Agent skill · research science · aiskillstore
simpy
Process-based discrete-event simulation framework in Python. Use this skill when building simulations of systems with processes, queues, resources, and time-based events such as manufacturing systems, service operations, network traffic, logistics, or any system where entities interact with shared resources over time.
Why this skill is useful
Provides domain-specific knowledge on discrete-event simulation patterns and resource management in Python that the AI wouldn't reliably generate on its own.
What it needs
Requires simpy installed locally. About 6k tokens when loaded. Last updated 2026-08-07. 405 stars on the source repository.
What this skill does
SimPy - Discrete-Event Simulation Overview SimPy is a process-based discrete-event simulation framework based on standard Python. Use SimPy to model systems where entities (customers, vehicles, packets, etc.) interact with each other and compete for shared resources (servers, machines, bandwidth, etc.) over time. Core capabilities: Process modeling using Python generator functions Shared resource management (servers, containers, stores) Event-driven scheduling and synchronization Real-time simulations synchronized with wall-clock time Comprehensive monitoring and data collection When to Use This Skill Use the SimPy skill when: 1. Modeling discrete-event systems - Systems where events occur at irregular intervals 2. Resource contention - Entities compete for limited resources (servers, machines, staff) 3. Queue analysis - Studying waiting lines, service times, and throughput 4. Process optimization - Analyzing manufacturing, logistics, or service processes 5. Network simulation - Packet routing, bandwidth allocation, latency analysis 6. Capacity planning - Determining optimal resource levels for desired performance 7. System validation - Testing system behavior before implementation Not suitable for: Continuous simulations with fixed time steps (consider SciPy ODE solvers) Independent processes without resource sharing Pure mathematical optimization (consider SciPy optimize) Quick Start Basic Simulation Structure Resource Usage Pattern Core Concepts 1. Environment The simulation environment manages time and schedules events. 2. Processes Processes are defined using Python generator functions (functions with yield statements). 3. Events Events are the fundamental mechanism for process synchronization. Processes yield events and resume when those events are triggered. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aiskillstore/simpy