Margin Simulation

Model the full commercial viability of any agency engagement — from a single campaign to a multi-year retainer — using deterministic P&L analysis, Monte Carlo simulation for uncertainty quantification, leakage detection, sensitivity analysis, and scenario modeling.

How This Skill Thinks

This skill does not just calculate margin. It orchestrates a pipeline:

1. Script execution (scripts/margin_engine.py): Runs the deterministic P&L, Monte Carlo simulation (5,000 draws), leakage detection, and sensitivity analysis programmatically
2. Reference lookup (references/leakage_and_pricing.md): Provides benchmark data, leakage taxonomy, pricing strategies, and the 70/30 model impact on margin
3. Qualitative judgment (Claude): Interprets results in context — client relationship dynamics, market positioning, competitive pressure, historical patterns — and shapes the recommendation
4. Visual output (Visualizer): Renders the margin dashboard as an inline widget with Monte Carlo distribution, leakage waterfall, and scenario cards

The script produces numbers. Claude produces insight. The Visualizer makes it actionable. None of these replaces the other.

Quick Reference