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From expropriation-law
Analyzes settlement vs. hearing decisions for expropriation files using BATNA, ZOPA, holdout risk scoring, and concession strategy. Produces SETTLE/HEARING/NEGOTIATE recommendations.
npx claudepluginhub reggiechan74/vp-real-estate --plugin expropriation-lawHow this skill is triggered — by the user, by Claude, or both
Slash command
/expropriation-law:settlement-analysis-expertThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
1. **Settlement vs. Hearing Analysis**
README.mdmodules/__init__.pymodules/analysis.pymodules/calculations.pymodules/output_formatters.pymodules/validators.pysamples/sample_1_transmission_easement.jsonscripts/shared_utils/README_FINANCIAL_UTILS.mdscripts/shared_utils/__init__.pyscripts/shared_utils/financial_utils.pyscripts/shared_utils/land_assembly_utils.pyscripts/shared_utils/negotiation_utils.pyscripts/shared_utils/report_utils.pyscripts/shared_utils/risk_utils.pyscripts/shared_utils/schemas/comparable_sales_input_schema.jsonscripts/shared_utils/stakeholder_utils.pyscripts/shared_utils/timeline_utils.pysettlement_analyzer.pysettlement_input_schema.jsonCalculates BATNA, ZOPA, and optimal settlement ranges for infrastructure property acquisitions. Useful for utility easements, transit corridors, and expropriation settlements.
Plans multi-parcel land assembly for transit corridors, highways, transmission lines, pipelines, or mixed-use developments. Scores acquisition priorities, models phasing strategy and holdout risk, builds budgets with contingencies, and quantifies cost of delay.
Drafts and analyzes lease renewal arbitration clauses, covering baseball vs. conventional arbitration, arbitrator selection, and enforceability testing.
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Settlement vs. Hearing Analysis
BATNA Calculation
ZOPA Analysis
Risk Assessment
Strategic Planning
Location: ${CLAUDE_PLUGIN_ROOT}/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
validators.py
calculations.py
analysis.py
output_formatters.py
# 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
Required Fields:
case_id: Case identifiersettlement_offer: Current settlement offer amounthearing_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 counterofferbuyer_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)
{
"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"
}
}
The calculator generates a comprehensive markdown report with:
Executive Summary
Financial Summary
Hearing Risk Analysis
Settlement Scenarios
ZOPA Analysis (if counteroffer provided)
Owner Holdout Risk Assessment (if owner profile provided)
Litigation Risk Assessment (if case factors provided)
negotiation_utils.py:
calculate_batna(): Calculate hearing expected valuecalculate_zopa(): Identify zone of possible agreementprobability_weighted_ev(): Probability-weighted scenario comparisonhearing_cost_benefit(): Cost-benefit analysis settlement vs. hearingoptimal_settlement_range(): Calculate optimal negotiation rangecalculate_concession_strategy(): Generate diminishing concession patternrisk_utils.py:
assess_holdout_risk(): Owner holdout risk scoring (0-30)litigation_risk_assessment(): Litigation probability and durationsensitivity_analysis(): Impact of variable changesfinancial_utils.py:
npv(): Net present value calculationssafe_divide(): Division with zero handlingreport_utils.py:
generate_executive_summary(): Decision-focused summariesformat_markdown_table(): Scenario comparison tableseastern_timestamp(): Report timestampsgenerate_document_header(): Standard headersformat_number(): Currency/percentage formattingSETTLE (High Confidence):
SETTLE (Medium Confidence):
NEUTRAL (Continue Negotiations):
PROCEED TO HEARING:
Hearing Uncertainty Premium:
Holdout Risk Scoring (0-30 scale):
Litigation Probability Factors:
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
Combines with:
Ontario Expropriations Act:
Negotiation Theory:
Real Estate Valuation: