supply-chain-simulation-engine
Supply chain discrete-event simulation for scenario testing and optimization
Profile →npx skills add a5c-ai/babysitter --skill supply-chain-simulation-engine --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Supply Chain Simulation Engine ## Overview The Supply Chain Simulation Engine provides discrete-event simulation capabilities for testing supply chain scenarios, policies, and disruptions. It enables what-if analysis, Monte Carlo integration, and performance optimization through simulation-based experimentation. ## Capabilities - **End-to-End Supply Chain Simulation**: Full network modeling - **What-If Scenario Testing**: Policy and configuration testing - **Disruption Impact Modeling**: Shock and recovery simulation - **Policy Optimization Testing**: Inventory, sourcing policy experiments - **Monte Carlo Integration**: Stochastic variability modeling - **Sensitivity Analysis**: Parameter impact assessment - **Animation and Visualization**: Visual simulation playback - **Performance Metric Tracking**: KPI measurement through simulation ## Input Schema ```yaml simulation_request: network_model: nodes: array - node_id: string type: string # supplier, plant, DC, customer capacity: float processing_time: object inventory_policy: object arcs: array - from_node: string to_node: string lead_time: object cost: float demand_model: patterns: array variability: object events: array # promot
- Overview
- Capabilities
- Input Schema
- Output Schema
- Usage
- Inventory Policy Simulation
- Disruption Impact Analysis
- Network Configuration Testing
- Integration Points
- Process Dependencies
- Best Practices
What does the supply-chain-simulation-engine skill do?
Supply chain discrete-event simulation for scenario testing and optimization
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill supply-chain-simulation-engine --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.