Realtor.com School Rating Lookup

Purpose

Return Realtor.com's school-detail payload for a given school — GreatSchools rating (1–10), parent-reviews summary (count + average), grades served, total enrollment, student-teacher ratio, district name + id, address, NCES code, GreatSchools id, catchment polygon (when present), and the canonical Realtor.com school-detail URL. Accepts three input shapes: a direct Realtor.com school URL, a school name + city/state, or a property address (which is resolved to its assigned elementary / middle / high schools). Read-only.

When to Use

• A property-search agent needs school ratings to score listings.
• A relocation agent comparing assigned-school quality across candidate addresses.
• Bulk extraction of school metadata + catchment polygons across a metro.
• Anywhere you'd otherwise scrape Realtor.com's school-detail HTML — the embedded __NEXT_DATA__ JSON is faster, structurally stable, and renders without JS.

Workflow

Realtor.com's school-detail pages ship a fully populated <script id="__NEXT_DATA__" type="application/json"> hydration blob inline in the HTML. No bot challenge fires on a plain HTTP GET — browse cloud fetch is sufficient (~250–430 KB response, single round-trip, no proxy required). All required fields (rating, parent_rating, review_count, student_count, student_teacher_ratio, grades[], education_levels[], nces_code, greatschools_id, district.{id,name}, location.{...}, boundary GeoJSON catchment) live under props.pageProps.school in that blob. Lead with browse cloud fetch — the live-browser path (browse cloud browse + a Browserbase session) is only needed for the property-address input, because property-detail pages sit behind Kasada Bot Defense (see Gotchas).

Step 1 — Normalize the input to a canonical school-detail URL

The canonical URL pattern is:

https://www.realtor.com/local/schools/{slug_id}

where {slug_id} = {Name-With-Dashes}-{schoolId} — e.g. Sylvia-Mendez-Elementary-078571861, Poway-High-School-078657741. schoolId is Realtor.com's internal id (9–10 digit numeric string, not the NCES id and not the GreatSchools id).

Input shape (a): direct school-detail URL → skip to Step 2.

Input shape (b): school name + city/state → resolve via the public autocomplete API (no auth, no anti-bot, no proxy):

GET https://parser-external.geo.moveaws.com/suggest
    ?input=<urlenc "<name> <city> <state>">
    &client_id=rdc-search-default
    &area_types=school
    &limit=10

Take the highest-scoring autocomplete[i] whose area_type === "school". The result includes slug_id, school_id, school, line (address), city, postal_code, state_code, centroid.{lat,lon}, and has_catchment (boolean — whether the school has a GeoJSON catchment polygon attached). Construct the URL as https://www.realtor.com/local/schools/{autocomplete[0].slug_id}.

If autocomplete is empty, retry once with area_types omitted (some out-of-database schools surface only when the type filter is dropped). If still empty, emit {success: false, reason: "school_not_found"}.

Input shape (c): property address → see "Property-address flow" below.

Step 2 — Fetch the school-detail page

browse cloud fetch "https://www.realtor.com/local/schools/{slug_id}" --output /tmp/school.html

No --proxies, no Verified, no live browser session. School-detail pages render to ~410 KB of HTML containing the full hydration JSON. Verify status by checking that the response contains <script id="__NEXT_DATA__". A page that returned a Kasada interstitial would be < 2 KB and contain KPSDK / "reference ID" — if you see that on a school-detail URL, retry once; if it recurs, fall back to a Verified Browserbase session (see Step 5).

Step 3 — Extract and parse the hydration blob

import re, json
html = open('/tmp/school.html').read()
m = re.search(r'<script id="__NEXT_DATA__" type="application/json">(.*?)</script>', html, re.DOTALL)
data = json.loads(m.group(1))
school = data['props']['pageProps']['school']

All fields live under school (see "Field map" below). The page also exposes props.pageProps.district (often null — district data is denormalized into school.district) and props.pageProps.nearbySchools (which despite the name is nearby cities/areas metadata, not nearby schools — do not use this for assigned-schools).

Step 4 — Emit the consolidated output

Map the parsed fields per the schemas in Expected Output. Critical mappings:

Step 5 — Browser fallback (only on Kasada wall)

If browse cloud fetch ever returns a Kasada interstitial (< 2 KB body containing KPSDK and "reference ID") on a school-detail URL — uncommon, but observed under aggressive batched fetching — fall back to a Verified Browserbase session:

SID=$(browse cloud sessions create --keep-alive --verified --proxies | jq -r .id)
browse cloud browse --connect "$SID" newpage "https://www.realtor.com/local/schools/{slug_id}"
browse cloud browse --connect "$SID" wait load
HTML=$(browse cloud browse --connect "$SID" get html body)
# Then run the same Step 3 parse against $HTML
browse cloud sessions update "$SID" --status REQUEST_RELEASE

The __NEXT_DATA__ blob renders identically in the headless-browser DOM as in the raw HTML response.

Property-address flow (input shape c)

The Realtor.com property-detail page (/realestateandhomes-detail/...) is Kasada Bot Defense-protected and browse cloud fetch always returns the interstitial. Two viable paths:

Path A — Catchment point-in-polygon (preferred; pure browse cloud fetch). Use this when the address has a known lat/lon and you only need elementary / middle / high assigned schools.

1. Resolve the address with the suggest API:

   GET https://parser-external.geo.moveaws.com/suggest
       ?input=<urlenc address>
       &client_id=rdc-search-default
       &area_types=address
       &limit=5
   

   Take the top result; record centroid.{lat,lon} and mpr_id.
2. Fetch the city's candidate schools via the suggest API (one call per education level you need):

   GET https://parser-external.geo.moveaws.com/suggest
       ?input=<urlenc "elementary <city>">
       &client_id=rdc-search-default
       &area_types=school
       &limit=20
   

   Filter results to those with has_catchment: true and same state_code as the address.
3. For each candidate, browse cloud fetch the detail page and read school.boundary (GeoJSON MultiPolygon). Run point-in-polygon (Shapely Point(lon, lat).within(shape(boundary)) or turf.booleanPointInPolygon) against the address centroid.
4. Repeat for middle and high (use input=middle <city> / input=high <city>).
5. Emit one record per level with the matched school's full payload.

This path costs ~5–10 browse cloud fetch calls per address and completely avoids the property-detail page and Kasada.

Path B — Live browser to property page (fallback). Use when point-in-polygon is ambiguous (no candidate boundary contains the address — happens at district edges or in non-CA states with non-residential zoning), or when you need the exact "assigned schools" panel as Realtor.com renders it.

SID=$(browse cloud sessions create --keep-alive --verified --proxies | jq -r .id)
browse cloud browse --connect "$SID" newpage "https://www.realtor.com/realestateandhomes-detail/{address-slug}_{property-id}"
browse cloud browse --connect "$SID" wait load
browse cloud browse --connect "$SID" wait timeout 3000
# The assigned-schools panel is usually visible without scrolling; if not, scroll to "Schools" section
HTML=$(browse cloud browse --connect "$SID" get html body)
browse cloud sessions update "$SID" --status REQUEST_RELEASE

The property page also ships a __NEXT_DATA__ blob — parse it the same way and look for props.pageProps.propertyDetail.schools[] (each item has school_id, slug_id, assigned: true|false, funding_type, rating, grades, education_levels, distance_in_miles). Filter on assigned === true for the catchment-assigned list. Both --verified and --proxies are mandatory on the session — bare or Verified-only sessions get Kasada-blocked on the first page load.

Site-Specific Gotchas

• READ-ONLY. Never click "Save", "Contact agent", or any property-action button — the skill exists to extract data, not to interact.
• The anti-bot is Kasada, not PerimeterX or DataDome. The interstitial fingerprints are <script>window.KPSDK={} and a request path of the form /{uuid}/{uuid}/ips.js?KP_UIDz=…. Don't waste time configuring DataDome cookie spoofing or PerimeterX header bypasses — they're the wrong vendor. Verified + residential proxy on a real headless browser (Browserbase --verified --proxies) is the only known consistent bypass for the protected surfaces.
• School-detail pages are NOT Kasada-protected (verified across 7 schools across multiple states + funding types, 2026-05-16). browse cloud fetch returns the full __NEXT_DATA__ blob without any session, proxy, or Verified — this is the canonical fast path for the school-detail and name-lookup input shapes. Treat browse cloud fetch failure on a /local/schools/... URL as a transient hiccup, not a vendor change.
• The /local/schools/search?searchTerm=... URL is a dead end. It resolves to Realtor.com's internal _error page (page /_error in __NEXT_DATA__, query {searchTerm, slugId: "search"}). Don't use it. Use the parser-external.geo.moveaws.com/suggest API instead.
• props.pageProps.nearbySchools is a misnomer — its actual contents are nearby cities / neighborhoods / counties / zips metadata (slug_id, geo_statistics, recommended_cities, etc.), not other schools. Don't try to read assigned-schools from it.
• Private schools have null ratings. GreatSchools doesn't rate private schools. For funding_type === "private", expect rating: null, student_teacher_ratio: null, district.name: null (but district.id is still populated with a synthetic state-prefix code like "06151428551"), and boundary: null (no catchment). Emit great_schools_rating: null + a null_rating_reason: "private_school_not_rated" flag rather than failing.
• school.assigned is always null on the school-detail page. That field exists in the schema but is only populated when the school is referenced from a property-detail-page context. Don't read it from the school page.
• school.boundary is a GeoJSON MultiPolygon. When present (public schools with has_catchment: true), it's a real catchment polygon usable for point-in-polygon assignment — see the Property-address Path A above. Polygons are sometimes 1000+ vertices; budget memory accordingly when iterating across a district.
• nces_code length varies. Newer / mainstream entries are 12 digits (e.g. 060474000447); older charter / private entries are 8 (02061017). Both are valid — do not zero-pad or strip leading zeros.
• Two different ids on the same school. school.id (and school.slug_id trailing segment) is Realtor.com's internal id (9-10 digits, e.g. 078571861 or 0772862241). school.greatschools_id is the upstream GreatSchools id (typically 7 digits, e.g. 0600034). school.nces_code is the federal id. The slug_id always uses school.id, not the GreatSchools id — never construct URLs with the GreatSchools id.
• school.district.id is NOT the federal NCES district id. It's Realtor.com's internal id (11 chars, e.g. 06151428611). There is no NCES district code surfaced in the payload. If your output schema requires the federal district id, look it up separately.
• school.grades is an array of strings, not a range. Public-school payloads use values like ["K", "1", "2", "3", "4", "5"]; preK is "PK". Render to "K-5" only when the array is contiguous; otherwise join with commas. Don't assume integer ordering — "K" and "PK" sort before "1" lexically only if you special-case them.
• school.student_teacher_ratio is a float, not a colon string. Realtor.com returns 16.3; format to "16.3:1" only at the output layer.
• parser-external.geo.moveaws.com/suggest query whitelist is strict. Accepted params: input, client_id, area_types, limit, include. postal_code, city, state, lat, lon, has_catchment are all rejected with whitelistValidation 400s. Filter / scope results client-side after the call.
• The suggest API is unauthenticated and not rate-limited at typical agent volumes (tested at low double-digits RPS without throttling, 2026-05-16). It exposes school + address + city + street + county + zip area types. client_id=rdc-search-default is the Realtor.com web app's id; any non-empty value seems to work, but stick to rdc-search-default for forward-compat.
• browse cloud fetch with --proxies does not bypass Kasada. Kasada requires JS execution to clear the interstitial; the lightweight Fetch API doesn't run JS regardless of proxy. Verified 2026-05-16 — both proxied and unproxied browse cloud fetch on /realestateandhomes-detail/... return the same Kasada interstitial. For property pages, use the live browser path.
• Confirmed dead ends — don't re-probe:
  • https://www.realtor.com/api/v1/schools/search → 404 ("Cannot GET").
  • https://www.realtor.com/api/v1/hulk → 403.
  • https://www.realtor.com/api/v1/rdc_search/schools → 404.
  • parser-external.geo.moveaws.com/schools, /schools_search, /locality, /reverse_geocode → 404.
  • m.realtor.com/... → 301 to www.realtor.com (no separate mobile surface).

Expected Output

Input shape (a) / (b) — school detail URL or name+city/state

{
  "success": true,
  "input_type": "school_detail_url",
  "school": {
    "name": "Sylvia Mendez Elementary",
    "school_id": "078571861",
    "slug_id": "Sylvia-Mendez-Elementary-078571861",
    "great_schools_id": "0600032",
    "nces_id": "060474000445",
    "funding_type": "public",
    "education_levels": ["elementary"],
    "grades_served": "K-5",
    "great_schools_rating": 7,
    "parent_reviews": { "count": 4, "average": 5 },
    "enrollment": 379,
    "student_teacher_ratio": "16.3:1",
    "district": {
      "name": "Berkeley Unified School District",
      "realtor_id": "06151428611"
    },
    "address": "2840 Ellsworth Street, Berkeley, CA 94705",
    "coordinate": { "lat": 37.857694, "lon": -122.262234 },
    "phone": "(510) 644-6290",
    "url": "https://www.realtor.com/local/schools/Sylvia-Mendez-Elementary-078571861",
    "has_catchment": true
  }
}

Private school (null rating)

{
  "success": true,
  "input_type": "school_name",
  "school": {
    "name": "Fairmont Private Schools - Historic Anaheim Campus",
    "school_id": "078696341",
    "funding_type": "private",
    "education_levels": ["elementary", "middle", "high"],
    "grades_served": "PK-12",
    "great_schools_rating": null,
    "null_rating_reason": "private_school_not_rated",
    "parent_reviews": { "count": 15, "average": 4 },
    "enrollment": 1835,
    "student_teacher_ratio": null,
    "district": { "name": null, "realtor_id": "06151428551" },
    "address": "...",
    "url": "https://www.realtor.com/local/schools/Fairmont-Private-Schools-Historic-Anaheim-Campus-078696341",
    "has_catchment": false
  }
}

Input shape (c) — property address

{
  "success": true,
  "input_type": "property_address",
  "property": {
    "address": "680 Grizzly Peak Blvd, Berkeley, CA 94708",
    "mpr_id": "1299668687",
    "coordinate": { "lat": 37.899275, "lon": -122.265644 },
    "url": "https://www.realtor.com/realestateandhomes-detail/680-Grizzly-Peak-Blvd_Berkeley_CA_94708_M12996-68687",
    "resolution_method": "catchment_point_in_polygon"
  },
  "assigned_schools": [
    { "level": "elementary", "name": "...", "school_id": "...", "great_schools_rating": 9, "grades_served": "K-5", "url": "..." },
    { "level": "middle",     "name": "...", "school_id": "...", "great_schools_rating": 7, "grades_served": "6-8", "url": "..." },
    { "level": "high",       "name": "...", "school_id": "...", "great_schools_rating": 8, "grades_served": "9-12", "url": "..." }
  ]
}

Failure shapes

// School name doesn't match anything in the suggest API
{ "success": false, "reason": "school_not_found", "input": "Foo Bar Academy Nowhere XX" }

// School-detail URL returned the Kasada interstitial AND browser fallback also failed
{ "success": false, "reason": "anti_bot_block", "vendor": "kasada", "evidence": "KPSDK present in 1.8KB response" }

// __NEXT_DATA__ block was missing or props.pageProps.school was empty
{ "success": false, "reason": "data_not_hydrated", "evidence": "no __NEXT_DATA__ script in response" }

// Property address: address resolves but no candidate school's boundary contains the point (district edge, non-residential parcel, or unincorporated area)
{ "success": false, "reason": "no_catchment_match", "address": "...", "candidates_checked": 12 }

// Property address: live-browser fallback blocked by Kasada despite Verified + proxies
{ "success": false, "reason": "anti_bot_block", "vendor": "kasada", "where": "property_detail_page" }