Square Yards brings Indian real estate search and analysis into Claude. Look up resale and rental listings, browse new-construction projects, and get locality recommendations ranked for either living or investment. Compare properties, projects, or localities side by side, drill into full details on any one of them, and calculate home-loan EMIs or affordability. It also handles India-specific area-unit conversions and answers general buying, renting, and selling questions.
value (a positive number) and from; give to for a single target, or omit it to get the value in the common units at once. Units accept friendly aliases (sqft, sqm, gaj, acre, cent, ground…). IMPORTANT: bigha, biswa and kattha differ by state, so pass a state-qualified code (BIGHA_PUCCA_UP_I, BISWA_HP_I, KATTHA_BIHAR, …); a bare "bigha" or an unknown unit returns the list of valid codes. For property PRICE/EMI numbers use estimate_home_loan; for live listings use search_properties.entity, and you must already hold each numeric id: resolve each first via search_entities / search_properties / search_projects, never guessing. For city/locality/micromarket set idType to the id's source (beats default, or dotcom); it is ignored for project/listing. Cross-type comparison is not supported, and property-rates is not comparable. To RANK many localities or answer "which area is best" use recommend_localities.id; project -> a search_projects result's id, OR a search_entities type:"project" result's dotcomId (project has one id space); developer -> a search_entities type:"builder" result's dotcomId; city/locality/micromarket -> a search_entities result's beatsId (default) or dotcomId (then set idType="dotcom"). For projects the result includes possessionStartingFrom, the authoritative possession date (earliest upcoming RERA completion). For a PLACE's PRICE / PROPERTY RATES / market insights use entity="property-rates": resolve the place via search_entities, take its beatsId, then call with entity="property-rates", rateType=(city|locality|micromarket) and id=that beatsId. Optional fields adds sections (comma-separated); omit for the primary detail. Returns a compact, intent-filtered detail object.localities:[{id,idType}] (or cityId to rank a city's top localities). Optional budget (absolute INR) flags each inBudget; goal = end_use | investment | both (default). HONEST + deterministic: it only combines signals get_entity_details already returns and NEVER invents a verdict. Sub-scores (0-100): connectivity/lifestyle/livability = the backend 0-5 index x20; appreciation = price-trend % (0%->50, +/-12.5%->100/0); liquidity (govt registered-deal volume) + value (rental yield) are ranked RELATIVE to the set. Weights - end-use: livability .35, connectivity .30, lifestyle .25, value .10; investment: appreciation .40, liquidity .30, value .20, connectivity .10; overall = their mean. A missing signal is OMITTED (not zero-filled), BUT a locality is only RANKED when present signals cover >50% of the goal's CORE (discriminating) weight — investment = appreciation/liquidity/yield (connectivity alone can't rank it), end-use = livability/connectivity/lifestyle; thinner ones go to insufficientData (with known signals + reason), so a one-signal locality can never top the list. signalCoverage is that CORE-weight share (0-1); each item also carries signalsUsed + raw numbers (avgRate, rentalYield, priceTrendPct, transactions) and VERBATIM pros/cons. India only, read-only.location set (they resolve the place themselves in ONE call). Use search_entities ONLY to disambiguate an ambiguous place, get a landmark's coordinates, or resolve a builder/project name to an id. When you do use it, chain in the SAME turn: resolving a place but fetching no listings/projects/detail is INCOMPLETE. Reading results: - city/locality/micromarket/builder -> carries ready-made forProperties (beats-space ids -> search_properties) and forProjects (dotcom-space ids -> search_projects) scope objects; pass the matching one's fields VERBATIM, never build or transform ids. - type:"project" -> take its dotcomId; drill in with get_entity_details (entity="project") or scope search_projects by it. - type:"landmark" -> take its coordinates as lat/long (or landmarkId "lat|lng|name") for a near-<landmark> radius search. Routing after resolving: resale/rent -> search_properties; new-construction -> search_projects; general buy -> BOTH; one entity's full detail or a place's price-rates -> get_entity_details. Always pick the ONE result whose name and city match the user's words ("Noida" -> the city Noida, not Greater Noida). (search_faq answers how/what/why and needs no id.)category (e.g. buying/renting/selling) to scope results; top_k caps returned Q/A pairs (default 3).location as the place in the user's words ("Noida", "Wakad Pune") plus filters - it resolves the place itself, so you need NOT call search_entities first. For precise/repeat scope you may instead pass an entity's forProjects ids (cityId/localityId/micromarketId/builderId - DOTCOM id space) VERBATIM; explicit ids override location. Never reuse a search_properties BEATS id here, and never guess ids. SPECIFIC NAMED project: do NOT use this discovery list (a city-scoped search returns the wrong project) - resolve the name via search_entities (entityType="project"), take its dotcomId, and open it with get_entity_details (entity="project", id=that dotcomId). A geo (lat/long or landmark) search adds distanceInKm per card. Defaults: RESIDENTIAL projects unless buildingType=2 (commercial) or a type/q is set; default order is "Top Selling" (Square Yards promoted/featured ranking - cards carry isFocus/isAssured/hasExclusive flags; use sort for price/connectivity order). A card price + estimate_home_loan gives its EMI. DRILL-DOWN: every card has an id - for possession/completion date, per-wing RERA, amenities or full spec call get_entity_details (entity="project", id=that id verbatim - never the name/slug).location as the place in the user's words ("Gurgaon") plus filters - it auto-resolves the place, so do NOT call search_entities first. For precise scope pass an entity's forProperties ids (cityId/subLocalityId/microMarketId = BEATS ids) VERBATIM; explicit ids or lat/long override location; never guess numeric ids and never reuse a forProjects/dotcom id (different id space). budget = absolute INR (40 lakh -> 4000000); area in sq ft; bedrooms = BHK label ("2 BHK"). propertyTypeName takes EXACT propertyType values (Apartment, Villa, Builder Floor, Independent House, Office Space, Shop, Plot, ...) - "Studio"/"1 RK"/"Ind Floor" are bedrooms (unitType) values, NOT types. With NO propertyTypeName the search defaults to RESIDENTIAL types - set a commercial type explicitly for offices/shops (project-scoped searches exempt). A geo search (lat/long or landmark) adds distanceInKm per card. Results follow Square Yards ranking; promoted cards carry isFeatured/isExclusive flags (use sort for price/newest order). Each card carries a normalized pricePerSqft (₹/sq.ft) + areaSqft so "cheapest per sq.ft" is directly answerable; a dataQualityFlag caveats an implausible area/price. For "what EMI would this cost" pass a card price to estimate_home_loan. DRILL-DOWN: every listing has an id -> get_entity_details entity="listing" id=that id, copied verbatim (never the title or URL).App Stats
15
Tools
2
Prompts
ChatGPT, Claude
Platforms
Category
Property ResearchWorks with
Data refreshed daily
