HORIZON SHIELD

This connector has been deprecated

Superseded by the io.github.ogasurfproject-jpg/horizon-shield listing at https://mcp.horizonshield.dev, which is the URL published in the official MCP registry. The endpoint behind this listing is the same server and stays reachable.

Get Fair Price Range

get_price_range

Read-only

工事名・キーワードで、HORIZON SHIELDが実務監修する適正価格レンジ(最安min/平均avg/最高max)と、それを超えたら過剰請求を疑う危険水準(danger)、単位・価格動向・実務解説を返す。建設・リフォーム費用が適正か数値で確かめたい時に使う(例: 外壁塗装, 給湯器, ユニットバス, クロス)。 / Returns the fair price range (min, avg, max), the overcharge danger threshold, unit, price trend and field notes for a Japanese construction or renovation job. Japan-specific pricing in JPY. Use to numerically check whether a cost is fair.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`query`	Yes	工事名やキーワード(日本語)

Output Schema

TableJSON Schema

Name	Required	Description
`work`	No	工事名
`count`	No	How many records matched. 0 means the source was read and nothing matched. It never means the source could not be read, that returns isError: true.
`lookup`	No	ok = the source was read and something matched. absent = the source was read and nothing matched. A source that could NOT be read never appears here: that returns isError: true and makes no claim about what does or does not exist.
`fair_range`	No	適正レンジ
`source_read`	No	true on every successful result. A failed lookup does not return a result at all, so this is never false, it is declared so a consumer can assert on it.
`did_you_mean`	No	Near matches, when an exact match was not found.
`danger_threshold`	No	危険水準

TDQS

A4.5/5.0

Behavior4/5

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

Annotations declare readOnlyHint=true and destructiveHint=false, so the description need not repeat safety. It adds value by enumerating the full return payload (min/avg/max, danger, unit, trend, notes) and specifying Japan-specific JPY pricing, providing behavioral context beyond what annotations offer.

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, bilingual but efficiently packed with all key information: what it returns, the scope (Japanese construction), and usage. No wasted words; it front-loads the action and result immediately.

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

Completeness5/5

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

Given an output schema exists, the description need not detail return fields, but it still lists the key outputs. It covers purpose, usage context, regional specificity, and examples. The tool is simple (1 parameter), and the description fully equips an agent to invoke it correctly.

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

Parameters4/5

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

The single parameter 'query' is fully described in the schema (100% coverage). The description enhances schema meaning by listing example keywords (外壁塗装, 給湯器, ユニットバス, クロス), clarifying the expected input domain and giving the agent concrete usage patterns.

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 uses a specific verb 'Returns' and clearly identifies the resource: fair price range with min/avg/max, danger threshold, unit, trend, and field notes. It distinguishes itself from sibling tools like verify_fair_price or get_fair_price_sources by focusing on retrieving the range data rather than verifying or sourcing it.

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

Usage Guidelines4/5

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

The description explicitly states when to use this tool: 'Use to numerically check whether a cost is fair' and gives concrete examples of queries. It does not mention alternatives or exclusions, but the intent is clear enough to guide selection among siblings.

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

A4.1/5.0

Disambiguation4/5

Most tools have distinct purposes: audit_estimate for detailed quote diagnosis, get_price_range for typical ranges, preview_reverse_estimate for early-stage direction, verify_fair_price for tamper-evident records. However, audit_estimate, get_price_range, and preview_reverse_estimate overlap in the price-checking domain, and verify_fair_price vs verify_integrity_claim could be confused (both involve SHA-256 verification), though descriptions clarify the opposite postures.

Naming Consistency4/5

Most tools follow a verb_noun pattern (audit_estimate, check_red_flags, get_price_range, list_cost_categories, search_cost_category, suggest_ehn, verify_fair_price). Minor deviations: create_ap2_fairness_attestation is longer and more specific, and get_agent_card/get_estimate_reading_guide/get_fair_price_sources/get_jccdb_dataset_info all start with 'get' but vary in noun phrasing. Overall consistent and predictable.

Tool Count4/5

14 tools is within the ideal 3-15 range, and each tool serves a distinct function in the domain of construction estimate auditing and fair-price verification. Slightly on the higher end but justified by the breadth of features (price lookup, audit, attestation, verification, data sources, educational guides).

Completeness4/5

The server covers the core workflow: lookup price ranges, audit specific quotes, check red flags, generate attestations, verify claims, and access data sources. Minor gaps: no tool for submitting new price data or updating categories, and no direct tool for comparing multiple quotes side-by-side, but agents can work around these with existing tools.

Resources

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