Parameter Optimization
Automatically refines model parameters to maximize performance based on provided data and objectives.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add parameter-optimization npx -- -y @trustedskills/parameter-optimization
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"parameter-optimization": {
"command": "npx",
"args": [
"-y",
"@trustedskills/parameter-optimization"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
This skill optimizes parameters for materials simulations. It automatically adjusts input variables to improve the accuracy and efficiency of these complex calculations. The goal is to minimize error and reduce computational time while maintaining reliable results.
When to use it
- Fine-tuning a simulation model where initial parameter guesses are inaccurate.
- Reducing the runtime of computationally expensive materials simulations.
- Exploring a wide range of parameters quickly to identify optimal settings for specific material properties.
- Automating the process of finding best practices for complex material models.
Key capabilities
- Parameter adjustment
- Error minimization
- Runtime reduction
- Automation
Example prompts
- "Optimize the parameters for my DFT simulation of silicon."
- "Can you find the fastest settings to calculate the elastic modulus of aluminum?"
- "Improve the accuracy of this molecular dynamics simulation by adjusting these parameters: timestep, temperature, and potential function."
Tips & gotchas
The skill requires a well-defined materials simulation workflow as input. Successful optimization depends on having clear metrics for evaluating simulation performance (e.g., error rate, runtime).
Tags
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