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ClaudSkills / Science & Research / data-science-research

agentic-data-science-competition

Category: Science & Research  ·  Sub-category: data-science-research  ·  Last updated:
ai:agent
AI Agent-driven Kaggle competition workflow. Learn from real competition experience: score stabilization patterns, submission troubleshooting, kernel workflows, GPU task delegation, and the spec-driven development approach that achieved top leaderboard positions. Use when: working on any Kaggle competition, analyzing submission failures, setting up automated pipelines, or replicating top notebook solutions.

About this skill (catalog notes)

agentic-data-science-competition includes pricing or quota commentary; 11 code blocks for direct copy-paste. The SKILL.md runs to about 1,351 words, in the catalog's typical mid-range.

Source
github.com/ranxi2001/kaggel-auto-research
License
MIT
Original author
Frank S (IntelLab)
Indexed lastmod
Catalog position
Science & Research · data-science-research
Indexed related skills
10

How agentic-data-science-competition fits the catalog

agentic-data-science-competition sits in the Science & Research category under the data-science-research sub-topic in the ClaudSkills catalog. There are 10 related skills indexed alongside it; comparing a few before installing usually reveals which fits your workflow best.

These notes are auto-generated from features detected in the SKILL.md file and from this catalog's structure — they aren't part of the source repository.

What this skill does

agentic-data-science-competition is a community-contributed Claude Code skill in the data-science-research sub-category. It ships as a SKILL.md file that Claude Code auto-discovers under ~/.claude/skills/agentic-kaggle-competition/ and loads when your prompt matches the skill's trigger.

When to invoke it: Use when: working on any Kaggle competition, analyzing submission failures, setting up automated pipelines, or replicating top notebook solutions.

Who uses this skill

The agentic-data-science-competition Claude Code skill is built for researchers, data scientists, academics, and analysts working with complex data and scientific literature. It's part of ClaudSkills (also referred to as Claude Skills or Claude Code Skills) — the open community-curated registry of 116,000+ SKILL.md files for Anthropic's Claude Code agent and the wider Claude ecosystem (Claude API, Claude Agent SDK).

How to install

Free

Manual install (2 steps)

mkdir -p ~/.claude/skills/agentic-kaggle-competition
curl -L https://claudskills.com/skills/agentic-kaggle-competition/SKILL.md \
  -o ~/.claude/skills/agentic-kaggle-competition/SKILL.md

Or just download SKILL.md directly and drop it into ~/.claude/skills/agentic-kaggle-competition/. Claude Code auto-discovers it on next session.

Skills live at ~/.claude/skills/agentic-kaggle-competition/SKILL.md on macOS/Linux, or %USERPROFILE%\.claude\skills\agentic-kaggle-competition\SKILL.md on Windows. See the full install guide for step-by-step instructions.

Telegram

📱 Install from your phone or desktop Telegram

Open @claudskills_bot on Telegram, tap Open Desktop App, and the desktop app installs this skill for you. Or share the bot link with a colleague — they get the same one-tap install. Learn more →

Pro

One-click install via the desktop app

The ClaudSkills desktop app installs any skill directly into ~/.claude/skills/ with one click — no terminal required. Pro starts at $9/mo or $149 lifetime.

Pro

For the full experience including quality scoring and one-click install features for each skill — upgrade to Pro.

Frequently asked questions

How do I install the agentic-data-science-competition Claude Code skill?
Install via the ClaudSkills desktop app (one click) or copy SKILL.md from the source repository to ~/.claude/skills/agentic-kaggle-competition/SKILL.md and restart Claude Code. Both flows are detailed at claudskills.com/install/.
What does the agentic-data-science-competition skill do?
AI Agent-driven Kaggle competition workflow. Learn from real competition experience: score stabilization patterns, submission troubleshooting, kernel workflows, GPU task delegation, and the spec-driven development approach that achieved top leaderboard positions. Use when: working on any Kaggle competition, analyzing submission failures, setting up automated pipelines, or replicating top notebook solutions.
Is this skill free to install?
Yes. ClaudSkills is an open registry — every skill keeps its source repository's license, and manual install via copy is free. ClaudSkills Pro ($9/mo, $79/yr, or $149 one-time) adds one-click install via the desktop app and a multi-signal Quality Score.
When should I use the agentic-data-science-competition skill?
Use agentic-data-science-competition when your Claude Code task falls under the Science & Research category — specifically in the data science research area. Claude Code auto-discovers installed skills and invokes the right one based on the task description, so you can also ask Claude directly (e.g. "use agentic-data-science-competition" or describe the task and let Claude pick). Browse related skills at /category/science/.
What is a Claude Code skill and how does the agentic-data-science-competition skill fit in?
A Claude Code skill is a SKILL.md file that lives under ~/.claude/skills/<name>/ and tells the Claude Code CLI agent how to perform a specific task (instructions, prompts, allowed tools). Skills are auto-discovered at session start. agentic-data-science-competition is one of 67,000+ skills indexed in the open ClaudSkills catalog, classified under the Science & Research category. Learn more at /learn/what-is-a-claude-skill/.

Attribution & license

Cite this skill

If you reference this skill in a blog post, paper, or documentation, you can cite it as:

APA
Frank S (IntelLab). (2026). agentic-data-science-competition [Claude Code skill]. ClaudSkills. https://claudskills.com/skills/agentic-kaggle-competition/
BibTeX
@misc{agentic-kaggle-competition-2026,
  author    = {Frank S (IntelLab)},
  title     = {agentic-data-science-competition [Claude Code skill]},
  year      = {2026},
  publisher = {ClaudSkills},
  url       = {https://claudskills.com/skills/agentic-kaggle-competition/}
}

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