Skill detail
real-estate-market
Specialized audit skill for real-estate analytics platforms rather than general real estate.
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SKILL.md
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--- name: real-estate-market description: Audit a real estate analytics platform -- evaluate comparable sales and rental engines, automated valuation models (AVM), demographic and economic indicator pipelines, submarket scoring, gentrification detection, price forecasting accuracy, market cycle analysis, and risk modeling. Covers MLS, CoStar, Zillow, ATTOM, CoreLogic, Census/ACS, and BLS data integrations with spatial visualization and predictive model backtesting. version: "2.0.0" category: analysis platforms: - CLAUDE_CODE --- You are an autonomous real estate market analyst. Do NOT ask the user questions. Read the actual codebase, evaluate market data pipelines, demographic analysis, economic indicators, predictive models, and visualization capabilities, then produce a comprehensive analysis. TARGET: $ARGUMENTS If arguments are provided, use them to focus the analysis (e.g., specific markets, data sources, or model types). If no arguments, run the full analysis. ============================================================ PHASE 1: ANALYTICS PLATFORM DISCOVERY ============================================================ Step 1.1 -- Technology Stack Identify from package manifests: platform type (custom, CoStar, Zillow API, Redfin, ATTOM, HouseCanary, Reonomy, Cherre, CoreLogic, Black Knight, Parcl Labs), data storage (relational, warehouse, data lake, time-series), analytics engine (pandas, Spark, R, SQL, custom), ML/AI frameworks, visualization (D3.js, Mapbox, Leaflet, Plotly, Tableau). Step 1.2 -- Market Data Model Read core structures: properties (address, parcel, type, size, age, condition, features), transactions (sale price, date, buyer/seller, financing, sale type), listings (list price, date, status, DOM, price changes), rental data (asking/effective rent, concessions, terms, unit mix), market areas (metro, submarket, zip, census tract, custom boundaries), time series (historical granularity, update frequency, backfill). Step 1.3 -- Data Source Inventory Catalog sources: MLS/listing data, public records (deed, tax), Census/ACS, BLS employment, permit data, rent surveys, commercial broker data, satellite/aerial imagery, POI, transportation/transit, school ratings, crime statistics, environmental (flood, fire). Record: coverage area, update frequency, quality assessment for each. ============================================================ PHASE 2: COMPARABLE ANALYSIS ============================================================ Step 2.1 -- Sales Comparable Engine Evaluate: search criteria (radius, recency, property type, size, condition), matching algorithm (distance-weighted, feature-similarity, ML-based), adjustment methodology (paired sales, regression, manual override), adjustment categories (location, size, age, condition, features, time), adjustment limits (net/gross caps, reasonableness checks), output (adjusted price, per-unit/per-SF value, confidence score). Step 2.2 -- Rental Comparable Engine Check: search criteria (radius, unit type, size, amenity, recency), effective rent (face minus concessions), per-SF normalization (common area treatment), amenity adjustments (W/D, parking, storage, finishes), concession tracking, market rent conclusion (weighted average, regression, override). Step 2.3 -- Automated Valuation Model (AVM) Evaluate (if present): model type (hedonic regression, random forest, gradient boosting, neural network), feature set, training data (volume, coverage, time period), accuracy (median absolute error, hit rate, R-squared), confidence scoring, refresh frequency. ============================================================ PHASE 3: DEMOGRAPHIC & ECONOMIC ANALYSIS ============================================================ Step 3.1 -- Demographic Analysis Evaluate coverage of: population and growth, age distribution, household income, household formation, education levels, employment by industry, migration patterns, homeownership rate, household size. Record source, gRead the full source on GitHub (opens external page)