$npx skillfedfor your agent

cwicr-risk-calculator

Quantify cost estimate uncertainty by running Monte Carlo simulations across work items with configurable risk levels and probability distributions. The tool generates confidence intervals (P50, P80, P90) and identifies high-impact risk items to guide contingency planning.

CWICR Risk Calculator computes risk-adjusted cost estimates using Monte Carlo simulation and probability distributions.

AI-generated summary based on this skill's SKILL.md

254 65 MITupdated by datadrivenconstruction

Decision gist · record as of 2026-02-14

CWICR Risk Calculator computes risk-adjusted cost estimates using Monte Carlo simulation and probability distributions. Quantify cost estimate uncertainty by running Monte Carlo simulations across work items with configurable risk levels and probability distributions. The tool generates confidence intervals (P50, P80, P90) and identifies high-impact risk items to guide contingency planning.

manual: git clone https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction → cp -r DDC_Skills_for_AI_Agents_in_Construction/1_DDC_Toolkit/CWICR-Database/cwicr-risk-calculator ~/.claude/skills/cwicr-risk-calculator
1_DDC_Toolkit/CWICR-Database/cwicr-risk-calculator/SKILL.md · version 2450cf05

Use it when

  • cwicr-risk-calculator produces P50, P80, and P90 confidence intervals for your cost estimates.
  • Yes.

Verify before relying

Read SKILL.md below before installing (3 files). Open directory: indexed for reading, not audited.

Same gist for agents: .md · .json

Install

datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction/cwicr-risk-calculator · repository language: Python

Open directory. Skills are indexed for reading, not audited. Review a skill's body before installing it.

Frequently asked questions

AI-generated answers based on this skill's SKILL.md and metadata

How does cwicr-risk-calculator calculate risk-adjusted cost estimates?

cwicr-risk-calculator uses Monte Carlo simulation to quantify cost estimate uncertainty across work items. The tool runs thousands of iterations using configurable probability distributions and risk levels for each item, then aggregates results to generate risk-adjusted totals that reflect the full range of possible project costs.

What confidence intervals does cwicr-risk-calculator generate?

cwicr-risk-calculator produces P50, P80, and P90 confidence intervals for your cost estimates. P50 represents the median expected cost, P80 indicates the cost level with 80% confidence of not being exceeded, and P90 provides a high-confidence upper bound—helping you set realistic contingency reserves.

Can cwicr-risk-calculator determine appropriate contingency allowances by project phase?

Yes. cwicr-risk-calculator analyzes cost uncertainty across different project phases and recommends phase-specific contingency allowances based on the risk profiles and probability distributions you configure for work items in each phase.

How does cwicr-risk-calculator identify high-risk work items?

cwicr-risk-calculator flags work items with the highest cost exposure by analyzing their probability distributions and sensitivity to cost drivers. This prioritization helps you focus risk mitigation efforts on activities that pose the greatest threat to your project budget.

What probability distributions does cwicr-risk-calculator support for Monte Carlo simulation?

cwicr-risk-calculator supports triangular distribution cost modeling and other configurable probability distributions for Monte Carlo simulation. You define the distribution parameters for each work item to reflect your uncertainty about costs.

Can cwicr-risk-calculator perform sensitivity analysis on cost drivers?

Yes. cwicr-risk-calculator includes sensitivity analysis capabilities to test how changes in key cost drivers affect your overall estimate. This helps you understand which factors have the greatest influence on project cost uncertainty and where to focus estimation refinement.

SKILL.md

Rendered from the published skill. Quoted content, verbatim.

CWICR Risk Calculator

Business Case

Problem Statement

Cost estimates have inherent uncertainty: - What contingency to apply? - What is the confidence range? - Which items have highest risk? - How to quantify uncertainty?

Solution

Risk-adjusted cost calculations using contingency analysis, Monte Carlo simulation, and probability distributions based on CWICR cost data.

Business Value
  • Informed decisions - Understand estimate uncertainty
  • Appropriate contingency - Data-driven risk allowance
  • Confidence intervals - P50, P80, P90 estimates
  • Risk prioritization - Focus on high-impact items

Technical Implementation

```python import pandas as pd import numpy as np from typing import Dict, Any, List, Optional, Tuple from dataclasses import

(truncated - see the full file via the links below)

File tree — 3 files
1_DDC_Toolkit/CWICR-Database/cwicr-risk-calculator/SKILL.md
1_DDC_Toolkit/CWICR-Database/cwicr-risk-calculator/claw.json
1_DDC_Toolkit/CWICR-Database/cwicr-risk-calculator/instructions.md

Let your AI agent find skills like this

Example. Real query, live index.

You found this page by searching. An agent finds it by wishing: SkillFed indexes 56,283 agent skills by what they can do, searchable in plain language.

wish › “Calculate risk-adjusted cost estimates with Monte Carlo simulation”

Give your agent the search over MCP, or paste the wish link into any chat. No install? Search from any chat →

Related skills

cwicr-comparison-tool
by datadrivenconstruction · datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction

This tool enables side-by-side analysis of CWICR-based cost estimates, surfacing quantity and cost differences between versions, design alternatives, or projects. It categorizes variances by significance level and produces summaries by work category to support objective decision-making and audit trails.

MITupdated Feb 2026
★ 254repo stars
scenario-planner
by datadrivenconstruction · datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction

Scenario Planner lets you model different construction project approaches and see how each affects total cost, timeline, and resource needs. Create alternatives, run comparisons, and identify trade-offs to make better project decisions.

MITupdated Feb 2026
★ 254repo stars
cwicr-bid-analyzer
by datadrivenconstruction · datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction

This skill evaluates contractor bids by comparing them against CWICR-based market benchmarks, flagging unusual pricing patterns and cost composition issues. It produces detailed line-item analysis with variance metrics to support fair, documented bid decisions.

MITupdated Feb 2026
★ 254repo stars
construction-expert
by personamanagmentlayer · personamanagmentlayer/pcl

construction-expert brings structured project oversight to construction workflows through intelligent persona-driven automation. Leverage scheduling, budget management, and real-time progress monitoring to keep teams aligned and projects on track. Built on Persona Control Language (PCL) for seamless AI coordination.

Apache-2.0updated Mar 2026
★ 38repo stars
risk-analysis
by HKUDS · HKUDS/Vibe-Trading

Risk-analysis provides quantitative methods for measuring portfolio risk through Value at Risk, Conditional Value at Risk, maximum drawdown analysis, and Monte Carlo simulation. It includes historical and parametric VaR calculation, tail-risk analysis via extreme value theory, and stress-testing frameworks using both historical scenarios and hypothetical shock models.

MITupdated Jul 2026
★ 28,096repo stars
risk-metrics-calculation
by wshobson · wshobson/agents

Measure portfolio risk across volatility, tail risk, drawdown, and risk-adjusted performance dimensions. Includes Value at Risk, Expected Shortfall, and drawdown analysis with support for multiple time horizons and stress testing scenarios.

MITupdated Jul 2026
★ 38,308repo stars
Tags
probabilistic-modelingcost-uncertaintycontingency-planningstatistical-simulationrisk-quantificationconstruction-financeestimate-confidencescenario-analysis