Contract support package: generate risk matrix, price negotiation anchors, recommended clauses from neighborhood/property data. Markdown + branded PDF. | 売買契約支援パッケージ。リスクマトリックス・価格交渉アンカー・推奨特約を生成。
| Name | Required | Description | Default |
|---|---|---|---|
| ward | Yes | 名古屋市の区名 (例: 中区, 中村区) | |
| price | Yes | 取得予定価格 (円) | |
| chochou | No | 町丁目名 (省略時は区全体) | |
| floorArea | Yes | 専有面積 (㎡) | |
| buildingAge | Yes | 築年数 | |
| propertyType | No | 物件種別 | mansion |
| proposedClauses | No | すでに検討中の特約・条項（任意） |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is known. The description adds the output format (Markdown + branded PDF), which is useful, but it does not disclose any other behavioral traits such as whether the tool generates files, requires external services, or has rate limitations. Beyond the output format, it adds little 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 concise, with the core purpose and deliverables front-loaded. The bilingual inclusion (English + Japanese) doubles length but likely serves the target audience; it's not verbose, and every sentence contributes to understanding the tool's output.
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?
With 7 parameters, no output schema, and a generation-style tool, the description should clarify what 'package' means structurally and when to use it vs. simpler assessment tools. It mentions output formats but not the package's contents or any limitations. Given the complexity and lack of output schema, the description is adequate but not fully complete.
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 100%, so all seven parameters have in-schema descriptions. The description's phrase 'from neighborhood/property data' loosely ties to the parameters but doesn't add any per-parameter meaning beyond the schema. As baseline for full coverage, a score of 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 states a specific verb ('generate') and resource ('contract support package'), and enumerates concrete deliverables (risk matrix, price negotiation anchors, recommended clauses). It differentiates from sibling tools like assess_contract_risk or assess_property_risk by framing the output as a consolidated package rather than a single assessment.
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 context ('from neighborhood/property data') and output format (Markdown + branded PDF), but it does not explicitly state when to choose this tool over alternatives like assess_contract_risk for a lighter analysis, nor does it mention any exclusions. The guidance is implicit rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.