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Japan Real Estate Transaction Prices (MLIT)

Real estate prices published by MLIT, by municipality

realestate_prices_by_municipality
Read-onlyIdempotent

What real estate transaction and contract prices has MLIT (Japan) published for this municipality and quarter? Give a 5-digit municipality code and up to 8 quarters (YYYY-Qn). Per quarter and per classification (never pooled): records_published, no_records_published or unknown with a reason, record counts, min/median/max computed by us (null below 5 values), and a capped sample of records as published. Carries the required MLIT credit. Statistics as published; not an appraisal or advice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toNoLast quarter, e.g. 2025-Q4 (default: same as from). At most 8 quarters per request.
fromYesFirst quarter, e.g. 2025-Q1 (Q1 = Jan-Mar). Transaction prices start at 2005-Q3, contract prices at 2021-Q1.
sample_sizeNoNumber of published records to include as a sample, 0-50 (default 10). total and truncated tell how many matched.
property_typeNoOptional filter on MLIT's transaction type: land (宅地(土地)), land_and_building (宅地(土地と建物)), used_condominium (中古マンション等), agricultural_land (農地), forest_land (林地).
municipality_codeYes5-digit Japanese municipality code, e.g. 13101 (Chiyoda, Tokyo). Find codes with realestate_municipalities. Unknown codes are rejected, not guessed.
price_classificationNotransaction (MLIT 不動産取引価格情報), contract (MLIT 成約価格情報) or both (default).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
termsYesURL of the terms of service.
sampleYes
statusYesrecords_published = at least one quarter has published records matching the query; no_records_published = every quarter was answered and none has matching records; unknown = nothing found and at least one quarter could not be determined (see quarters[].unknown_reason). An upstream failure is never reported as no records.
completeYestrue when no quarter is unknown.
quartersYes
provenanceYesFreshness receipts for every upstream source used.
answered_atYes
attributionYesRequired credit (MLIT API terms, Article 7; credit_ja is the required wording) and the statement that counts and statistics are computed by MK Career Planning. Keep it when you pass results on.
legal_noticeYes
municipalityYesAs published in MLIT's municipality list (XIT002). Null when the list could not be read.
retrieved_atYesEarliest time the data used here was retrieved from MLIT (cached answers keep their original retrieval time).
computed_noteYes
quarters_coveredYesQuarters actually answered (records_published or no_records_published).
small_sample_minYesStatistics with fewer values than this return only n (min, median and max are null).
quarters_requestedYes
classification_noteYesTransaction and contract prices are summarised separately; the same deal may appear in both datasets.
max_quarters_per_requestYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Adds real behavioral context beyond the annotations: results are never pooled, always split per quarter and per classification, counts may be records_published/no_records_published/unknown with a reason, min/median/max are our own computation and become null below 5 values, and the sample is capped. It also flags the required MLIT credit and that this is not an appraisal or advice.

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?

Front-loaded question then a compact enumeration of inputs and outputs; dense but no filler sentences, and the credit/disclaimer is short.

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

Completeness4/5

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

With an output schema present and annotations covering read-only/idempotent/open-world safety, the description fills the remaining gaps well: output shape caveats (pooling, small-sample nulls, capped sample) and the published-not-advice framing.

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 100%, so parameters are fully documented structurally. The description only echoes the 'up to 8 quarters (YYYY-Qn)' constraint and the per-classification split, adding little beyond the schema.

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?

States a specific verb+resource in a question form: which MLIT-published transaction/contract prices exist for a municipality and quarter. It is clearly distinct from realestate_municipalities (code lookup), though it names no sibling explicitly in the description itself.

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?

Usage is implied: supply a municipality code and up to 8 quarters, with classification choice. There is no explicit when-to-use/when-not or routing to siblings beyond the in-schema pointer to realestate_municipalities for code lookup.

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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