ServiceHub real-estate-analyzer

Evaluate properties, neighborhoods, and investment returns for home buying

install
source · Clone the upstream repo
git clone https://github.com/Dhirubhaidhanush/ServiceHub
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/Dhirubhaidhanush/ServiceHub "$T" && mkdir -p ~/.claude/skills && cp -r "$T/.local/secondary_skills/real-estate-analyzer" ~/.claude/skills/dhirubhaidhanush-servicehub-real-estate-analyzer && rm -rf "$T"
manifest: .local/secondary_skills/real-estate-analyzer/SKILL.md
source content

Real Estate Analyzer

Analyze properties, neighborhoods, and real estate investment opportunities for home buyers and investors. Evaluate listings, estimate fair value, assess neighborhoods, and model investment returns.

When to Use

  • User wants to evaluate a property listing for purchase
  • User asks about neighborhood quality, schools, or safety
  • User wants to compare properties or neighborhoods
  • User needs help estimating if a home is fairly priced
  • User wants to analyze a property as an investment (rental yield, appreciation)

When NOT to Use

  • Apartment rental hunting (use apartment-finder skill)
  • Mortgage or loan calculations only (use budget-planner skill)
  • Legal review of purchase agreements (use legal-contract skill)

Methodology

Step 1: Property Assessment

Gather and evaluate listing details:

Basic Details:

  • Address, price, square footage, lot size
  • Bedrooms, bathrooms, year built
  • Property type (single-family, condo, townhouse, multi-family)
  • Days on market, price history, price reductions

Condition Indicators:

  • Age of major systems (roof, HVAC, water heater, electrical)
  • Recent renovations or updates
  • Foundation type and condition
  • Photos analysis — look for staging tricks, unflattering angles, missing rooms

Red Flags:

  • Significantly below market price (could indicate undisclosed issues)
  • Frequent ownership changes (flipped too fast?)
  • "As-is" or "investor special" language
  • Missing disclosures or incomplete listing info
  • High DOM (days on market) without price reduction

Step 2: Valuation Analysis

Pull comps — specific sources:

  • webFetch
    Redfin sold filter:
    redfin.com/city/{id}/filter/include=sold-6mo
    — recently sold within 0.5mi, ±20% sqft, same beds
  • Zillow Research (
    zillow.com/research/data/
    ) — free CSV downloads of ZHVI (home value index) and ZORI (rent index) by ZIP, monthly back to 1996
  • County assessor website — webSearch
    "{county name} property assessor {address}"
    for tax-assessed value, last sale price, permit history. Assessed value is typically 70-90% of market value.
  • Adjust comps: ±$15-40/sqft for size delta, ±$5-15k per bedroom, ±10-20% for condition

Affordability math (compute, don't estimate):


# PITI at 30yr fixed — webSearch current rates (use Freddie Mac PMMS)
# PMMS reports percentage (e.g. 6.76), so divide by 100 first
P, r, n = loan_amount, annual_rate/100/12, 360
monthly_PI = P * (r*(1+r)**n) / ((1+r)**n - 1)

# + property tax (county rate × assessed value / 12)

# + homeowners insurance (~$150-250/mo, varies wildly by state)

# + PMI if <20% down (~0.5-1.0% of loan/yr)

  • 28/36 rule: PITI <28% gross income, total debt <36%. Lenders stretch to 43% DTI — don't.
  • Closing costs: 2-5% of purchase. Maintenance reserve: 1-2% of home value/yr.

Step 3: Neighborhood Analysis

webSearch/webFetch targets (name the source, don't be vague):

  • Schools:
    greatschools.org/{state}/{city}
    — rating ≥7 protects resale value even if user has no kids
  • Crime:
    crimemapping.com
    or
    spotcrime.com/{city}
    — check 6-month trend, not just snapshot. NeighborhoodScout for demographic overlay.
  • Walk/Transit/Bike Score:
    walkscore.com/score/{address}
  • Flood:
    msc.fema.gov/portal/search
    — Zone A/AE/V = mandatory flood insurance ($400-3,000+/yr, often kills deals)
  • Market velocity: Redfin Data Center — median DOM, sale-to-list ratio, months of supply. <3 months supply = seller's market.
  • Future development: webSearch
    "{city} planning commission agenda"
    +
    "{city} zoning map"
    — a highway expansion or apartment rezoning next door changes everything

Step 4: Investment Analysis — Run the Numbers

Quick-filter rules (kill deals fast):

  • 1% rule: monthly rent ≥ 1% of purchase price. Dead in coastal/HCOL markets — there, 0.5-0.7% is realistic and you're betting on appreciation, not cash flow.
  • 50% rule: operating expenses (NOT mortgage) eat ~50% of gross rent. Vacancy + repairs + management + taxes + insurance + capex reserve. Beginners always underestimate this.
  • 70% rule (flips/BRRRR): max offer = (ARV × 0.70) − rehab cost. ARV = after-repair value from renovated comps.

Full underwriting (build in Python):

Gross rent (use Rentometer or Zillow ZORI for the ZIP)
− Vacancy (5-8% typical; 10% conservative)
− Property management (8-10% of collected rent)
− Repairs/maintenance (~8% of rent)
− CapEx reserve (~5% — roof/HVAC/water heater sinking fund)
− Taxes + insurance
= NOI (Net Operating Income)

Cap rate = NOI / purchase price
  → <4%: you're buying appreciation, not cash flow
  → 4-6%: typical for A/B-class in growth metros
  → 6-8%: solid cash flow, B/C-class
  → >10%: either a great deal or a war zone — verify crime data

NOI − annual debt service (P+I) = annual cash flow
Cash-on-cash = annual cash flow / total cash in (down pmt + closing + rehab)
  → Target 8%+ CoC. Below that, an index fund wins with zero tenants.

DSCR (what lenders check for investment loans):

  • DSCR = NOI / annual debt service. Lenders want ≥1.20-1.25× (2025 standard). <1.0 means rent doesn't cover the mortgage.
  • DSCR loans (2025): ~6.5-7.5% rate, qualify on property income not W-2, typical max 75% LTV. How investors scale past 10 conventional mortgages.

BRRRR stack: Buy distressed (hard money, 7-14 day close) → Rehab → Rent → Refinance at 75% of new ARV into DSCR loan → pull most capital out → Repeat. Only works if

ARV × 0.75 ≥ purchase + rehab + holding costs
.

Rent comps: webSearch Rentometer free tier, or pull Zillow rentals for the ZIP and compute median $/sqft for same bed count.

Step 5: Due Diligence Checklist

Before making an offer:

  • Pre-approval letter from lender
  • Professional home inspection ($300-500)
  • Pest/termite inspection
  • Title search for liens or encumbrances
  • Survey (if boundaries unclear)
  • Flood zone check (FEMA maps)
  • Environmental concerns (radon, lead paint for pre-1978 homes)
  • HOA review (financials, rules, pending assessments)
  • Property tax history and assessment

Output Format

Always present key findings and recommendations as a plaintext summary in chat, even when also generating files. The user should be able to understand the results without opening any files.


# Property Analysis: [Address]

## Summary

- Asking Price: $XXX,XXX
- Estimated Fair Value: $XXX,XXX — [Over/Under/Fair priced by X%]
- Recommendation: [Strong Buy / Buy / Hold / Pass]

## Property Details
[Key facts table]

## Valuation
[Comps analysis, price per sqft comparison]

## Neighborhood
[Schools, safety, livability scores]

## Financial Analysis
[Monthly payment breakdown, investment returns if applicable]

## Risks & Concerns
[Red flags, upcoming expenses, market risks]

## Verdict
[2-3 sentence recommendation]

Best Practices

  1. Asking price is marketing — only sold comps within 6 months matter
  2. Model three scenarios — base case, 10% vacancy + 20% higher repairs, and "tenant trashes it year 1"
  3. Permit history is free alpha — county assessor site shows pulled permits. No permits on an "updated kitchen" = unpermitted work = your liability.
  4. Price/sqft is a blunt tool — lot size, corner lots, and basement finish skew it hard. Use for screening, not for offers.
  5. Cap rate without appreciation — in a flat market, if cap rate < your mortgage rate, you're paying to own it

Interactive Map — Web App Visualization

After analyzing properties, build a web app that displays properties and relevant neighborhood data on an interactive map.

Property Markers

  • Color-coded by recommendation: green = Strong Buy, blue = Buy, yellow = Hold, red = Pass
  • Popup on each marker showing: address, asking price, estimated fair value, beds/baths, sqft, price/sqft, and recommendation
  • Click to expand with key details: comp-adjusted value, cap rate (if investment), flood zone, school rating

Neighborhood Context Layers

Display relevant context around the properties:

  • Sold comps — recent comparable sales as smaller markers, with sale price and date
  • School locations with GreatSchools ratings (color-coded: green ≥7, yellow 4-6, red <4)
  • Flood zones if any properties are in or near FEMA Zone A/AE/V
  • Nearby amenities — transit, grocery, parks when walkability matters to the user

Geocoding

Use the free Nominatim API (OpenStreetMap) to convert addresses to lat/lng — no API key required:

https://nominatim.openstreetmap.org/search?q={url_encoded_address}&format=json&limit=1

Rate limit: max 1 request/second. Batch geocode all addresses before building the map.

Always generate the map alongside the text-based analysis — the map is a visual complement, not a replacement for the detailed evaluation.

Limitations & Disclaimer

  • This is NOT real estate, legal, or financial advice. Informational analysis only. Always engage a licensed realtor, real estate attorney, and professional inspector before purchasing.
  • Cannot access MLS — Redfin/Zillow public data lags and misses pocket listings
  • Cannot provide appraisals (licensed appraiser required for lending)
  • Cannot physically inspect — photos hide foundation cracks, mold, and grading issues
  • Market snapshot only — rates and comps move weekly