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datasets_housing_markets_search

Search monthly Redfin US housing-market stats by region/property type since 2012, joined to Census ACS income for affordability metrics.

Instructions

Search the US housing markets dataset. Searches monthly Redfin housing-market statistics per region and property type since 2012, joined to Census ACS income for affordability metrics. region_type enum: national, metro, county, city, zip. property_type enum: All Residential, Single Family Residential, Condo/Co-op, Townhouse, Multi-Family (2-4 Unit), Single Units Only. Sort enum: relevance, price_desc, price_asc, list_price_desc, list_price_asc, price_to_income_desc, price_to_income_asc, salary_to_buy_desc, salary_to_buy_asc, dom_asc, dom_desc, inventory_desc, homes_sold_desc, period_desc. Use latest=true for the most recent period per region series.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoFull-text query over region name and city, max 256 characters
pageNoPage number, defaults to 1
sortNoSort enum: relevance, price_desc, price_asc, list_price_desc, list_price_asc, price_to_income_desc, price_to_income_asc, salary_to_buy_desc, salary_to_buy_asc, dom_asc, dom_desc, inventory_desc, homes_sold_desc, period_desc
latestNoFilter for the most recent period per region and property type
periodNoExact period start date filter, YYYY-MM-DD
zip_codeNoExact zip code filter (zip-level rows only), e.g. 60616
page_sizeNoPage size, defaults to 20 and maxes at 100; page * page_size must be <= 10000
state_codeNoExact two-letter state code filter, e.g. CA
region_typeNoRegion level enum: national, metro, county, city, zip
max_inventoryNoMaximum active inventory
min_inventoryNoMinimum active inventory
property_typeNoProperty type enum: All Residential, Single Family Residential, Condo/Co-op, Townhouse, Multi-Family (2-4 Unit), Single Units Only
max_median_domNoMaximum median days on market
min_homes_soldNoMinimum homes sold in the period
min_median_domNoMinimum median days on market
max_salary_to_buyNoMaximum salary needed to buy in USD per year
min_salary_to_buyNoMinimum salary needed to buy in USD per year
parent_metro_codeNoExact parent metro (CBSA) code filter, e.g. 16980
max_price_to_incomeNoMaximum price-to-income ratio
min_price_to_incomeNoMinimum price-to-income ratio
max_median_list_priceNoMaximum median list price in USD
max_median_sale_priceNoMaximum median sale price in USD
min_median_list_priceNoMinimum median list price in USD
min_median_sale_priceNoMinimum median sale price in USD

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.17.5
    • addedInput schema / properties / region_type / enum
      Added value: +[
+  "national",
+  "metro",
+  "county",
+  "city",
+  "zip"
+]
    • addedInput schema / properties / sort / enum
      Added value: +[
+  "relevance",
+  "price_desc",
+  "price_asc",
+  "list_price_desc",
+  "list_price_asc",
+  "price_to_income_desc",
+  "price_to_income_asc",
+  "salary_to_buy_desc",
+  "salary_to_buy_asc",
+  "dom_asc",
+  "dom_desc",
+  "inventory_desc",
+  "homes_sold_desc",
+  "period_desc"
+]
  2. Addedv1.5.0

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. It adds useful context about the data source, time range, granularity, and joined affordability metrics, which goes beyond the raw schema. However, it does not disclose return format, pagination behavior, or what happens when called with no filters, leaving some behavioral uncertainty.

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 front-loaded with the core purpose, then provides the data-source context, enum values, and a practical usage tip. It is somewhat long and repeats enum values already present in the schema, but every part serves a useful role for a complex 24-parameter search tool.

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?

For a tool with 24 parameters, no annotations, and no output schema, the description covers the data domain and key enums well. It is still incomplete: it does not describe the return shape, clarify how to combine filters, or mention sibling tools like datasets_housing_markets_facets for exploring available values.

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?

Schema description coverage is 100%, so the baseline is 3, but the description adds meaningful semantic context: it explains that the data is 'joined to Census ACS income for affordability metrics,' which clarifies the price_to_income and salary_to_buy filters, and it gives an explicit tip for the latest parameter. The enum listings are redundant with the schema but still reinforce correct usage.

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 clearly states a specific verb and resource: 'Search the US housing markets dataset,' and adds valuable scope with 'monthly Redfin housing-market statistics per region and property type since 2012, joined to Census ACS income for affordability metrics.' This is specific enough to understand what the tool does, though it does not explicitly contrast itself with sibling tools like datasets_housing_markets_facets or datasets_housing_markets_item.

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 usage by saying 'Search the US housing markets dataset,' and it provides one concrete usage hint: 'Use latest=true for the most recent period per region series.' However, it does not explain when to choose this tool over the sibling facets or item tools, nor does it state any exclusions or prerequisites.

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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