symbolic-equation
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Description
# Symbolic Equation Discovery Discover interpretable scientific equations from data using LLM-guided evolutionary search. ## Input - `$0` — Dataset description, variable names, and physical context ## References - LLM-SR patterns (prompts, evolution, sampling): `~/.claude/skills/symbolic-equation/references/llmsr-patterns.md` ## Workflow (from LLM-SR) ### Step 1: Define Problem Specification Create a specification with: 1. **Input variables**: Physical quantities with types (e.g., `x: np.ndarray`, `v: np.nd
Install symbolic-equation
Run this in your OpenClaw agent to add symbolic-equation from the ClawHub registry.
openclaw skills install symbolic-equationRequires ClawHub registry access. Review the security analysis below before installing.
Security Analysis
Open Source
Code is publicly available for audit.
Community Verified
Reviewed by the ClawHub community.
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Frequently asked questions
Is symbolic-equation safe to install?
symbolic-equation has a SkillsReview security score of 50/100. It is open source and community-verified on ClawHub. Check the full Security Analysis on this page before installing.
How much does symbolic-equation cost?
symbolic-equation is free to install for OpenClaw via ClawHub.
What are the best alternatives to symbolic-equation?
You can compare symbolic-equation side by side with similar OpenClaw skills on the SkillsReview comparison page to find the best fit for your workflow.
How do I install symbolic-equation?
Install symbolic-equation from ClawHub at clawhub.ai/skills/symbolic-equation, or use the install action on this page to copy the command for your OpenClaw agent.
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