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ix-optimize

Automate continuous and discrete function optimization with configurable algorithms.

Updated Mar 12, 2026
Search Tags:#algorithm#optimization#machine learning#hyperparameter tuning#function optimization
One-click install
npx skills add https://github.com/GuitarAlchemist/ix --skill ix-optimize
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ix-optimize
Source: https://github.com/GuitarAlchemist/ix/tree/main/.claude/skills/ix-optimize
Command: npx skills add https://github.com/GuitarAlchemist/ix --skill ix-optimize

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

The ix-optimize skill solves the problem of optimizing complex functions using robust and efficient algorithms.

Core Features & Use Cases

  • Function Optimization: Offers methods for minimizing or maximizing complex functions.
  • Algorithm Variety: Includes stochastic (e.g., PSO, SA) and deterministic (e.g., SGD, Adam) algorithms.
  • Customization: Allows users to choose from various algorithms and specify parameters like dimensions, iterations, and function names.
  • Use Case: Optimize a machine learning model's hyperparameters or find the best set of parameters for a complex simulation.

Quick Start

Optimize the function sphere with PSO in 10 dimensions and 100 iterations using the command: optimize --algo pso --function sphere --dim 10 --max-iter 100.

Frequently Asked Questions about ix-optimize

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I optimize machine learning hyperparameters using stochastic algorithms?▼

You can optimize machine learning hyperparameters by running the provided scripts with stochastic algorithms like PSO or SA, specifying the function name, dimensions, and iteration limits. This automates tuning for continuous and discrete functions.

What are the differences between stochastic and deterministic optimization algorithms for function minimization?▼

Function optimization includes stochastic algorithms like PSO and SA, which use randomness to explore spaces, and deterministic algorithms like SGD and Adam, which follow precise gradients. You choose the method based on your function landscape.

Do I need Rust and Cargo to run function optimization scripts?▼

Yes, you need Rust and Cargo installed to run the function optimization scripts. The scripts rely on this environment to execute algorithms and perform continuous and discrete parameter adjustments.

How do I configure iterations and dimensions for a sphere function optimization task?▼

You configure sphere function optimization by passing arguments like `--function sphere`, `--dim`, and `--max-iter` to the script. This specifies the exact dimensions and iteration limits for the algorithm.

Can I use this for simulation parameter adjustment as well as hyperparameter tuning?▼

Yes, you can use it for simulation parameter adjustment. The tool automates the optimization of continuous and discrete functions, supporting both simulation parameters and machine learning hyperparameter tuning.

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