菜单
Use this skill whenever the user is working with the Egor optimizer. Triggers on any mention of: Egor optimizer Bayesian optimization in Rust/Python or requests to minimize expensive black-box functions using surrogate models.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
| name | egobox-egor-tuning |
| description | Use this skill whenever the user is working with the Egor optimizer. Triggers on any mention of: Egor optimizer Bayesian optimization in Rust/Python or requests to minimize expensive black-box functions using surrogate models. |
Automatically select and adapt EGOR optimization parameters based on:
If optimization stagnates:
Use KPLS for Gaussian process fitting.
Examples:
Use CoEGO.
Example:
If evaluations can run in parallel: use qEIConfig.
Examples:
Use this skill whenever the user is working with the `gpx` command-line tool from the EGObox project. Triggers on any mention of: the gpx CLI, `gpx fit`, `gpx predict`, `gpx qa`, `gpx spec`, `gpx py`, training a surrogate model from CSV or npy files on the command line, assessing GP model quality from the terminal, generating a Python helper from a saved .gpx/.bin/.json model, or using gpx to run inference on tabular data without writing Python code. Also use when the user wants to inspect or use a .gpx, .bin, or .json model file saved by the Egor optimizer or the Python Gpx.save().
Use this skill whenever the user is working with the EGObox / egobox Python library for Bayesian optimization, Gaussian processes, surrogate modeling, or efficient global optimization (EGO). Triggers on any mention of: egobox, Egor optimizer, Gpx surrogate, Bayesian optimization in Rust/Python, latin hypercube sampling with egobox, mixed-integer optimization with egobox, or requests to minimize expensive black-box functions using surrogate models. Also use when the user pastes egobox code or imports like `import egobox as egx`.
