simulation-orchestrator
Orchestrate multi-simulation campaigns including parameter sweeps, batch jobs, and result aggregation. Use for running parameter studies, managing simulation batches, tracking job status, combining results from multiple runs, or automating simulation workflows.
npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill simulation-orchestrator --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.
# Simulation Orchestrator ## Goal Provide tools to manage multi-simulation campaigns: generate parameter sweeps, track job execution status, and aggregate results from completed runs. ## Requirements - Python 3.10+ - No external dependencies (uses Python standard library only) - Works on Linux, macOS, and Windows ## Inputs to Gather Before running orchestration scripts, collect from the user: | Input | Description | Example | |-------|-------------|---------| | Base config | Template simulation configuration | `base_config.json` | | Parameter ranges | Parameters to sweep with bounds | `dt:[1e-4,1e-2],kappa:[0.1,1.0]` | | Sweep method | How to sample parameter space | `grid`, `lhs`, `linspace` | | Output directory | Where to store campaign files | `./campaign_001` | | Simulation command | Command to run each simulation | `python sim.py --config {config}` | ## Decision Guidance ### Choosing a Sweep Method ``` Need every combination (full factorial)? ├── YES → Use grid (warning: exponential growth with parameters) └── NO → Is space-filling coverage needed? ├── YES → Use lhs (Latin Hypercube Sampling) └── NO → Use linspace for uniform sampling per parameter ``` | Method | Best For | Sa
- Goal
- Requirements
- Inputs to Gather
- Decision Guidance
- Choosing a Sweep Method
- Campaign Size Guidelines
- Script Outputs (JSON Fields)
- Workflow
- Step 1: Generate Parameter Sweep
- Step 2: Initialize Campaign
- Step 3: Track Job Status
- Step 4: Aggregate Results
- CLI Examples
- Conversational Workflow Example
python3 scripts/sweep_generator.py \ python3 scripts/campaign_manager.py \ python3 scripts/job_tracker.py \ python3 scripts/result_aggregator.py \ Generate 5x3=15 runs varying dt (5 values) and kappa (3 values) Generate LHS samples for 4 parameters with budget of 20 runs Check campaign status Get summary statistics from completed runs
What does the simulation-orchestrator skill do?
Orchestrate multi-simulation campaigns including parameter sweeps, batch jobs, and result aggregation. Use for running parameter studies, managing simulation batches, tracking job status, combining results from multiple runs, or automating simulation workflows.
How do I install it?
Run `npx skills add FreedomIntelligence/OpenClaw-Medical-Skills --skill simulation-orchestrator --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 FreedomIntelligence/OpenClaw-Medical-Skills, a repository with 2,909 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.