Skilllibrary property-research

install
source · Clone the upstream repo
git clone https://github.com/merceralex397-collab/skilllibrary
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/merceralex397-collab/skilllibrary "$T" && mkdir -p ~/.claude/skills && cp -r "$T/16-business-research-and-optional-domains/property-research" ~/.claude/skills/merceralex397-collab-skilllibrary-property-research && rm -rf "$T"
manifest: 16-business-research-and-optional-domains/property-research/SKILL.md
source content

Purpose

Provides a structured, repeatable framework for evaluating residential or small commercial real estate. Covers property scoring, financial viability, comparable sales analysis, area profiling, and risk assessment so that buy/hold/pass decisions are grounded in evidence rather than gut feeling.

When to use this skill

  • User asks to evaluate a specific property or shortlist of properties
  • Task requires comparable sales ("comps") analysis for a target address or area
  • User needs a rental yield calculation, cap rate estimate, or cash-on-cash return model
  • Due diligence checklist is needed before making an offer
  • Area research is requested: crime stats, schools, transport, development pipeline
  • Budget or renovation feasibility modeling for a potential acquisition

Do not use this skill when

  • The task is broad market-trend research with no specific property — use
    market-research
  • The user needs a spreadsheet built or audited — use
    spreadsheet-analysis
  • The task is competitive business analysis, not real estate — use
    competitor-teardown
  • The user needs legal or tax advice — flag this as out of scope and recommend a professional
  • The question is a simple factual lookup ("what's the average price in X?") with no decision support

Operating procedure

Step 1 — Define the investment thesis

  1. Clarify the strategy: buy-and-hold rental, fix-and-flip, BRRRR, or owner-occupy.
  2. Establish target metrics: minimum cap rate, target cash-on-cash return, max purchase price.
  3. Document the buyer's financing assumptions: down payment %, interest rate, loan term.
  4. Record any hard constraints: geography, property type, bedroom count, condition tolerance.

Step 2 — Comparable sales analysis (comps)

  1. Identify 3–6 recent sales (last 6 months, within 0.5 mile) of similar property type, size (±20% sq ft), and condition.
  2. For each comp, record: address, sale price, price per sq ft, days on market, condition, date sold.
  3. Calculate adjusted comp values: apply adjustments for differences in bedrooms, bathrooms, lot size, condition, and age.
  4. Derive a fair market value range: low (worst comp adjusted), midpoint (median adjusted), high (best comp adjusted).
  5. Flag any comps that are outliers and explain why (distressed sale, estate sale, off-market).

Step 3 — Financial modeling

Calculate each metric and show the formula used:

MetricFormula
Gross Rent Multiplier (GRM)Purchase Price ÷ Annual Gross Rent
Cap RateNet Operating Income (NOI) ÷ Purchase Price × 100
Cash-on-Cash ReturnAnnual Pre-Tax Cash Flow ÷ Total Cash Invested × 100
Price per Sq FtPurchase Price ÷ Livable Sq Ft
Gross YieldAnnual Gross Rent ÷ Purchase Price × 100
Net Yield(Annual Gross Rent − Annual Expenses) ÷ Purchase Price × 100

Expense line items to include in NOI calculation:

  • Property tax, insurance, property management (8–10% of gross rent)
  • Maintenance reserve (5–10% of gross rent), vacancy allowance (5–8%)
  • HOA/body corporate fees, utilities (if landlord-paid), capex reserve

Step 4 — Due diligence checklist

Work through each item; mark as ✅ verified, ⚠️ needs attention, or ❌ blocker:

  1. Title search — confirm clean title, no liens, easements, or encumbrances
  2. Zoning verification — confirm permitted use matches investment strategy
  3. Environmental assessment — check flood zone, contamination history, asbestos/lead (pre-1978 builds)
  4. Building inspection — structural, roof, plumbing, electrical, HVAC, pest
  5. Survey and boundaries — confirm lot lines match listing
  6. Insurance quotes — obtain quotes; flag if flood or special hazard insurance required
  7. Rent roll verification (if tenanted) — confirm current leases, deposits, arrears
  8. Code compliance — check for unpermitted work, outstanding violations

Step 5 — Area profiling

Research and score each factor on a 1–5 scale with evidence:

FactorData sources
Crime statsLocal police data, CrimeMapping, NeighborhoodScout
School ratingsGreatSchools, Ofsted (UK), state education dept
Transport linksWalk Score, Transit Score, proximity to highway/rail
EmploymentMajor employers, unemployment rate, job growth trend
Development pipelineCouncil/city planning applications, new permits, infrastructure projects
DemographicsPopulation growth, median income, age distribution, renter vs owner ratio
AmenitiesGrocery, healthcare, parks, restaurants within 1 mile

Step 6 — Budget modeling

Build a complete acquisition budget:

  1. Purchase price — based on comp-supported offer price
  2. Closing costs — estimate 2–5% of purchase price (stamp duty, legal, lender fees)
  3. Renovation estimate — itemized by trade (cosmetic, structural, systems), with 15% contingency
  4. Carrying costs — monthly holding cost × estimated months to stabilize or flip
  5. Total cash invested — down payment + closing + renovation + carrying costs
  6. Exit strategy — target resale price (flip) or stabilized annual cash flow (hold), with timeline

Step 7 — Synthesize and recommend

  1. Compile the Property Scorecard (see output structure).
  2. State a clear recommendation: Buy, Negotiate (with target price), Pass, or Needs more data.
  3. Identify the top 3 risks and what would change the recommendation.
  4. If data is missing, list exactly what is needed and where to get it.

Decision rules

  • Cap rate < 4% in a buy-and-hold strategy → flag as low-return unless strong appreciation thesis exists.
  • Cash-on-cash < 8% → requires explicit justification (appreciation play, value-add opportunity).
  • GRM > 15 → rental income unlikely to cover debt service; stress-test assumptions.
  • Vacancy assumption < 5% → override to minimum 5%; use 8% for areas with > 10% local vacancy.
  • Maintenance reserve < 5% of gross rent → override to minimum 5%; use 10% for properties > 30 years old.
  • Comps older than 12 months → discount reliability; flag as stale data.
  • Environmental red flags (flood zone, contamination) → escalate to professional assessment before proceeding.
  • Unpermitted work detected → quantify cost to rectify or value discount before modeling.
  • Never model with 100% occupancy — always apply a vacancy factor.
  • Always separate the renovation budget from the purchase price in return calculations.

Output structure

Deliver these sections in order:

1. Property Scorecard

DimensionScore (1–5)Key evidence
Location
Condition
Financial return
Risk profile
Area fundamentals
Overall

2. Comparable Sales Analysis

Table of 3–6 comps with adjustments and derived fair market value range.

3. Financial Model

Full income/expense breakdown, all six metrics calculated, sensitivity table showing returns at ±5% purchase price and ±10% rent assumptions.

4. Area Profile

Scored factor table from Step 5 with data sources cited.

5. Due Diligence Status

Checklist from Step 4 with status markers and notes on any open items.

6. Budget Summary

Itemized budget from Step 6 with total cash required and contingency.

7. Risk Assessment

Top 3–5 risks ranked by likelihood × impact, with mitigation actions.

8. Recommendation

Clear Buy / Negotiate / Pass / Needs More Data verdict with reasoning.

Anti-patterns

  • Ignoring maintenance reserves — modeling with zero maintenance creates fantasy returns; always include 5–10% of gross rent.
  • Assuming 100% occupancy — no market has zero vacancy; minimum 5% vacancy factor, higher in soft markets.
  • Skipping title search — liens, easements, and encumbrances can destroy a deal post-closing.
  • Emotional bidding — exceeding the comp-supported price range because "it feels right" is not analysis.
  • Using asking price as market value — always validate against actual closed comps, not listings.
  • Single-comp analysis — one comp is an anecdote; use 3–6 for statistical confidence.
  • Ignoring capex — roofs, HVAC, and plumbing are when-not-if expenses; model them.
  • Projecting rent increases without evidence — use historical rent growth data, not wishful thinking.

Related skills

  • market-research
    — broader market trend analysis that feeds into area profiling
  • spreadsheet-analysis
    — build and audit the financial model workbook
  • financial-tracker-ops
    — ongoing tracking of rental income and expenses post-acquisition
  • competitor-teardown
    — analyzing competing listings or investment opportunities
  • document-to-structured-data
    — extracting data from property listings, inspection reports, or title documents

Failure handling

  • If the user provides no address or area, ask for at least a city/suburb and property type before proceeding.
  • If comp data is unavailable or stale (>12 months), explicitly state this, widen the search radius, and lower confidence.
  • If key financial inputs are missing (purchase price, rent estimate), provide a template for the user to fill in rather than guessing.
  • If due diligence reveals a potential blocker (title issue, environmental), halt the financial analysis and escalate the blocker first.
  • If the investment strategy is unclear, present returns under both buy-and-hold and flip scenarios and ask the user to confirm.