tool description adds no extra parameter context; it does not explain relationships, defaults, or the meaning of propertyType. Since the schema already does the heavy lifting, a baseline of 3 is appropriate.

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

Purpose4/5

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

The description states a clear verb ('Open') and resource ('visualization dashboard'), and specifies two modes (2D map / PLATEAU 3D view). This is specific enough to distinguish from the data-analysis siblings, although it does not explicitly name which sibling it is not, so it stops short of a 5.

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

Usage Guidelines3/5

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

The description implies its purpose (use to open a dashboard) and lists modes, but provides no explicit guidance on when to choose 2D vs 3D, nor when not to use this tool or which alternative to pick. Basic context is present, exclusions are absent.

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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TDQS

B3.3/5.0
Disambiguation3/5

Many tools have overlapping purposes (e.g., analyze_renovation_yield vs recommend_renovation_targets, multiple scoring functions). While descriptions provide some differentiation, an agent could easily confuse tools like assess_property_risk, assess_family_friendly_score, and composite_value_score, all of which aggregate multiple axes into a single score.

Naming Consistency4/5

Most tools follow a verb_noun pattern (analyze_, assess_, get_, simulate_, etc.), but a few deviate with noun phrases (composite_value_score, portfolio_optimizer, scenario_what_if) or adjective-led names (quick_visual_summary). The pattern is largely consistent with minor exceptions, making it predictable overall.

Tool Count2/5

With 33 tools, the surface is quite heavy and exceeds the 25-tool threshold. While the server covers a broad domain (real estate analysis, simulation, contract review, reporting), many tools could be consolidated (e.g., multiple scoring functions). The count feels overwhelming for an agent to manage efficiently, though the scope is comprehensive.

Completeness4/5

The tool set covers the primary workflows of real estate intel: search/discovery, data retrieval, scoring, simulation, reporting, and contract support. Minor gaps exist (e.g., no direct property transaction listing lookup or lease-specific analysis), but these are not core to the server's stated purpose. The lifecycle of analysis is well-supported.