happy-sim-analyze

Name: happy-sim-analyze
Availability: InStock
Author: Adam

Analyze happy-simulator simulation results for health, metrics, and bottlenecks.

11|Updated Mar 16, 2024

Search Tags:#performance #analysis #metrics #simulation #bottleneck #happysimulator

Ready to run

npx skills add https://github.com/adamfilli/happy-simulator --skill happy-sim-analyze

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: happy-sim-analyze
Source: https://github.com/adamfilli/happy-simulator/tree/main/.claude/skills/happy-sim-analyze
Command: npx skills add https://github.com/adamfilli/happy-simulator --skill happy-sim-analyze

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps users understand the performance and behavior of discrete-event simulations by analyzing their results and providing actionable insights.

Core Features & Use Cases

Simulation Analysis: Interprets simulation output from happy-simulator, including throughput, latency, and queue depths.
Phase Detection: Identifies distinct phases like warmup, steady-state, and anomalies within simulation data.
Bottleneck Identification: Pinpoints performance bottlenecks within the simulated system.
Use Case: After running a complex queuing system simulation, use this Skill to determine if the system is stable, identify the slowest component, and get recommendations on how to improve its performance.

Quick Start

Analyze the simulation results from the file 'simulation_log.txt'.

Frequently Asked Questions about happy-sim-analyze

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

FAQPage Schema

How do I analyze discrete-event simulation results for bottlenecks?▼

To analyze discrete-event simulation results, this Skill processes output from the happy-simulator library to pinpoint performance bottlenecks, evaluate system stability, and identify the slowest components within your simulated system.

What performance metrics are included in a discrete-event simulation analysis?▼

Performance metrics in a discrete-event simulation analysis include throughput, latency, and queue depths. The analysis interprets SimulationSummary objects, latency trackers, and probe data to provide insights into system health and behavior.

Can I detect warmup and steady-state phases in my simulation data?▼

Yes, you can detect warmup and steady-state phases in your simulation data. The analysis includes phase detection capabilities that identify distinct phases like warmup, steady-state, and anomalies within the simulation results.

Does this tool work with happy-simulator latency trackers and probe data?▼

Yes, this tool works with happy-simulator latency trackers and probe data. It supports the analysis of SimulationSummary objects, latency trackers, and probe data generated by the happy-simulator library to produce full analysis reports.

What is the best way to identify a queuing system bottleneck after running a simulation?▼

The best way to identify a queuing system bottleneck after running a simulation is to analyze the simulation log file. This process pinpoints performance bottlenecks, determines system stability, and provides recommendations for performance improvement.