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apex-risk-quantification

Quantify project risk with Monte Carlo, EMV, and sensitivity analysis.

Updated Mar 31, 2026
Search Tags:#risk#sensitivity#decision-tree#monte-carlo#contingency#emv
One-click install
npx skills add https://github.com/JaviMontano/metodologia-propuesta-agent-public --skill apex-risk-quantification
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: apex-risk-quantification
Source: https://github.com/JaviMontano/metodologia-propuesta-agent-public/tree/main/.claude/skills/governance/risk-quantification
Command: npx skills add https://github.com/JaviMontano/metodologia-propuesta-agent-public --skill apex-risk-quantification

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Quantitative risk analysis is essential for turning qualitative risk assessments into actionable, numeric projections for schedules and budgets, enabling data-driven contingency planning.

Core Features & Use Cases

  • Monte Carlo simulations to produce schedule and cost distributions (P50/P80/P90) and confidence intervals.
  • EMV and sensitivity (tornado) analyses to identify top risk drivers and quantify potential impacts.
  • Decision-tree and scenario analysis to compare risk response options with transparent, auditable outcomes.
  • Deliverables generation including reports, charts, and structured risk registers for governance and stakeholder communication.

Quick Start

Run a full Monte Carlo risk quantification using the project risk register and baseline schedules to generate EMV, confidence levels, and sensitivity outputs.

Frequently Asked Questions about apex-risk-quantification

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I convert qualitative project risks into numeric schedule and cost projections?▼

Monte Carlo risk analysis converts qualitative project risks into numeric schedule and cost projections using probabilistic simulations. It generates confidence intervals like P50, P80, and P90 to support data-driven budgeting and contingency planning.

How do I calculate Expected Monetary Value and sensitivity for a project risk register?▼

Expected Monetary Value (EMV) and sensitivity analysis quantify potential impacts from your project risk register. This process produces EMV tables and tornado diagrams to identify top risk drivers and transparently compare risk response options.

When do I need Monte Carlo simulations and decision-tree analysis for contingency planning?▼

Monte Carlo simulations and decision-tree analysis are needed for contingency planning when comparing risk response options requires transparent, auditable outcomes. They produce confidence intervals and structured risk registers for stakeholder communication and governance.

Can I generate tornado diagrams and P80 confidence intervals from a baseline schedule?▼

Yes, you can generate tornado diagrams and P80 confidence intervals from a baseline schedule. Monte Carlo simulations applied to your baseline produce cost distributions, confidence levels, and sensitivity outputs to identify top risk drivers.

What is the best way to compare risk response options using quantitative risk analysis?▼

The best way to compare risk response options is using decision-tree and scenario analysis. This approach evaluates potential impacts against baseline schedules, producing auditable outcomes, EMV tables, and structured reports for transparent decision making.

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