Agent-Skills.md

Agent Skills: Monte Carlo Simulation

Monte Carlo methods for uncertainty quantification

uncertainty-quantificationID: a5c-ai/babysitter/monte-carlo-simulation

Repository

a5c-ai/babysitter
a5c-aiLicense: MIT
244

Install this agent skill to your local

pnpm dlx add-skill https://github.com/a5c-ai/babysitter/tree/HEAD/plugins/babysitter/skills/babysit/process/specializations/domains/science/mathematics/skills/monte-carlo-simulation

Skill Files

Browse the full folder contents for monte-carlo-simulation.

Download Skill

Loading file tree…

plugins/babysitter/skills/babysit/process/specializations/domains/science/mathematics/skills/monte-carlo-simulation/SKILL.md

Skill Metadata

Name
monte-carlo-simulation
Description
Monte Carlo methods for uncertainty quantification

Monte Carlo Simulation

Purpose

Provides Monte Carlo methods for uncertainty quantification, integration, and probabilistic analysis.

Capabilities

  • Standard Monte Carlo sampling
  • Importance sampling
  • Stratified sampling
  • Quasi-Monte Carlo (Sobol, Halton sequences)
  • Markov chain Monte Carlo
  • Convergence analysis

Usage Guidelines

  1. Sampling Strategy: Choose appropriate sampling method
  2. Sample Size: Determine sufficient sample sizes
  3. Variance Reduction: Apply variance reduction techniques
  4. Convergence: Monitor convergence diagnostics

Tools/Libraries

  • NumPy
  • scipy.stats
  • SALib