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tabpfn-core

Defines shared identity, workflow rules, and conventions for TabPFN skills.

5|1|Updated Feb 25, 2026
Search Tags:#workflow#baseline#competition#guardrails#kaggle#tabpfn
One-click install
npx skills add https://github.com/dianaprior/kaggle-competition-agent-skill --skill tabpfn-core
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: tabpfn-core
Source: https://github.com/dianaprior/kaggle-competition-agent-skill/tree/main/.claude/skills/tabpfn-core
Command: npx skills add https://github.com/dianaprior/kaggle-competition-agent-skill --skill tabpfn-core

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Shared identity, behavior rules, workflow principles, and project conventions for TabPFN tabular competition skills. Referenced by tabpfn-classify, tabpfn-regress, and tabpfn-explore — not invoked directly.

Core Features & Use Cases

  • Defines Claude's role, the four-step workflow, and guardrails; serves as background context loaded by the task skills.
  • Provides action-oriented directives to prioritize fast baseline submissions and controlled resource usage.
  • Establishes conventions for references and auxiliary materials used by all TabPFN skills.

Quick Start

Follow the Prime Directive to produce a fast TabPFN baseline submission.

Frequently Asked Questions about tabpfn-core

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

FAQPage Schema
How do I set up a baseline workflow for Kaggle tabular competitions using TabPFN?▼

This core workflow defines shared identity, behavior rules, and a four-step process for TabPFN Kaggle competition skills. It acts as background context loaded by classify, regress, and explore task skills to ensure consistent decision-making.

What are the guardrails for using TabPFN in data competitions?▼

TabPFN competition guardrails enforce controlled resource usage and action-oriented directives to prioritize fast baseline submissions. These rules ensure safe operation when applied to classify, regress, and explore tasks during Kaggle competitions.

Do I need to invoke the TabPFN core workflow directly for classification tasks?▼

No, the TabPFN core workflow is not invoked directly. It provides shared identity and behavior rules referenced by tabpfn-classify, tabpfn-regress, and tabpfn-explore skills, serving as background context for those specific task skills.

How does the TabPFN baseline workflow handle regression and classification differently?▼

The TabPFN workflow provides shared conventions and guardrails applied uniformly across classify, regress, and explore tasks. It establishes consistent decision-making and safe resource usage rules rather than handling specific algorithms differently.

Can I use TabPFN competition skills for exploratory data analysis?▼

Yes, the TabPFN workflow is applied to explore tasks alongside classify and regress operations. It provides shared identity and behavior rules that ensure consistent decision-making during exploratory data analysis in Kaggle competitions.

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