name: bcpao-data-extraction-skill description: Extract property data from Brevard County Property Appraiser GIS API including photos, valuations, and parcel details

BCPAO Data Extraction Skill

Extracts comprehensive property data from Brevard County Property Appraiser's GIS API.

When to Use This Skill

• Stage 2 of Everest Ascent pipeline (Scraping)
• Getting property valuations for ARV calculations
• Retrieving property photos for reports
• Extracting parcel details for title research

API Endpoint

Base URL:

https://gis.brevardfl.gov/gissrv/rest/services/Base_Map/Parcel_New_WKID2881/MapServer/5

Operation: /query

Query Parameters

params = {
    'where': f"PARCEL_ID = '{parcel_id}'",  # or SITE_ADDR LIKE '%123 Main St%'
    'outFields': '*',
    'returnGeometry': 'false',
    'f': 'json'
}

Key Fields Returned

Property Identification

• PARCEL_ID: Unique parcel identifier (e.g., "29-37-38-00-00000.0-000010.0")
• ACCOUNT: Account number for photo URLs
• SITE_ADDR: Full property address
• LEGAL_DESC: Legal description

Ownership

• OWNER_NAME: Current owner of record
• OWNER_ADDR: Mailing address
• MAIL_CITY, MAIL_STATE, MAIL_ZIP

Valuations

• JUST_VAL: Just (assessed) value
• ASSESSED_VAL: Assessed value for tax purposes
• TAXABLE_VAL: Taxable value after exemptions
• LAND_VAL: Land value only
• BLDG_VAL: Building value only

Property Characteristics

• LIV_AREA: Living area in square feet
• YR_BLT: Year built
• ZONING: Zoning classification
• USE_CODE: Property use code
• TOTAL_BEDROOMS: Bedroom count (NOT RELIABLE - often missing)
• TOTAL_BATHROOMS: Bathroom count (NOT RELIABLE - often missing)

Tax Information

• TAX_DIST: Tax district
• EXEMPTIONS: Homestead/other exemptions

Photo URL Generation

Photos follow predictable pattern:

def get_photo_url(account_number):
    # Format: https://www.bcpao.us/photos/{prefix}/{account}011.jpg
    # Account: 2934567 → prefix: 293, photo: 2934567011.jpg
    
    prefix = account_number[:3]
    photo_url = f"https://www.bcpao.us/photos/{prefix}/{account_number}011.jpg"
    return photo_url

Example:

• Account: 2934567
• Prefix: 293
• URL: https://www.bcpao.us/photos/293/2934567011.jpg

Availability:

• ~13/15 properties have photos (87% success rate)
• Returns 404 if photo doesn't exist
• Fallback: Use placeholder or note "No photo available"

Data Limitations

❌ NOT Available in BCPAO API:

• Bedrooms (field exists but often null)
• Bathrooms (field exists but often null)
• Detailed property condition
• Recent sales comparables
• Interior features

✓ Available via BCPAO:

• Living area (reliable)
• Year built (reliable)
• Assessed values (reliable)
• Ownership (reliable)
• Photos (87% available)

🔍 Must Use Other Sources For:

• Beds/Baths: Zillow, Redfin, Realtor.com
• Comps: MLS, Zillow, recent sales
• Condition: Drive-by, photos, inspector
• Rental rates: Airbnb, Furnished Finder, Zillow

Example Response

{
  "features": [
    {
      "attributes": {
        "PARCEL_ID": "29-37-38-00-00000.0-000010.0",
        "ACCOUNT": "2934567",
        "SITE_ADDR": "123 MAIN ST",
        "OWNER_NAME": "SMITH JOHN & MARY",
        "JUST_VAL": 425000,
        "ASSESSED_VAL": 425000,
        "LAND_VAL": 125000,
        "BLDG_VAL": 300000,
        "LIV_AREA": 2150,
        "YR_BLT": 2005,
        "ZONING": "RES-1",
        "USE_CODE": "0100",
        "LEGAL_DESC": "LOT 10 BLOCK A SUBDIVISION PLAT..."
      }
    }
  ]
}

ARV Calculation Strategy

Since BCPAO doesn't give comps, use multi-source approach:

Step 1: BCPAO Baseline

bcpao_value = response['JUST_VAL']  # Assessed value

Step 2: Zillow/Redfin Comps

# Search Zillow for recent sales within 0.5 miles
# Similar: beds, baths, sqft, year
comparable_sales = get_recent_sales(address, radius=0.5)
avg_comp_value = mean([sale['price'] for sale in comparable_sales])

Step 3: Calculate ARV

# Weight: 40% BCPAO, 60% comps
arv = (bcpao_value * 0.4) + (avg_comp_value * 0.6)

# Conservative adjustment
arv_conservative = arv * 0.95  # 5% haircut for safety

Integration with Pipeline

# Stage 2: Scraping
bcpao_data = bcpao_extraction_skill.query(parcel_id)

property_details = {
    'address': bcpao_data['SITE_ADDR'],
    'living_area': bcpao_data['LIV_AREA'],
    'year_built': bcpao_data['YR_BLT'],
    'assessed_value': bcpao_data['JUST_VAL'],
    'photo_url': get_photo_url(bcpao_data['ACCOUNT']),
    'legal_desc': bcpao_data['LEGAL_DESC']
}

# Use for ARV calculation in Stage 8
# Use photo in Stage 10 (Report Generation)

Error Handling

try:
    response = requests.get(api_url, params=params)
    data = response.json()
    
    if not data.get('features'):
        # Parcel not found
        return None
    
    # Extract first feature
    property_data = data['features'][0]['attributes']
    
except requests.exceptions.RequestException:
    # API timeout or error
    return None

Example Usage

"Use bcpao-data-extraction-skill to get details for parcel 29-37-38-00-00000.0-000010.0"

"Extract BCPAO data for property at 123 Main St Melbourne FL"

"Get assessed value and photo for account 2934567"

Best Practices

1. Cache Results: Don't query same parcel multiple times
2. Handle Missing Photos: 13% don't have photos, use fallback
3. Don't Trust Bed/Bath: BCPAO data unreliable, use Zillow/Redfin
4. Use JUST_VAL for ARV: Most accurate baseline value
5. Verify Legal Desc: Critical for title research