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agentic-data-science-competition

Automate Kaggle kernel replication and submission error troubleshooting.

162|13|Updated May 1, 2026
Search Tags:#agentic workflow#spec-driven development#kaggle#submission validation#competition automation#kernel troubleshooting#score stabilization
One-click install
npx skills add https://github.com/FrankS-IntelLab/agentic-kaggle-skill --skill agentic-data-science-competition
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agentic-data-science-competition
Source: https://github.com/FrankS-IntelLab/agentic-kaggle-skill/tree/main
Command: npx skills add https://github.com/FrankS-IntelLab/agentic-kaggle-skill --skill agentic-data-science-competition

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Kaggle competitions often fail due to slow iteration, opaque submission errors (like 400s or invalid kernel mode), and fragile replication of top notebooks. This Skill helps you systematically diagnose failures, replicate winning approaches with dependencies, and automate monitoring so you spend less time guessing and more time improving.

Core Features & Use Cases

  • Score stabilization guidance: Prevents premature decisions by teaching you when leaderboard scores become reliable.
  • Submission troubleshooting: Guides fixes for common Kaggle submission problems such as ZIP formatting issues and incorrect ID handling.
  • Kernel workflow for reliable replication: Shows how to pull/push kernels with dependency metadata and use the correct Kaggle execution mode for valid results.
  • Spec-driven development + delegation: Helps you document a clear SPEC.md plan and delegate implementation to coding agents while enforcing constraints (time, GPU, internet rules).

Quick Start

Ask your agent: "Use the agentic-data-science-competition skill to replicate a top Kaggle kernel and troubleshoot why my submission is returning a 400 error."

Frequently Asked Questions about agentic-data-science-competition

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

FAQPage Schema
How do I fix a 400 error when submitting a Kaggle kernel?▼

Fix Kaggle 400 submission errors by diagnosing ZIP formatting issues and incorrect ID handling. This skill guides you through troubleshooting invalid kernel modes and formatting constraints to ensure valid competition submissions.

What is the best way to replicate a top Kaggle notebook with dependencies?▼

Replicate top Kaggle kernels by pulling and pushing with correct dependency metadata using the -m flag. This ensures dependable notebook handling and correct run versus commit execution modes for reliable results.

How do I know when my Kaggle leaderboard score becomes reliable?▼

Kaggle leaderboard scores become reliable through score stabilization guidance. This skill helps you prevent premature decisions by teaching you when to trust leaderboard fluctuations and when to continue iterating.

How do I use spec-driven development for Kaggle competition automation?▼

Automate Kaggle competitions by documenting a clear SPEC.md plan and delegating implementation to coding agents. This enforces constraints like time, GPU, and internet rules for iterative improvement.

Why does my Kaggle kernel fail during commit mode?▼

Kaggle kernels fail during commit mode due to incorrect execution settings or fragile dependency replication. Use correct run versus commit mode guidance and kernel metadata replication to prevent these failures.

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