skills/reggiechan74/vp-real-estate/settlement-analysis-expert

settlement-analysis-expert

SKILL.md

You are an expert in settlement scenario analysis vs. expropriation hearing risk, providing decision-focused guidance using probability-weighted expected value, BATNA/ZOPA calculations, and strategic negotiation planning.

Settlement Analysis Expert

Expert in settlement scenario analysis vs. expropriation hearing risk with probability-weighted outcomes, BATNA/ZOPA calculations, and strategic negotiation planning.

When to Use This Skill

Use this skill when:

  • Analyzing settlement offers vs. proceeding to expropriation hearing
  • Calculating BATNA (Best Alternative to Negotiated Agreement)
  • Evaluating ZOPA (Zone of Possible Agreement)
  • Assessing owner holdout risk and litigation probability
  • Developing concession strategies for settlement negotiations
  • Quantifying expected value of hearing outcomes with uncertainty
  • Comparing multiple settlement scenarios with probability weighting

What This Skill Provides

Core Analysis Capabilities

  1. Settlement vs. Hearing Analysis

    • Probability-weighted expected value of hearing outcomes
    • Settlement scenario comparison (current offer, counteroffer, midpoint)
    • Net benefit calculation with risk adjustment
    • Breakeven settlement determination
  2. BATNA Calculation

    • Expected award calculation across low/mid/high scenarios
    • Total hearing costs (legal fees, expert fees, time costs)
    • Net BATNA (total expected cost to buyer)
    • Uncertainty analysis (standard deviation, coefficient of variation)
  3. ZOPA Analysis

    • Zone of possible agreement identification
    • Optimal settlement range recommendations
    • Opening offer, target, and walkaway points
    • Negotiation leverage assessment
  4. Risk Assessment

    • Owner holdout risk scoring (0-30 scale)
    • Litigation probability estimation
    • Expected hearing duration and cost ranges
    • Risk factor identification and mitigation strategies
  5. Strategic Planning

    • Concession strategy with diminishing increments
    • Negotiation rounds planning
    • Timeline and action items
    • Decision confidence levels

Key Metrics Calculated

  • Expected Hearing Cost: Probability-weighted award + legal/expert fees
  • Net Benefit: Settlement savings vs. hearing
  • Holdout Risk Score: 0-30 scale (motivation + sophistication + alternatives)
  • Litigation Probability: 0-100% based on valuation gap, owner profile, case complexity
  • ZOPA Range: Lower bound (seller min) to upper bound (buyer max)
  • Optimal Settlement: Target, floor, ceiling within ZOPA
  • Risk-Adjusted Benefit: Net benefit minus uncertainty premium

Calculator: settlement_analyzer.py

Location: .claude/skills/settlement-analysis-expert/settlement_analyzer.py

Purpose: Analyze settlement scenarios vs. hearing risk with probability-weighted outcomes

Architecture: Modular design following Issue #21 requirements

  • Thin orchestration layer (main calculator)
  • Separate modules for validation, calculations, analysis, output formatting
  • Shared utilities integration (negotiation_utils, risk_utils, financial_utils, report_utils)

Modules

validators.py

  • Input validation against JSON schema
  • Probability distribution validation (must sum to 1.0)
  • Owner profile and case factors validation
  • Award amount ordering validation (low <= mid <= high)

calculations.py

  • Settlement scenario calculations
  • Hearing expected value (BATNA)
  • Net benefit and savings analysis
  • Scenario comparison with probability weighting

analysis.py

  • Settlement vs. hearing decision analysis
  • ZOPA and optimal range calculation
  • Concession strategy generation
  • Owner holdout risk assessment
  • Litigation risk assessment
  • Sensitivity analysis

output_formatters.py

  • Comprehensive markdown reports
  • Executive summaries
  • Scenario comparison tables
  • Financial summaries

Usage

# Basic usage (markdown report to stdout)
python settlement_analyzer.py samples/sample_1_transmission_easement.json

# Generate report to file
python settlement_analyzer.py samples/sample_1_transmission_easement.json --output report.md

# JSON output for programmatic use
python settlement_analyzer.py samples/sample_1_transmission_easement.json --json > results.json

Input Schema

Required Fields:

  • case_id: Case identifier
  • settlement_offer: Current settlement offer amount
  • hearing_probabilities: {low_award, mid_award, high_award} (must sum to 1.0)
  • hearing_costs: {low/mid/high_award_amount, legal_fees, expert_fees, time_cost}

Optional Fields:

  • counteroffer: Owner's counteroffer
  • buyer_max_settlement: Maximum buyer willing to pay (defaults to BATNA)
  • settlement_costs: {legal_fees_to_settle, settlement_risk}
  • owner_profile: {motivation, sophistication, alternatives}
  • case_factors: {valuation_gap, property_value, legal_complexity, precedent_clarity, jurisdiction_history}
  • discount_rate: Annual discount rate for NPV (default 5%)

Full Schema: See settlement_input_schema.json (JSON Schema Draft 2020-12)

Sample Input

{
  "case_id": "HYDRO-2025-001",
  "property_description": "Transmission line easement across 50-acre farm",
  "settlement_offer": 180000,
  "counteroffer": 220000,
  "hearing_probabilities": {
    "low_award": 0.2,
    "mid_award": 0.5,
    "high_award": 0.3
  },
  "hearing_costs": {
    "low_award_amount": 150000,
    "mid_award_amount": 185000,
    "high_award_amount": 230000,
    "legal_fees": 50000,
    "expert_fees": 30000,
    "time_cost": 10000
  },
  "settlement_costs": {
    "legal_fees_to_settle": 5000,
    "settlement_risk": 0.1
  },
  "owner_profile": {
    "motivation": {
      "financial_need": "low",
      "emotional_attachment": "high",
      "business_impact": "moderate"
    },
    "sophistication": {
      "real_estate_experience": "medium",
      "legal_representation": true,
      "previous_negotiations": 1
    },
    "alternatives": {
      "relocation_options": "some",
      "financial_flexibility": "medium",
      "timeline_pressure": "low"
    }
  },
  "case_factors": {
    "valuation_gap": 40000,
    "property_value": 200000,
    "legal_complexity": "medium",
    "precedent_clarity": "mixed",
    "jurisdiction_history": "neutral"
  }
}

Output Report

The calculator generates a comprehensive markdown report with:

  1. Executive Summary

    • Recommendation (SETTLE / PROCEED TO HEARING / NEUTRAL)
    • Rationale and confidence level
    • Financial impact
  2. Financial Summary

    • Settlement total cost vs. hearing total cost
    • Net benefit and savings percentage
    • Breakeven settlement amount
  3. Hearing Risk Analysis

    • Expected award with probability distribution
    • Total costs breakdown (legal, expert, time)
    • Award range (low/mid/high scenarios)
    • Uncertainty metrics (standard deviation, coefficient of variation)
  4. Settlement Scenarios

    • Scenario comparison table (current offer, counteroffer, midpoint)
    • Probability-weighted costs
    • Scenario descriptions
  5. ZOPA Analysis (if counteroffer provided)

    • ZOPA existence and range
    • Optimal settlement range (opening, target, walkaway)
    • Negotiation room and leverage
  6. Owner Holdout Risk Assessment (if owner profile provided)

    • Risk level (LOW/MEDIUM/HIGH/CRITICAL)
    • Holdout probability
    • Score breakdown (motivation, sophistication, alternatives)
    • Key risk factors and mitigation strategies
  7. Litigation Risk Assessment (if case factors provided)

    • Litigation probability
    • Expected duration (months) and cost
    • Risk factors

Shared Utilities Used

negotiation_utils.py:

  • calculate_batna(): Calculate hearing expected value
  • calculate_zopa(): Identify zone of possible agreement
  • probability_weighted_ev(): Probability-weighted scenario comparison
  • hearing_cost_benefit(): Cost-benefit analysis settlement vs. hearing
  • optimal_settlement_range(): Calculate optimal negotiation range
  • calculate_concession_strategy(): Generate diminishing concession pattern

risk_utils.py:

  • assess_holdout_risk(): Owner holdout risk scoring (0-30)
  • litigation_risk_assessment(): Litigation probability and duration
  • sensitivity_analysis(): Impact of variable changes

financial_utils.py:

  • npv(): Net present value calculations
  • safe_divide(): Division with zero handling

report_utils.py:

  • generate_executive_summary(): Decision-focused summaries
  • format_markdown_table(): Scenario comparison tables
  • eastern_timestamp(): Report timestamps
  • generate_document_header(): Standard headers
  • format_number(): Currency/percentage formatting

Decision Framework

Recommendation Thresholds

SETTLE (High Confidence):

  • Net benefit > $10,000
  • Settlement saves material amount vs. hearing
  • Low hearing uncertainty acceptable

SETTLE (Medium Confidence):

  • Net benefit $0 - $10,000
  • Settlement saves small amount vs. hearing
  • Uncertainty may be concerning

NEUTRAL (Continue Negotiations):

  • Net benefit between -$10,000 and $0
  • Costs roughly equivalent
  • Room for negotiation exists within ZOPA

PROCEED TO HEARING:

  • Net benefit < -$10,000
  • Hearing expected to save material amount vs. settlement
  • Settlement offer insufficient

Risk Adjustment

Hearing Uncertainty Premium:

  • Calculate standard deviation of hearing outcomes
  • Apply risk premium = std_dev × 0.5 (risk aversion factor)
  • Risk-adjusted benefit = net_benefit - risk_premium

Holdout Risk Scoring (0-30 scale):

  • 0-9: LOW risk (15% holdout probability)
  • 10-14: MEDIUM risk (30% holdout probability)
  • 15-19: HIGH risk (50% holdout probability)
  • 20-30: CRITICAL risk (70% holdout probability)

Litigation Probability Factors:

  • Valuation gap percentage
  • Owner risk profile
  • Legal complexity
  • Precedent clarity
  • Jurisdiction history

Workflow Integration

Typical Use Cases

1. Initial Settlement Evaluation

# Evaluate initial settlement offer vs. hearing
python settlement_analyzer.py case_data.json --output initial_analysis.md

2. Counteroffer Analysis

# Update JSON with counteroffer, recalculate ZOPA
python settlement_analyzer.py case_data_with_counter.json --output counter_analysis.md

3. Negotiation Strategy Development

# Generate concession strategy based on ZOPA
python settlement_analyzer.py case_data.json --json | jq '.concession_strategy'

4. Board Approval Package

# Comprehensive report for executive decision
python settlement_analyzer.py case_data.json --output board_memo.md

Integration with Other Skills

Combines with:

  • expropriation-compensation-entitlement-analysis: Legal entitlement framework for hearing scenarios
  • injurious-affection-assessment: Quantify damages for hearing cost estimates
  • agricultural-easement-negotiation-frameworks: Farm-specific negotiation strategies
  • negotiation-expert: Evidence-based persuasion and calibrated questions

Key Terms

  • BATNA: Best Alternative to Negotiated Agreement (hearing outcome)
  • ZOPA: Zone of Possible Agreement (overlap between buyer max and seller min)
  • Holdout Risk: Probability owner refuses settlement and forces hearing
  • Litigation Probability: Likelihood of proceeding to expropriation hearing
  • Net Benefit: Settlement savings vs. hearing (positive = settle, negative = hearing better)
  • Expected Award: Probability-weighted hearing compensation
  • Optimal Settlement Range: Opening offer, target, and walkaway points
  • Concession Strategy: Diminishing increments from opening to target
  • Risk-Adjusted Benefit: Net benefit minus uncertainty premium

Expert Guidance

When Settlement Makes Sense

  1. Certainty Value: Settlement eliminates hearing uncertainty
  2. Cost Savings: Avoid legal fees, expert fees, time delays
  3. Relationship Preservation: Maintain goodwill for future dealings
  4. Timeline Advantage: Faster resolution enables project progress
  5. Risk Mitigation: Avoid worst-case hearing outcomes

When Hearing Makes Sense

  1. Insufficient Offer: Settlement offer materially below expected hearing award
  2. Precedent Setting: Need hearing decision for future similar cases
  3. Owner Unreasonable: Counteroffer far exceeds fair value
  4. Strong Case: High confidence in favorable hearing outcome
  5. ZOPA Absent: No overlap between buyer max and seller min

Negotiation Best Practices

  1. Start with BATNA: Know your walkaway point before negotiating
  2. Calculate ZOPA: Identify settlement range where both parties benefit
  3. Use Diminishing Concessions: Signal approaching limit
  4. Anchor High/Low: Buyer starts low, seller starts high, meet in middle
  5. Justify Movements: Each concession tied to new information or reciprocity
  6. Monitor Owner Risk: Adjust strategy based on holdout probability
  7. Document Everything: Create audit trail for decision rationale

References

Ontario Expropriations Act:

  • s.13: Market value determination
  • s.14: Basis of compensation
  • s.18: Disturbance damages
  • s.20: Interest on compensation

Negotiation Theory:

  • Fisher & Ury, "Getting to Yes" (BATNA/ZOPA framework)
  • Kahneman & Tversky, Prospect Theory (risk aversion, loss aversion)
  • Raiffa, "The Art and Science of Negotiation" (optimal settlement ranges)

Real Estate Valuation:

  • USPAP Standard 1: Real Property Appraisal (hearing award estimation)
  • CUSPAP: Canadian Uniform Standards of Professional Appraisal Practice
Weekly Installs
7
GitHub Stars
9
First Seen
Jan 24, 2026
Installed on
claude-code6
gemini-cli5
codex5
opencode5
antigravity4
windsurf4