Stata
dylantmoore/stata-skill
Comprehensive Stata reference for writing correct .do files, data management, econometrics, causal inference, graphics, Mata programming, and 20 community packages (reghdfe, estout, did, rdrobust…
Agent skill
Statistical Modeling
by brycewang-stanford in brycewang-stanford/Auto-Empirical-Research-Skills
A skill your agent uses when estimating a statistical or econometric model, running a regression, specifying an identification strategy, testing a hypothesis, or fitting any model to empirical data.
Install Statistical Modeling
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill statistical-modeling -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills statistical-modeling --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/brycewang-stanford/Auto-Empirical-Research-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/60-regisely-superpapers/skills/statistical-modeling .claude/skills/statistical-modeling && 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 "statistical-modeling" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/60-regisely-superpapers/skills/statistical-modeling into .claude/skills/statistical-modeling/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "statistical-modeling", 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/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/60-regisely-superpapers/skills/statistical-modelingType 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 brycewang-stanford/Auto-Empirical-Research-Skills --skill statistical-modeling -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills statistical-modeling --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/60-regisely-superpapers/skills/statistical-modeling .agents/skills/statistical-modeling && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "statistical-modeling" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/60-regisely-superpapers/skills/statistical-modeling into .agents/skills/statistical-modeling/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "statistical-modeling", 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 brycewang-stanford/Auto-Empirical-Research-Skills --skill statistical-modeling -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills statistical-modeling --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/60-regisely-superpapers/skills/statistical-modeling .cursor/skills/statistical-modeling && 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 "statistical-modeling" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/60-regisely-superpapers/skills/statistical-modeling into .cursor/skills/statistical-modeling/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "statistical-modeling", 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/brycewang-stanford/Auto-Empirical-Research-Skills.git --path skills/60-regisely-superpapers/skills/statistical-modeling--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 brycewang-stanford/Auto-Empirical-Research-Skills --skill statistical-modeling -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills statistical-modeling --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/60-regisely-superpapers/skills/statistical-modeling .gemini/skills/statistical-modeling && 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 "statistical-modeling" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/60-regisely-superpapers/skills/statistical-modeling into .gemini/skills/statistical-modeling/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "statistical-modeling", 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 brycewang-stanford/Auto-Empirical-Research-Skills statistical-modelingInstalls 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 brycewang-stanford/Auto-Empirical-Research-Skills --skill statistical-modeling -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/60-regisely-superpapers/skills/statistical-modeling .github/skills/statistical-modeling && 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 "statistical-modeling" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/60-regisely-superpapers/skills/statistical-modeling into .github/skills/statistical-modeling/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "statistical-modeling", 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 brycewang-stanford/Auto-Empirical-Research-Skills --skill statistical-modeling -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills statistical-modeling --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/60-regisely-superpapers/skills/statistical-modeling .opencode/skills/statistical-modeling && 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 "statistical-modeling" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/60-regisely-superpapers/skills/statistical-modeling into .opencode/skills/statistical-modeling/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "statistical-modeling", 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
statistical-modeling- GitHub stars
- 4.5k
- Token cost
- ~1.9k tokens
- SKILL.md length
- 949 words
- Files
- 6 (incl. references)
- Skills in repo
- 364
- Repo updated
- First seen
- Licence
- Custom licence
At a glance
A skill your agent uses when estimating a statistical or econometric model, running a regression, specifying an identification strategy, testing a hypothesis, or fitting any model to empirical data.
- Works in 6 steps: Define the Estimand → Verify Assumptions Match the Data → Choose the Method → …
- Estimating a statistical
- SKILL.md covers Overview, When to Use, Mandatory Steps and Reference Files, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Statistical Modeling is an agent skill from brycewang-stanford/Auto-Empirical-Research-Skills. Use when estimating a statistical or econometric model, running a regression, specifying an identification strategy, testing a hypothesis, or fitting any model to empirical data. Guides the process (assumptions, estimation, reporting, diagnostics) without forcing a fixed method list.
Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including reference files (for example `references/causal-inference.md`, `references/cross-section.md` and `references/modeling-process.md`).
It sits in Research & Science, covering Econometrics and empirical research and Trading and backtesting. The repository describes itself as: 🔬 A curated collection of 23,000+ agent skills for empirical research across 8 social science disciplines. | 精选 23,000+ AI Agent 技能库，覆盖8大社会科学学科的实证研究。CoPaper.AI…
When your agent uses it
- Estimating a statistical
- Econometric model
- Running a regression
- Specifying an identification strategy
Example prompts
- “/statistical-modeling”
Workflow steps
6 steps, taken from the step headings in SKILL.md.
- Define the Estimand
- Verify Assumptions Match the Data
- Choose the Method
- Estimate
- Diagnose
- Report
What it can do on your machine
Read from SKILL.md and the folder at commit 9fa87d8. 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.
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
Statistical Modeling loads about 1.9k tokens when it runs, and up to ~9.7k if it reads all its reference files. Until then it costs about 76 tokens; SKILL.md has 949 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
Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 949 words (~1,857 tokens).
“This skill defines the process for statistical modeling in empirical research. It is method-agnostic and field-agnostic — the appropriate method for a research question comes from the data and the estimand, not from a fixed list. Reference files organized by…”
- name
- statistical-modeling
Files
SKILL.md and 5 other files (references) in skills/60-regisely-superpapers/skills/statistical-modeling of brycewang-stanford/Auto-Empirical-Research-Skills.
- SKILL.md
- references/causal-inference.md
- references/cross-section.md
- references/modeling-process.md
- references/panel.md
- references/time-series.md
Open the folder on GitHubat commit 9fa87d8
Compare with similar skills
Statistical Modeling 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 |
|---|---|---|---|---|---|---|
| Statistical Modeling this skillbrycewang-stanford/Auto-Empirical-Research-Skills | 4.5k | — | ~1.9k | Automated safety check: Pass | Custom licence | |
| Statadylantmoore/stata-skill | 291 | 1 repos | ~4.2k | Automated safety check: Pass | Custom licence | |
| Stata C Pluginsdylantmoore/stata-skill | 291 | 1 repos | ~5.8k | Automated safety check: Pass | Custom licence | |
| Example Datasetspymc-labs/CausalPy | 1.2k | — | ~587 | Automated safety check: Pass | Apache-2.0 | |
| Stata AuditSepineTam/mcp-for-stata | 264 | — | ~1.2k | Automated safety check: Pass | AGPL-3.0 | |
| Stata Skill Contributordylantmoore/stata-skill | 291 | 1 repos | ~2.4k | Automated safety check: Pass | Custom licence |
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Related
Categories
Questions about Statistical Modeling
What does Statistical Modeling do?
A skill your agent uses when estimating a statistical or econometric model, running a regression, specifying an identification strategy, testing a hypothesis, or fitting any model to empirical data. Statistical Modeling is an agent skill from brycewang-stanford/Auto-Empirical-Research-Skills. Use when estimating a statistical or econometric model, running a regression, specifying an identification strategy, testing a hypothesis, or fitting any model to empirical data.
When should I use Statistical Modeling?
Statistical Modeling fits situations like: estimating a statistical; econometric model; running a regression; specifying an identification strategy.
How do I install Statistical Modeling in Claude Code?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill statistical-modeling -a claude-code`. Or copy the skill folder (skills/60-regisely-superpapers/skills/statistical-modeling in brycewang-stanford/Auto-Empirical-Research-Skills) into .claude/skills/statistical-modeling in your project. Claude Code loads it when a task matches its description.
How do I install Statistical Modeling in Codex?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill statistical-modeling -a codex`. Or copy the skill folder (skills/60-regisely-superpapers/skills/statistical-modeling in brycewang-stanford/Auto-Empirical-Research-Skills) into .agents/skills/statistical-modeling in your project. Codex loads it when a task matches its description.
Can I use Statistical Modeling 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 brycewang-stanford/Auto-Empirical-Research-Skills --skill statistical-modeling -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/statistical-modeling, .gemini/skills/statistical-modeling, .github/skills/statistical-modeling and .opencode/skills/statistical-modeling in your project.
What does Statistical Modeling need to run?
SKILL.md names no scripts, command-line tools or credentials: Statistical Modeling is instructions for the agent only.
Does Statistical Modeling 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 Statistical Modeling 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 Statistical Modeling use?
Statistical Modeling 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 Statistical Modeling use?
About 1.9k tokens (SKILL.md is roughly 7.4k 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 7.9k tokens, read only when the agent opens those files.
What are the alternatives to Statistical Modeling?
Skills that share tags, products or a category with Statistical Modeling: Stata (dylantmoore/stata-skill, 291 stars), Stata C Plugins (dylantmoore/stata-skill, 291 stars), Example Datasets (pymc-labs/CausalPy, 1.2k stars) and Stata Audit (SepineTam/mcp-for-stata, 264 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Statistical Modeling?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Auto-Empirical-Research-Skills, which has 4,529 GitHub stars. The repository holds 364 skills in this directory. The repository was last updated on October 5, 2026.
Source: brycewang-stanford/Auto-Empirical-Research-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.