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Audit Estimate Against Fair Price

audit_estimate
Read-only

業者が提示した見積金額が適正かを、HORIZON SHIELDの適正レンジ(souba-db, 大賀俊勝 実務監修)と照合して判定する。手元に具体的な見積額がある時に使う。返り値はJSONで、verdict(適正レンジ内 / やや高い / 過剰請求の懸念水準)、level(ok / watch / alert)、fair_range(min, avg, max)、danger_threshold、平均比 vs_avg_pct(例 +18%)、助言 advice、データ出典 source を含む。工事名が見つからない場合、近い候補があれば did_you_mean として返す。単価(平米など)建ての工事に総額らしい金額を渡した場合は unit_mismatch の案内を返す。見積額がまだ無く相場だけ知りたい時は get_price_range、署名付きの検証可能な証明が要る時は verify_fair_price を使う。Japan only, JPY。 / Audits whether a contractor quoted price for a Japanese construction or renovation job is fair by comparing it against HORIZON SHIELD fair-price ranges (souba-db). Use when the user already has a specific quoted amount. Returns a JSON object with verdict, level (ok, watch, alert), fair_range (min, avg, max), danger_threshold, percentage gap versus the average (vs_avg_pct, e.g. +18%), advice, and data source. If the work name has no match, close candidates may be returned as did_you_mean. If the work is priced per unit and the amount looks like a total, a unit_mismatch notice is returned instead. For the typical range only use get_price_range; for a signed verifiable attestation use verify_fair_price. Trigger phrases: この見積もり高い?, 適正?, ぼったくり?, 妥当?, is this quote fair, am I being overcharged, is this a rip-off.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workYes工事名(日本語)。材料やグレード込みで具体的に。例: 外壁塗装 シリコン。部分一致で照合するため曖昧だと別カテゴリにヒットしやすい。未マッチ時は近い候補が did_you_mean で返ることがある。
regionNo(任意) 地域。都道府県か市名(例: 神奈川県, 平塚市)か kanto/kinki/chubu/tohoku/other。渡すと地域係数を掛けたレンジで判定し、基準値も返す。 / (optional) Prefecture, city, or region key. The verdict then uses the regionally adjusted range; base values are returned too.
quoted_priceYes業者提示の金額(円, 数値)。一式見積はその総額。税込/税抜は正規化せず、渡した数値をそのまま適正レンジと照合する。

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNoHow 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.
levelNook / watch / alert
adviceNo助言
lookupNook = 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.
verdictNo判定
fair_rangeNomin/avg/max
vs_avg_pctNo平均比(例 +18%)
source_readNotrue 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_meanNoNear matches, when an exact match was not found.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

With readOnlyHint already covering safety, the description adds substantial behavioral context: full return payload (verdict, level, fair_range, danger_threshold, vs_avg_pct, advice, source), edge-case handling (did_you_mean, unit_mismatch), and JP-only/JPY scope. Doesn't state rate limits or failure modes, but the fallback behaviors are disclosed.

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?

Dense but earns its length: purpose, usage, return fields, edge cases, alternatives, and trigger phrases, all in two language blocks. Slightly repetitive across languages but well front-loaded.

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?

Output schema exists yet the description still conveys verdict semantics and edge cases, plus sibling routing, JP-only scope, and trigger phrases. Complete for an agent to select and invoke correctly.

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 100% with rich per-parameter descriptions, so baseline 3 applies. The description adds minor complementary info (total vs unit mismatch, JPY, no tax normalization) already implied by schema.

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?

States a specific verb (audit/判定) and resource (contractor quoted price vs HORIZON SHIELD fair-price ranges), and explicitly distinguishes from siblings get_price_range and verify_fair_price. Bilingual, front-loaded.

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

Usage Guidelines5/5

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

Explicit when-to-use ('手元に具体的な見積額がある時に使う') and names alternatives with their conditions: get_price_range for range-only, verify_fair_price for signed attestation. Trigger phrases reinforce context.

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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