# Simulation Reasoning

> Simulates complex system behaviors over time under varying initial conditions or agent interactions.

- Skill: `felipecustodio/simulation-reasoning` (Agent Skill, multi-file: 3 files)
- Install (CLI): `npx skillmds@latest add felipecustodio/simulation-reasoning`
- Raw SKILL.md: https://api.skillmd.com/api/skills/felipecustodio/simulation-reasoning/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- License: MIT
- Author: felipecustodio (https://skillmd.com/u/felipecustodio)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/felipecustodio/simulation-reasoning

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## Overview & Purpose

Simulation Reasoning conducts step-by-step dynamic modeling of complex systems to observe emergent behavior, identify tipping points, and evaluate long-term outcomes under synthetic conditions.

## When to Use

- **Complex Dynamic Systems**: Queueing systems, load behavior under traffic bursts, concurrency race conditions.
- **Scenario Planning**: Simulating multi-agent market conditions, adoption curves, or failure cascades.

## Execution Workflow

1. **Define State Variables & Rules**: Establish system entities, parameters, and transition rules.
2. **Initialize Simulation**: Set initial seed conditions and time-step size ($\Delta t$).
3. **Step Through Epochs**: Execute state transitions iteratively over $N$ time steps.
4. **Analyze Emergent Patterns**: Identify bottlenecks, steady states, or catastrophic failure modes.

## Expected Output Contract

```markdown
### Simulation Results
- **Initial Conditions**: [Seed Parameters]
- **Execution Horizon**: [N Time Steps]
- **Key Metrics over Time**: [Summary Table / Stats]
- **Emergent Insights**: [System Behavior Analysis]
```

## Scripts

- `scripts/simulation_reasoning.py` - Deterministic evaluation, state validation, and CLI tool for simulation-reasoning.