"Use PhySO for symbolic regression, class symbolic regression,
Scanned 9/8/2026
Install to Claude Code
npx -y skills add VectorSpaceLab/AREX-Skill --skill physo --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Physo?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/vectorspacelab-physo)More formats (shields.io, HTML) on the badges page.
---
name: physo
description: "Use PhySO for symbolic regression, class symbolic regression,
toolkit-level expression workflows, and benchmark problem loaders."
read_when: "Use when the user names `physo`, `PhySO`, symbolic regression,
ClassSR, toolkit expression helpers, or benchmark problem loaders."
disable-model-invocation: true
metadata:
disco-role: operating
license: MIT
---
# PhySO
Use this skill when working with the `physo` package, the scientific Python symbolic-regression library.
## Install and Import Check
Run [`scripts/physo_skill_doctor.py`](scripts/physo_skill_doctor.py) to confirm the installed package, key public exports, and the CPU scientific stack used by the verified baseline. The checked baseline was PhySO 1.2.0 on CPU; this skill does not claim CUDA verification. Import-time LaTeX warnings are expected when optional display tools are missing.
## Route by Task
- One dataset with `X`, `y`, units, `y_weights`, `candidate_wrapper`, run presets, logging, or Pareto inspection: use [`sub-skills/sr/SKILL.md`](sub-skills/sr/SKILL.md).
- Multiple realizations with shared class constants or realization-specific constants: use [`sub-skills/class-sr/SKILL.md`](sub-skills/class-sr/SKILL.md).
- Prefix expressions, libraries, tokens, `Program`/`VectPrograms`, random sampling, constant optimization, display, or result reloads: use [`sub-skills/toolkit/SKILL.md`](sub-skills/toolkit/SKILL.md).
- Feynman/Class benchmark problems, sample generation, metadata, or symbolic equivalence checks: use [`sub-skills/benchmarks/SKILL.md`](sub-skills/benchmarks/SKILL.md).
## Shared References
- [`references/install-and-smoke.md`](references/install-and-smoke.md): install/import check and smoke commands.
- [`references/troubleshooting.md`](references/troubleshooting.md): cross-cutting import, display, backend, and routing failures.
- [`references/repo-provenance.md`](references/repo-provenance.md): source version, dirty-state snapshot, and evidence paths.
- [`references/repo-routing-metadata.json`](references/repo-routing-metadata.json): router placement metadata for compatible agents.
## Common Starting Points
- Start with the doctor script when the environment or package import is uncertain.
- Route to a sub-skill before drafting commands or code for a user workflow.
- Use the sub-skill smoke scripts for route-specific tiny checks after the environment is known to be usable.
- If the user asks for benchmark reproduction, training-scale sweeps, or maintainer jobfiles, stop at the boundary and keep this runtime skill focused on day-to-day package workflows.
## Boundaries
This skill is self-contained. It does not depend on opening the source checkout at runtime, and it does not cover repo maintenance, release automation, or long benchmark campaigns.
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!