Automl Skill
LeoYeAI/openclaw-master-skills
AutoML 自动化机器学习技能 | Automated Machine Learning Skill. An agent skill from LeoYeAI/openclaw-master-skills.
This skill should be used when the user asks to "learn from Kaggle", "study Kaggle solutions", "analyze Kaggle competitions", or mentions Kaggle competition URLs.
Install Kaggle Learner
$ npx skills add Galaxy-Dawn/claude-scholar --skill kaggle-learner -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Galaxy-Dawn/claude-scholar kaggle-learner --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/Galaxy-Dawn/claude-scholar.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/kaggle-learner .claude/skills/kaggle-learner && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "kaggle-learner" agent skill from https://github.com/Galaxy-Dawn/claude-scholar/tree/main/skills/kaggle-learner into .claude/skills/kaggle-learner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "kaggle-learner", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/Galaxy-Dawn/claude-scholar/tree/main/skills/kaggle-learnerType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add Galaxy-Dawn/claude-scholar --skill kaggle-learner -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Galaxy-Dawn/claude-scholar kaggle-learner --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Galaxy-Dawn/claude-scholar.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/kaggle-learner .agents/skills/kaggle-learner && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "kaggle-learner" agent skill from https://github.com/Galaxy-Dawn/claude-scholar/tree/main/skills/kaggle-learner into .agents/skills/kaggle-learner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "kaggle-learner", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Galaxy-Dawn/claude-scholar --skill kaggle-learner -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Galaxy-Dawn/claude-scholar kaggle-learner --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Galaxy-Dawn/claude-scholar.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/kaggle-learner .cursor/skills/kaggle-learner && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "kaggle-learner" agent skill from https://github.com/Galaxy-Dawn/claude-scholar/tree/main/skills/kaggle-learner into .cursor/skills/kaggle-learner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "kaggle-learner", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/Galaxy-Dawn/claude-scholar.git --path skills/kaggle-learner--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add Galaxy-Dawn/claude-scholar --skill kaggle-learner -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Galaxy-Dawn/claude-scholar kaggle-learner --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Galaxy-Dawn/claude-scholar.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/kaggle-learner .gemini/skills/kaggle-learner && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "kaggle-learner" agent skill from https://github.com/Galaxy-Dawn/claude-scholar/tree/main/skills/kaggle-learner into .gemini/skills/kaggle-learner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "kaggle-learner", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install Galaxy-Dawn/claude-scholar kaggle-learnerInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add Galaxy-Dawn/claude-scholar --skill kaggle-learner -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Galaxy-Dawn/claude-scholar.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/kaggle-learner .github/skills/kaggle-learner && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "kaggle-learner" agent skill from https://github.com/Galaxy-Dawn/claude-scholar/tree/main/skills/kaggle-learner into .github/skills/kaggle-learner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "kaggle-learner", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Galaxy-Dawn/claude-scholar --skill kaggle-learner -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Galaxy-Dawn/claude-scholar kaggle-learner --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Galaxy-Dawn/claude-scholar.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/kaggle-learner .opencode/skills/kaggle-learner && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "kaggle-learner" agent skill from https://github.com/Galaxy-Dawn/claude-scholar/tree/main/skills/kaggle-learner into .opencode/skills/kaggle-learner/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "kaggle-learner", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
kaggle-learner- GitHub stars
- 5.7k
- Used in
- 1 other repo
- Token cost
- ~940 tokens
- SKILL.md length
- 329 words
- Files
- 20 (incl. references)
- Skills in repo
- 34
- Repo updated
- First seen
- Licence
- MIT
At a glance
This skill should be used when the user asks to "learn from Kaggle", "study Kaggle solutions", "analyze Kaggle competitions", or mentions Kaggle competition URLs.
- Works in 4 steps: Provide the Kaggle competition URL → The kaggle-miner agent will extract the… → Knowledge is automatically added to the… → …
- Asks to learn from Kaggle
- SKILL.md covers Overview, When to Use, Knowledge Categories and Quick Reference, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Kaggle Learner is an agent skill from Galaxy-Dawn/claude-scholar. This skill should be used when the user asks to "learn from Kaggle", "study Kaggle solutions", "analyze Kaggle competitions", or mentions Kaggle competition URLs. Provides access to extracted knowledge from winning Kaggle solutions across NLP, CV, time series, tabular, and multimodal domains.
Its SKILL.md is about 940 tokens, which your agent loads only when the skill is triggered. The skill folder holds 25 other files, including reference files (for example `references/knowledge/.archive/cv.md`, `references/knowledge/.archive/multimodal.md` and `references/knowledge/.archive/nlp.md`).
It sits in Data & Analytics, covering Natural language processing and Forecasting and time series. It works with Kaggle. The repository describes itself as: Semi-automated research assistant for academic research and software development. Supports Claude Code, Codex CLI, Kimi Code CLI, and OpenCode across ideation, coding… The licence is MIT.
When your agent uses it
- Asks to learn from Kaggle
- Study Kaggle solutions
- Analyze Kaggle competitions
- Mentions Kaggle competition URLs
Example prompts
- “learn from Kaggle”
- “study Kaggle solutions”
- “analyze Kaggle competitions”
- “/kaggle-learner”
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- Provide the Kaggle competition URL
- The kaggle-miner agent will extract the winning solution
- Knowledge is automatically added to the relevant category
- 前排方案详细技术分析 (Front-runner Detailed Technical Analysis) is automatically included
What it can do on your machine
Read from SKILL.md and the folder at commit 9037873. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Kaggle Learner loads about 940 tokens when it runs, and up to ~285k if it reads all its reference files. Until then it costs about 77 tokens; SKILL.md has 329 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from Galaxy-Dawn/claude-scholar at commit 9037873, republished under its MIT licence (© Galaxy-Dawn). 329 words, ~940 tokens.
Download SKILL.mdSave it as
.claude/skills/kaggle-learner/SKILL.md (or your agent's skills folder). This skill also uses 19 other files; get the full folder from GitHub.- name
- kaggle-learner
- description
- This skill should be used when the user asks to "learn from Kaggle", "study Kaggle solutions", "analyze Kaggle competitions", or mentions Kaggle competition URLs. Provides access to extracted knowledge from winning Kaggle solutions across NLP, CV, time series, tabular, and multimodal domains.
- version
- 0.1.0
Kaggle Learner
Extract and apply knowledge from Kaggle competition winning solutions. This skill provides access to a continuously updated knowledge base of techniques, code patterns, and best practices from top Kaggle competitors.
Overview
Kaggle competitions are at the forefront of practical machine learning. Winning solutions often innovate with novel techniques, clever feature engineering, and optimized pipelines. This skill captures that knowledge and makes it accessible for your projects.
When to Use
Use this skill when:
- Studying for a Kaggle competition
- Looking for proven techniques in a specific domain (NLP, CV, etc.)
- Need code templates for common ML tasks
- Want to learn from competition winners
Knowledge Categories
| Category | Focus | Directory |
|---|---|---|
| NLP | Text classification, NER, translation, LLM applications | references/knowledge/nlp/ |
| CV | Image classification, detection, segmentation, generation | references/knowledge/cv/ |
| Time Series | Forecasting, anomaly detection, sequence modeling | references/knowledge/time-series/ |
| Tabular | Feature engineering, traditional ML, structured data | references/knowledge/tabular/ |
| Multimodal | Cross-modal tasks, vision-language models | references/knowledge/multimodal/ |
文件组织结构：每个竞赛一个独立的 markdown 文件，按 domain 分类到对应目录。
示例：
time-series/birdclef-plus-2025.mdnlp/aimo-2-2025.md
Quick Reference
To learn from a competition:
- Provide the Kaggle competition URL
- The kaggle-miner agent will extract the winning solution
- Knowledge is automatically added to the relevant category
- 前排方案详细技术分析 (Front-runner Detailed Technical Analysis) is automatically included
To browse existing knowledge:
- 浏览相关 domain 目录：
references/knowledge/[domain]/ - 每个竞赛一个独立文件，包含：
- Competition Brief (竞赛简介)
- 前排方案详细技术分析 (前排方案详细技术分析) ⭐
- Code Templates (代码模板)
- Best Practices (最佳实践)
Self-Evolving
This skill automatically updates its knowledge base when the kaggle-miner agent processes new competitions. The more you use it, the smarter it becomes.
Knowledge Extraction Standard
每次从 Kaggle 竞赛提取知识时，必须包含以下标准部分：
必需内容清单
| 部分 | 说明 | 必需性 |
|---|---|---|
| Competition Brief | 竞赛背景、任务描述、数据规模、评估指标 | ✅ 必需 |
| Original Summaries | 前排方案的简要概述 | ✅ 必需 |
| 前排方案详细技术分析 | Top 20 方案的核心技巧和实现细节 | ✅ 必需 ⭐ |
| Code Templates | 可复用的代码模板 | ✅ 必需 |
| Best Practices | 最佳实践和常见陷阱 | ✅ 必需 |
| Metadata | 数据源标签和日期 | ✅ 必需 |
前排方案详细技术分析格式
每个前排方案应包含：
- 排名和团队/作者
- 核心技巧列表 (3-6 个关键技术点)
- 实现细节 (具体的参数、配置、数据)
示例格式：
**排名 Place - 核心技术名称 (作者)**
核心技巧：
- **技巧1**: 简短说明
- **技巧2**: 简短说明
实现细节：
- 具体参数、模型、配置
- 数据和实验结果建议覆盖 Top 20 方案，获取更多前排选手的创新技巧
Additional Resources
Knowledge Directories
references/knowledge/nlp/- NLP competition techniquesreferences/knowledge/cv/- Computer vision techniquesreferences/knowledge/time-series/- Time series methodsreferences/knowledge/tabular/- Tabular data approachesreferences/knowledge/multimodal/- Multimodal solutions
Competition Examples
- BirdCLEF+ 2025 (
time-series/birdclef-plus-2025.md) - 包含完整的 Top 14 前排方案详细技术分析 - BirdCLEF 2024 (
time-series/birdclef-2024.md) - 包含 Top 3 方案详细技术分析 - AIMO-2 (
nlp/aimo-2-2025.md) - 包含 Top 12+ 前排方案技术总结
© Galaxy-Dawn, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 19 other files (references) in skills/kaggle-learner of Galaxy-Dawn/claude-scholar.
- SKILL.md
- references/knowledge/.archive/cv.md
- references/knowledge/.archive/multimodal.md
- references/knowledge/.archive/nlp.md
- references/knowledge/.archive/tabular.md
- references/knowledge/.archive/time-series.md
- references/knowledge/nlp/aimo-2-2025.md
- references/knowledge/nlp/arc-prize-2025.md
- references/knowledge/nlp/eedi-2024.md
- references/knowledge/nlp/konwinski-prize-2025-6th-place-study.md
- references/knowledge/nlp/konwinski-prize-2025-comparison.md
- references/knowledge/nlp/konwinski-prize-2025.md
- references/knowledge/nlp/map-2024.md
- references/knowledge/tabular/amp-parkinsons-2021.md
- references/knowledge/time-series/birdclef-2023.md
- … and 5 more
Open the folder on GitHubat commit 9037873
Used in 1 other repository
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in Galaxy-Dawn/claude-scholar, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Kaggle Learner next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Kaggle Learner this skillGalaxy-Dawn/claude-scholar | 5.7k | 1 repos | ~940 | Automated safety check: Pass | MIT | |
| Automl SkillLeoYeAI/openclaw-master-skills | 2.2k | — | ~3.6k | Automated safety check: Pass | MIT | |
| Data Science For IntelligenceHack23/cia | 239 | — | ~7.4k | Automated safety check: Pass | Apache-2.0 | |
| TimesFM Forecastinggoogle-research/timesfm | 34k | — | ~4.7k | Automated safety check: Pass | Apache-2.0 | |
| StatsmodelszLanqing/codex-claude-academic-skills | 4.7k | 15 repos | ~4.9k | Automated safety check: Pass | BSD-3-Clause | |
| Timesfm ForecastingzLanqing/codex-claude-academic-skills | 4.7k | 3 repos | ~7.5k | Automated safety check: Notes | Apache-2.0 |
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Questions about Kaggle Learner
What does Kaggle Learner do?
This skill should be used when the user asks to "learn from Kaggle", "study Kaggle solutions", "analyze Kaggle competitions", or mentions Kaggle competition URLs. Kaggle Learner is an agent skill from Galaxy-Dawn/claude-scholar. This skill should be used when the user asks to "learn from Kaggle", "study Kaggle solutions", "analyze Kaggle competitions", or mentions Kaggle competition URLs.
When should I use Kaggle Learner?
Kaggle Learner fits situations like: asks to learn from Kaggle; study Kaggle solutions; analyze Kaggle competitions; mentions Kaggle competition URLs.
How do I install Kaggle Learner in Claude Code?
Run `npx skills add Galaxy-Dawn/claude-scholar --skill kaggle-learner -a claude-code`. Or copy the skill folder (skills/kaggle-learner in Galaxy-Dawn/claude-scholar) into .claude/skills/kaggle-learner in your project. Claude Code loads it when a task matches its description.
How do I install Kaggle Learner in Codex?
Run `npx skills add Galaxy-Dawn/claude-scholar --skill kaggle-learner -a codex`. Or copy the skill folder (skills/kaggle-learner in Galaxy-Dawn/claude-scholar) into .agents/skills/kaggle-learner in your project. Codex loads it when a task matches its description.
Can I use Kaggle Learner in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Galaxy-Dawn/claude-scholar --skill kaggle-learner -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/kaggle-learner, .gemini/skills/kaggle-learner, .github/skills/kaggle-learner and .opencode/skills/kaggle-learner in your project.
What does Kaggle Learner need to run?
SKILL.md names no scripts, command-line tools or credentials: Kaggle Learner is instructions for the agent only.
Does Kaggle Learner access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Kaggle Learner safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Kaggle Learner use?
Kaggle Learner is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Kaggle Learner use?
About 940 tokens (SKILL.md is roughly 3.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 284k tokens, read only when the agent opens those files.
What are the alternatives to Kaggle Learner?
Skills that share tags, products or a category with Kaggle Learner: Automl Skill (LeoYeAI/openclaw-master-skills, 2.2k stars), Data Science For Intelligence (Hack23/cia, 239 stars), TimesFM Forecasting (google-research/timesfm, 34k stars) and Statsmodels (zLanqing/codex-claude-academic-skills, 4.7k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Kaggle Learner?
Galaxy-Dawn (a GitHub user) maintains it in Galaxy-Dawn/claude-scholar, which has 5,717 GitHub stars. The repository holds 34 skills in this directory. The repository was last updated on September 23, 2026.
Source: Galaxy-Dawn/claude-scholar on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.