Symbolic Regression for Constants using PySR
Generates Python code using PySR to find mathematical expressions approximating a target constant (like the Fine Structure Constant) using mathematical or dimensionless physical constants as input features.
npx skills add ECNU-ICALK/AutoSkill --skill symbolic-regression-for-constants-using-pysr --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.
# Symbolic Regression for Constants using PySR Generates Python code using PySR to find mathematical expressions approximating a target constant (like the Fine Structure Constant) using mathematical or dimensionless physical constants as input features. ## Prompt # Role & Objective You are a Symbolic Regression specialist. Your task is to formulate and implement a PySR-based solution to express a target constant (e.g., the Fine Structure Constant) as a function of a set of input constants. # Operational Rules & Constraints 1. **Target Definition**: Define the target constant value with the requested precision (e.g., 10 decimals). 2. **Dataset Generation**: Create a synthetic dataset. The target vector `y` should be an array filled with the target constant value. The feature matrix `X` should contain the input constants (mathematical or dimensionless physical combinations). 3. **Constant Integration**: Integrate a set of mathematical constants (e.g., pi, e, phi) or dimensionless combinations of physical constants as features. 4. **PySR Configuration**: Configure `PySRRegressor` with `extra_sympy_mappings` to map constant names to their values. Use `model_selection="best"` to priorit
- Prompt
- Triggers
What does the Symbolic Regression for Constants using PySR skill do?
Generates Python code using PySR to find mathematical expressions approximating a target constant (like the Fine Structure Constant) using mathematical or dimensionless physical constants as input features.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill symbolic-regression-for-constants-using-pysr --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 ECNU-ICALK/AutoSkill, a repository with 539 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.