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foreclosure-analysis-skill

@breverdbidder/brevard-bidder-landing
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Execute 12-stage Everest Ascent pipeline for foreclosure auction analysis from discovery to disposition

Install Skill

1Download skill
2Enable skills in Claude

Open claude.ai/settings/capabilities and find the "Skills" section

3Upload to Claude

Click "Upload skill" and select the downloaded ZIP file

Note: Please verify skill by going through its instructions before using it.

SKILL.md

name foreclosure-analysis-skill
description Execute 12-stage Everest Ascent pipeline for foreclosure auction analysis from discovery to disposition

Foreclosure Analysis Skill

Executes the complete 12-stage Everest Ascent™ methodology for foreclosure auction intelligence.

When to Use This Skill

  • Analyzing upcoming foreclosure auctions
  • Processing new auction listings
  • Generating investment recommendations
  • Creating property reports for bidding decisions

The Everest Ascent™ Pipeline

Stage 1: Discovery

  • Monitor RealForeclose.com for new listings
  • Extract: case number, plaintiff, property address, auction date
  • Filter: Brevard County only, exclude tax deeds
  • Output: candidate_properties list

Stage 2: Scraping

  • BCPAO Scraper: Property details, valuations, photos
  • RealForeclose Scraper: Auction specifics, judgment amount
  • AcclaimWeb Scraper: Mortgages, liens, legal descriptions
  • RealTDM Scraper: Tax certificates, delinquencies
  • Census API: Demographics, neighborhood data

Stage 3: Title Search

  • Parse legal description
  • Identify all recorded instruments
  • Build chain of title
  • Flag gaps or issues

Stage 4: Lien Priority Analysis

CRITICAL STAGE - Use lien-discovery-skill

  • Identify lien positions (1st, 2nd, 3rd+)
  • Detect HOA foreclosures (senior mortgage survives)
  • Calculate lien satisfaction amounts
  • Determine what buyer inherits

Stage 5: Tax Certificates

  • Check RealTDM for outstanding certificates
  • Calculate tax debt
  • Verify redemption status
  • Add to cost basis

Stage 6: Demographics

  • Census API: median income, vacancy rate
  • Neighborhood score: rental demand, appreciation potential
  • Target zips: 32937, 32940, 32953, 32903
  • Flag: optimal for Third Sword MTR strategy

Stage 7: ML Prediction

  • XGBoost model: third-party purchase probability (64.4% accuracy)
  • Features: plaintiff, property type, judgment amount, location
  • Output: probability score 0-1
  • Brand as "BrevardBidderAI ML" in reports

Stage 8: Max Bid Calculation

Use max-bid-calculator-skill

  • Formula: (ARV×70%) - Repairs - $10K - MIN($25K, 15%×ARV)
  • ARV: After-repair value from BCPAO + comps
  • Repairs: Conservative estimate based on age/condition
  • Holding costs: $10K standard
  • Profit buffer: $25K or 15% ARV (whichever less)

Stage 9: Decision Logic

  • Calculate bid/judgment ratio
  • BID: Ratio ≥ 75% (strong value)
  • REVIEW: Ratio 60-74% (marginal, needs human review)
  • SKIP: Ratio < 60% (insufficient value)
  • DO_NOT_BID: HOA foreclosure with senior mortgage

Stage 10: Report Generation

  • One-page DOCX format
  • BrevardBidderAI branding (NOT Property360)
  • Include: property details, BCPAO photo, max bid, decision, rationale
  • ML prediction prominently displayed
  • Lien analysis summary

Stage 11: Disposition Tracking

  • Log to Supabase auction_results table
  • Fields: property_id, decision, max_bid, actual_bid, outcome
  • Track: won/lost/skipped
  • Calculate: actual ROI vs predicted

Stage 12: Archive

  • Store all data in Supabase historical_auctions
  • Preserve: scraper outputs, ML predictions, decisions
  • Enable: backtesting, model improvements, pattern analysis

Data Sources & APIs

RealForeclose: brevard.realforeclose.com (auction listings) BCPAO: gis.brevardfl.gov/gissrv/rest/services/Base_Map/Parcel_New_WKID2881/MapServer/5 AcclaimWeb: Search by case number, parcel ID RealTDM: Tax certificate search by parcel Census: api.census.gov/data (demographics)

Decision Rules

Auto-BID if:

  • Bid/judgment ≥ 75%
  • No HOA foreclosure issues
  • Clean title chain
  • Target zip code (optional boost)

Flag REVIEW if:

  • Bid/judgment 60-74%
  • Minor title issues
  • Unusual property characteristics
  • High repair uncertainty

Auto-SKIP if:

  • Bid/judgment < 60%
  • Insufficient margin
  • High risk factors

DO_NOT_BID if:

  • HOA foreclosure + senior mortgage survives
  • Title defects
  • Legal complications

Output Format

{
  "property_id": "2024-CA-001234",
  "address": "123 Main St, Melbourne FL 32940",
  "decision": "BID",
  "max_bid": 285000,
  "judgment": 320000,
  "bid_ratio": 0.89,
  "ml_probability": 0.72,
  "lien_analysis": "Clean 1st position",
  "reasoning": "Strong equity position, target zip, clean title"
}

Example Usage

"Analyze the December 3rd foreclosure auction using foreclosure-analysis-skill"

"Process new RealForeclose listings with the Everest Ascent pipeline"

Integration Points

  • Triggers lien-discovery-skill at Stage 4
  • Triggers max-bid-calculator-skill at Stage 8
  • Uses bcpao-data-extraction-skill throughout
  • Logs to Supabase at Stages 11-12

Best Practices

  1. NO GUESSING: Always use actual recorded documents
  2. Verify Everything: Don't trust automated data blindly
  3. Conservative Repairs: Better to overestimate than underestimate
  4. Document Reasoning: Every decision needs clear rationale
  5. Track Performance: Log actual vs predicted outcomes