Splitting Datasets
jeremylongshore/tons-of-skills-marketplace
Process split datasets into training, validation, and testing sets for ML model development.
Parameterized Python empirical-analysis and machine-learning workflow for applied economics, public health epidemiology, supervised ML, and ML causal inference.
Install Empirical Analysis Skill Python
$ npx skills add Drchronx/ai-agent-research-starter-kit --skill empirical-analysis-skill-python -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Drchronx/ai-agent-research-starter-kit empirical-analysis-skill-python --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/Drchronx/ai-agent-research-starter-kit.git skills-src && mkdir -p .claude/skills && cp -r skills-src/'综合学术部署包/04_数据采集整合与实证Skills/empirical-analysis-skill-python' .claude/skills/empirical-analysis-skill-python && 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 "empirical-analysis-skill-python" agent skill from https://github.com/Drchronx/ai-agent-research-starter-kit/tree/main/%E7%BB%BC%E5%90%88%E5%AD%A6%E6%9C%AF%E9%83%A8%E7%BD%B2%E5%8C%85/04_%E6%95%B0%E6%8D%AE%E9%87%87%E9%9B%86%E6%95%B4%E5%90%88%E4%B8%8E%E5%AE%9E%E8%AF%81Skills/empirical-analysis-skill-python into .claude/skills/empirical-analysis-skill-python/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "empirical-analysis-skill-python", 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/Drchronx/ai-agent-research-starter-kit/tree/main/%E7%BB%BC%E5%90%88%E5%AD%A6%E6%9C%AF%E9%83%A8%E7%BD%B2%E5%8C%85/04_%E6%95%B0%E6%8D%AE%E9%87%87%E9%9B%86%E6%95%B4%E5%90%88%E4%B8%8E%E5%AE%9E%E8%AF%81Skills/empirical-analysis-skill-pythonType 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 Drchronx/ai-agent-research-starter-kit --skill empirical-analysis-skill-python -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Drchronx/ai-agent-research-starter-kit empirical-analysis-skill-python --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Drchronx/ai-agent-research-starter-kit.git skills-src && mkdir -p .agents/skills && cp -r skills-src/'综合学术部署包/04_数据采集整合与实证Skills/empirical-analysis-skill-python' .agents/skills/empirical-analysis-skill-python && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "empirical-analysis-skill-python" agent skill from https://github.com/Drchronx/ai-agent-research-starter-kit/tree/main/%E7%BB%BC%E5%90%88%E5%AD%A6%E6%9C%AF%E9%83%A8%E7%BD%B2%E5%8C%85/04_%E6%95%B0%E6%8D%AE%E9%87%87%E9%9B%86%E6%95%B4%E5%90%88%E4%B8%8E%E5%AE%9E%E8%AF%81Skills/empirical-analysis-skill-python into .agents/skills/empirical-analysis-skill-python/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "empirical-analysis-skill-python", 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 Drchronx/ai-agent-research-starter-kit --skill empirical-analysis-skill-python -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Drchronx/ai-agent-research-starter-kit empirical-analysis-skill-python --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Drchronx/ai-agent-research-starter-kit.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/'综合学术部署包/04_数据采集整合与实证Skills/empirical-analysis-skill-python' .cursor/skills/empirical-analysis-skill-python && 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 "empirical-analysis-skill-python" agent skill from https://github.com/Drchronx/ai-agent-research-starter-kit/tree/main/%E7%BB%BC%E5%90%88%E5%AD%A6%E6%9C%AF%E9%83%A8%E7%BD%B2%E5%8C%85/04_%E6%95%B0%E6%8D%AE%E9%87%87%E9%9B%86%E6%95%B4%E5%90%88%E4%B8%8E%E5%AE%9E%E8%AF%81Skills/empirical-analysis-skill-python into .cursor/skills/empirical-analysis-skill-python/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "empirical-analysis-skill-python", 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/Drchronx/ai-agent-research-starter-kit.git --path '综合学术部署包/04_数据采集整合与实证Skills/empirical-analysis-skill-python'--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 Drchronx/ai-agent-research-starter-kit --skill empirical-analysis-skill-python -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Drchronx/ai-agent-research-starter-kit empirical-analysis-skill-python --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Drchronx/ai-agent-research-starter-kit.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/'综合学术部署包/04_数据采集整合与实证Skills/empirical-analysis-skill-python' .gemini/skills/empirical-analysis-skill-python && 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 "empirical-analysis-skill-python" agent skill from https://github.com/Drchronx/ai-agent-research-starter-kit/tree/main/%E7%BB%BC%E5%90%88%E5%AD%A6%E6%9C%AF%E9%83%A8%E7%BD%B2%E5%8C%85/04_%E6%95%B0%E6%8D%AE%E9%87%87%E9%9B%86%E6%95%B4%E5%90%88%E4%B8%8E%E5%AE%9E%E8%AF%81Skills/empirical-analysis-skill-python into .gemini/skills/empirical-analysis-skill-python/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "empirical-analysis-skill-python", 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 Drchronx/ai-agent-research-starter-kit empirical-analysis-skill-pythonInstalls 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 Drchronx/ai-agent-research-starter-kit --skill empirical-analysis-skill-python -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Drchronx/ai-agent-research-starter-kit.git skills-src && mkdir -p .github/skills && cp -r skills-src/'综合学术部署包/04_数据采集整合与实证Skills/empirical-analysis-skill-python' .github/skills/empirical-analysis-skill-python && 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 "empirical-analysis-skill-python" agent skill from https://github.com/Drchronx/ai-agent-research-starter-kit/tree/main/%E7%BB%BC%E5%90%88%E5%AD%A6%E6%9C%AF%E9%83%A8%E7%BD%B2%E5%8C%85/04_%E6%95%B0%E6%8D%AE%E9%87%87%E9%9B%86%E6%95%B4%E5%90%88%E4%B8%8E%E5%AE%9E%E8%AF%81Skills/empirical-analysis-skill-python into .github/skills/empirical-analysis-skill-python/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "empirical-analysis-skill-python", 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 Drchronx/ai-agent-research-starter-kit --skill empirical-analysis-skill-python -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Drchronx/ai-agent-research-starter-kit empirical-analysis-skill-python --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Drchronx/ai-agent-research-starter-kit.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/'综合学术部署包/04_数据采集整合与实证Skills/empirical-analysis-skill-python' .opencode/skills/empirical-analysis-skill-python && 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 "empirical-analysis-skill-python" agent skill from https://github.com/Drchronx/ai-agent-research-starter-kit/tree/main/%E7%BB%BC%E5%90%88%E5%AD%A6%E6%9C%AF%E9%83%A8%E7%BD%B2%E5%8C%85/04_%E6%95%B0%E6%8D%AE%E9%87%87%E9%9B%86%E6%95%B4%E5%90%88%E4%B8%8E%E5%AE%9E%E8%AF%81Skills/empirical-analysis-skill-python into .opencode/skills/empirical-analysis-skill-python/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "empirical-analysis-skill-python", 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
empirical-analysis-skill-python- GitHub stars
- 135
- Token cost
- ~3k tokens
- SKILL.md length
- 993 words
- Files
- 37 (incl. scripts, references)
- Skills in repo
- 36
- Repo updated
- First seen
- Licence
- Custom licence
At a glance
Parameterized Python empirical-analysis and machine-learning workflow for applied economics, public health epidemiology, supervised ML, and ML causal inference.
- Works in 8 steps: Start with scripts/clean_data.py on the… → Use scripts/transform_data.py to create… → Use scripts/describe_data.py to generate… → …
- The user asks for data cleaning
- SKILL.md covers Hard Rules, Script Layout, Default Workflow and Domain Modes, plus 4 more sections
- Runs Python scripts from its folder; calls python
What it does
Empirical Analysis Skill Python is an agent skill from Drchronx/ai-agent-research-starter-kit. Parameterized Python empirical-analysis and machine-learning workflow for applied economics, public health epidemiology, supervised ML, and ML causal inference. Use when the user asks for data cleaning, feature engineering, train/test/validation splits, feature matrix X and target y, Table 1, diagnostic tests, OLS/panel/IV-style formulas, LinearRegression, Ridge, Lasso, ElasticNet, decision trees, random forests, GBDT, regression/classification metrics, DID/event-study formulas, DML/double machine learning with…
Its SKILL.md is about 3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 38 other files, including scripts and reference files (for example `README.md`, `references/01-data-cleaning.md` and `references/02-data-transformation.md`).
It sits in Data & Analytics, covering Machine learning, Econometrics and empirical research and Data cleaning. It works with Python. The repository describes itself as: AI Agent 科研全流程教学包，能教学生从零部署 Codex、Claude Code、OpenClaw、Hermes 等 Agent，学会使用 Skills、飞书、AMiner、AI4Scholar、Zotero、Obsidian…
When your agent uses it
- The user asks for data cleaning
- Feature engineering
- Train/test/validation splits
- Feature matrix X and target y
Example prompts
- “/empirical-analysis-skill-python”
Requirements
- Python 3
Workflow steps
8 steps, taken from the first numbered list in SKILL.md.
- Start with scripts/clean_data.py on the raw data. Always pass key variables and dedupe columns when known.
- Use scripts/transform_data.py to create analysis variables rather than doing inline dataframe mutations.
- Use scripts/describe_data.py to generate Table 1 and the main exploratory figures.
- Use scripts/run_diagnostics.py on the baseline formula before reporting results.
- Use scripts/run_model.py for the main results. Prefer progressive model columns with --progressive or explicit semicolon-separated…
- Use scripts/run_robustness.py for alternative controls, clusters, subsamples, and placebo checks.
- Use scripts/run_further_analysis.py for mechanism, heterogeneity, and mediation.
- Use scripts/render_manifest.py to produce the final manifest of tables and figures.
What it can do on your machine
Read from SKILL.md and the folder at commit aab1133. 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
Ships 7 files in scripts/ (Python, from the files we listed), which the agent can run.
Shell commands in SKILL.md call:
python
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
Empirical Analysis Skill Python loads about 3k tokens when it runs, and up to ~12k if it reads all its reference files. Until then it costs about 211 tokens; SKILL.md has 993 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); the scripts in this folder are not scanned.
SKILL.md
Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 993 words (~2,981 tokens).
“This skill runs a full empirical workflow through fixed, decoupled Python scripts. The agent may choose variables, formulas, modes, and arguments, but must not invent Python snippets inside markdown responses or reference files.”
- name
- empirical-analysis-skill-python
- triggers
- full empirical analysis in Python, classical econometrics pipeline, applied economics paper replication, end-to-end empirical workflow, data cleaning…
Files
SKILL.md and 36 other files (scripts, references) in 综合学术部署包/04_数据采集整合与实证Skills/empirical-analysis-skill-python of Drchronx/ai-agent-research-starter-kit.
- SKILL.md
- README.md
- references/01-data-cleaning.md
- references/02-data-transformation.md
- references/03-descriptive-stats.md
- references/04-statistical-tests.md
- references/05-modeling.md
- references/06-robustness.md
- references/07-further-analysis.md
- references/08-tables-plots.md
- references/09-machine-learning.md
- references/method-index.md
- scripts/clean_data.py
- scripts/common.py
- scripts/describe_data.py
- scripts/empirical_cli.py
- scripts/model_utils.py
- scripts/plot_factory.py
- scripts/prepare_ml_data.py
- … and 18 more
Open the folder on GitHubat commit aab1133
Compare with similar skills
Empirical Analysis Skill Python 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 |
|---|---|---|---|---|---|---|
| Empirical Analysis Skill Python this skillDrchronx/ai-agent-research-starter-kit | 135 | — | ~3k | Automated safety check: Pass | Custom licence | |
| Splitting Datasetsjeremylongshore/tons-of-skills-marketplace | 2.8k | 1 repos | ~836 | Automated safety check: Pass | MIT | |
| Senior Data Scientistalirezarezvani/claude-skills | 28k | 2 repos | ~2.3k | Automated safety check: Pass | MIT | |
| Sap Hana Cloud Data Intelligencesecondsky/sap-skills | 462 | — | ~3.2k | Automated safety check: Pass | GPL-3.0 | |
| Senior Data Scientistborghei/Claude-Skills | 881 | — | ~1.7k | Automated safety check: Pass | MIT | |
| Data Cleaningbrycewang-stanford/Auto-Empirical-Research-Skills | 4.5k | — | ~2.9k | Automated safety check: Pass | Custom licence |
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Related
Works with
Categories
Questions about Empirical Analysis Skill Python
What does Empirical Analysis Skill Python do?
Parameterized Python empirical-analysis and machine-learning workflow for applied economics, public health epidemiology, supervised ML, and ML causal inference. Empirical Analysis Skill Python is an agent skill from Drchronx/ai-agent-research-starter-kit. Parameterized Python empirical-analysis and machine-learning workflow for applied economics, public health epidemiology, supervised ML, and ML causal inference.
When should I use Empirical Analysis Skill Python?
Empirical Analysis Skill Python fits situations like: the user asks for data cleaning; feature engineering; train/test/validation splits; feature matrix X and target y.
How do I install Empirical Analysis Skill Python in Claude Code?
Run `npx skills add Drchronx/ai-agent-research-starter-kit --skill empirical-analysis-skill-python -a claude-code`. Or copy the skill folder (综合学术部署包/04_数据采集整合与实证Skills/empirical-analysis-skill-python in Drchronx/ai-agent-research-starter-kit) into .claude/skills/empirical-analysis-skill-python in your project. Claude Code loads it when a task matches its description.
How do I install Empirical Analysis Skill Python in Codex?
Run `npx skills add Drchronx/ai-agent-research-starter-kit --skill empirical-analysis-skill-python -a codex`. Or copy the skill folder (综合学术部署包/04_数据采集整合与实证Skills/empirical-analysis-skill-python in Drchronx/ai-agent-research-starter-kit) into .agents/skills/empirical-analysis-skill-python in your project. Codex loads it when a task matches its description.
Can I use Empirical Analysis Skill Python 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 Drchronx/ai-agent-research-starter-kit --skill empirical-analysis-skill-python -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/empirical-analysis-skill-python, .gemini/skills/empirical-analysis-skill-python, .github/skills/empirical-analysis-skill-python and .opencode/skills/empirical-analysis-skill-python in your project.
What does Empirical Analysis Skill Python need to run?
Going by SKILL.md and its folder, Empirical Analysis Skill Python needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.
Does Empirical Analysis Skill Python 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 Empirical Analysis Skill Python 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Empirical Analysis Skill Python use?
Empirical Analysis Skill Python has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.
How many tokens does Empirical Analysis Skill Python use?
About 3k tokens (SKILL.md is roughly 12k 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 8.7k tokens, read only when the agent opens those files.
What are the alternatives to Empirical Analysis Skill Python?
Skills that share tags, products or a category with Empirical Analysis Skill Python: Splitting Datasets (jeremylongshore/tons-of-skills-marketplace, 2.8k stars), Senior Data Scientist (alirezarezvani/claude-skills, 28k stars), Sap Hana Cloud Data Intelligence (secondsky/sap-skills, 462 stars) and Senior Data Scientist (borghei/Claude-Skills, 881 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Empirical Analysis Skill Python?
Drchronx (a GitHub user) maintains it in Drchronx/ai-agent-research-starter-kit, which has 135 GitHub stars. The repository holds 36 skills in this directory. The repository was last updated on May 19, 2026.
Source: Drchronx/ai-agent-research-starter-kit on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.