agent-based-simulator
Agent-based modeling skill for simulating complex adaptive systems with heterogeneous interacting agents
npx skills add a5c-ai/babysitter --skill agent-based-simulator --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.
# Agent-Based Simulator ## Overview The Agent-Based Simulator skill provides capabilities for modeling complex adaptive systems through the simulation of heterogeneous, interacting agents. It enables bottom-up understanding of emergent market behaviors, customer dynamics, and competitive interactions for strategic decision support. ## Capabilities - Agent definition and behavior modeling - Environment and spatial modeling - Interaction rules specification - Emergent behavior observation - Parameter sweeping - Ensemble simulation runs - Visualization and animation - Statistical analysis of outcomes ## Used By Processes - War Gaming and Competitive Response Modeling - Market Sizing and Opportunity Assessment - Customer Segmentation Analysis ## Usage ### Agent Definition ```python # Define customer agent customer_agent = { "type": "Customer", "attributes": { "budget": {"distribution": "normal", "mean": 1000, "std": 200}, "brand_loyalty": {"distribution": "uniform", "min": 0, "max": 1}, "price_sensitivity": {"distribution": "beta", "alpha": 2, "beta": 5}, "preferred_features": ["list of features"] }, "behaviors": { "purchase_decision": { "triggers": ["need_arises", "promotion_seen"], "
- Overview
- Capabilities
- Used By Processes
- Usage
- Agent Definition
- Environment Definition
- Interaction Rules
- Simulation Configuration
- Input Schema
- Output Schema
- Best Practices
- Use Cases
- Integration Points
What does the agent-based-simulator skill do?
Agent-based modeling skill for simulating complex adaptive systems with heterogeneous interacting agents
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill agent-based-simulator --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.