Statsmodels
zLanqing/codex-claude-academic-skills
Statistical models library for Python. An agent skill from zLanqing/codex-claude-academic-skills.
Statistical modeling: OLS/WLS/GLS, GLM (logit, probit, Poisson), time series (ARIMA, VAR), mixed effects, diagnostics.
Install Statsmodels
$ npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill statsmodels -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills statsmodels --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/17-DAAF-Contribution-Community-daaf/dot-claude/skills/statsmodels .claude/skills/statsmodels && 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 "statsmodels" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/17-DAAF-Contribution-Community-daaf/dot-claude/skills/statsmodels into .claude/skills/statsmodels/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "statsmodels", 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/17-DAAF-Contribution-Community-daaf/dot-claude/skills/statsmodelsType 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 statsmodels -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills statsmodels --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/17-DAAF-Contribution-Community-daaf/dot-claude/skills/statsmodels .agents/skills/statsmodels && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "statsmodels" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/17-DAAF-Contribution-Community-daaf/dot-claude/skills/statsmodels into .agents/skills/statsmodels/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "statsmodels", 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 statsmodels -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills statsmodels --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/17-DAAF-Contribution-Community-daaf/dot-claude/skills/statsmodels .cursor/skills/statsmodels && 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 "statsmodels" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/17-DAAF-Contribution-Community-daaf/dot-claude/skills/statsmodels into .cursor/skills/statsmodels/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "statsmodels", 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/17-DAAF-Contribution-Community-daaf/dot-claude/skills/statsmodels--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 statsmodels -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Auto-Empirical-Research-Skills statsmodels --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/17-DAAF-Contribution-Community-daaf/dot-claude/skills/statsmodels .gemini/skills/statsmodels && 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 "statsmodels" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/17-DAAF-Contribution-Community-daaf/dot-claude/skills/statsmodels into .gemini/skills/statsmodels/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "statsmodels", 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 statsmodelsInstalls 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 statsmodels -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/17-DAAF-Contribution-Community-daaf/dot-claude/skills/statsmodels .github/skills/statsmodels && 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 "statsmodels" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/17-DAAF-Contribution-Community-daaf/dot-claude/skills/statsmodels into .github/skills/statsmodels/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "statsmodels", 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 statsmodels -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 statsmodels --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/17-DAAF-Contribution-Community-daaf/dot-claude/skills/statsmodels .opencode/skills/statsmodels && 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 "statsmodels" agent skill from https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/tree/main/skills/17-DAAF-Contribution-Community-daaf/dot-claude/skills/statsmodels into .opencode/skills/statsmodels/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "statsmodels", 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
statsmodels- GitHub stars
- 4.5k
- Token cost
- ~3.4k tokens
- SKILL.md length
- 951 words
- Files
- 8 (incl. references)
- Skills in repo
- 369
- Repo updated
- First seen
- Licence
- Custom licence
At a glance
Statistical modeling: OLS/WLS/GLS, GLM (logit, probit, Poisson), time series (ARIMA, VAR), mixed effects, diagnostics.
- Works in 5 steps: New to statsmodels? Start with… → Need GLM or logit/probit? Read… → Time series analysis? Read quickstart.md… → …
- Regressions without fixed effects
- SKILL.md covers What is statsmodels?, How to Use This Skill, Related Skills and Quick Decision Trees, plus 4 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Statsmodels is an agent skill from brycewang-stanford/Auto-Empirical-Research-Skills. Statistical modeling: OLS/WLS/GLS, GLM (logit, probit, Poisson), time series (ARIMA, VAR), mixed effects, diagnostics. Formula API. Use for regressions without fixed effects, GLMs, or time series. For FE/DiD use pyfixest; panel/IV use linearmodels.
Its SKILL.md is about 3.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including reference files (for example `references/diagnostics.md`, `references/glm-discrete.md` and `references/gotchas.md`).
It sits in Data & Analytics, covering Forecasting and time series and Statistics. It works with statsmodels. 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
- Regressions without fixed effects
- Tasks that involve Forecasting and time series
- Tasks that involve Statistics
Example prompts
- “/statsmodels”
Requirements
- Python 3
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- New to statsmodels? Start with quickstart.md then linear-models.md
- Need GLM or logit/probit? Read quickstart.md then glm-discrete.md
- Time series analysis? Read quickstart.md then time-series.md
- Checking model assumptions? Read diagnostics.md
- Coming from R? Read quickstart.md (formula API mirrors R syntax)
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 (its code samples are 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
Statsmodels loads about 3.4k tokens when it runs, and up to ~36k if it reads all its reference files. Until then it costs about 65 tokens; SKILL.md has 951 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 951 words (~3,446 tokens).
“statsmodels general-purpose statistical modeling library for Python. Covers OLS/WLS/GLS, GLM (logit, probit, Poisson, negative binomial), discrete choice models, time series (ARIMA, SARIMAX, VAR), mixed effects (MixedLM), robust regression, hypothesis tests, and comprehensive diagnostics. Supports R-style formula API. Use when fitting…”
- name
- statsmodels
- metadata.audience
- research-coders
- metadata.domain
- python-library
- metadata.library-version
- 0.14.6
- metadata.skill-last-updated
- 2026-03-27
Files
SKILL.md and 7 other files (references) in skills/17-DAAF-Contribution-Community-daaf/dot-claude/skills/statsmodels of brycewang-stanford/Auto-Empirical-Research-Skills.
- SKILL.md
- references/diagnostics.md
- references/glm-discrete.md
- references/gotchas.md
- references/hypothesis-testing.md
- references/linear-models.md
- references/quickstart.md
- references/time-series.md
Open the folder on GitHubat commit 9fa87d8
Compare with similar skills
Statsmodels 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 |
|---|---|---|---|---|---|---|
| Statsmodels this skillbrycewang-stanford/Auto-Empirical-Research-Skills | 4.5k | — | ~3.4k | Automated safety check: Pass | Custom licence | |
| StatsmodelszLanqing/codex-claude-academic-skills | 4.6k | 16 repos | ~4.9k | Automated safety check: Pass | BSD-3-Clause | |
| Quant Statistical MethodsHKUDS/Vibe-Trading | 35k | — | ~4k | Automated safety check: Pass | MIT | |
| StatsmodelsK-Dense-AI/scientific-agent-skills | 48k | 1 repos | ~3.2k | Automated safety check: Notes | BSD-3-Clause | |
| Automl SkillLeoYeAI/openclaw-master-skills | 2.2k | — | ~3.6k | Automated safety check: Pass | MIT | |
| Statsmodels Statistical Modelingmajiayu000/claude-skill-registry | 666 | 2 repos | ~4.2k | Automated safety check: Pass | BSD-3-Clause |
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Related
Works with
Categories
Questions about Statsmodels
What does Statsmodels do?
Statistical modeling: OLS/WLS/GLS, GLM (logit, probit, Poisson), time series (ARIMA, VAR), mixed effects, diagnostics. Statsmodels is an agent skill from brycewang-stanford/Auto-Empirical-Research-Skills. Statistical modeling: OLS/WLS/GLS, GLM (logit, probit, Poisson), time series (ARIMA, VAR), mixed effects, diagnostics.
When should I use Statsmodels?
Statsmodels fits situations like: regressions without fixed effects; tasks that involve Forecasting and time series; tasks that involve Statistics.
How do I install Statsmodels in Claude Code?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill statsmodels -a claude-code`. Or copy the skill folder (skills/17-DAAF-Contribution-Community-daaf/dot-claude/skills/statsmodels in brycewang-stanford/Auto-Empirical-Research-Skills) into .claude/skills/statsmodels in your project. Claude Code loads it when a task matches its description.
How do I install Statsmodels in Codex?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill statsmodels -a codex`. Or copy the skill folder (skills/17-DAAF-Contribution-Community-daaf/dot-claude/skills/statsmodels in brycewang-stanford/Auto-Empirical-Research-Skills) into .agents/skills/statsmodels in your project. Codex loads it when a task matches its description.
Can I use Statsmodels 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 statsmodels -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/statsmodels, .gemini/skills/statsmodels, .github/skills/statsmodels and .opencode/skills/statsmodels in your project.
What does Statsmodels need to run?
SKILL.md names no scripts, command-line tools or credentials: Statsmodels is instructions for the agent only. Our summary lists: Python 3.
Does Statsmodels 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 Statsmodels 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 Statsmodels use?
Statsmodels 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 Statsmodels use?
About 3.4k tokens (SKILL.md is roughly 14k 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 32k tokens, read only when the agent opens those files.
What are the alternatives to Statsmodels?
Skills that share tags, products or a category with Statsmodels: Statsmodels (zLanqing/codex-claude-academic-skills, 4.6k stars), Quant Statistical Methods (HKUDS/Vibe-Trading, 35k stars), Statsmodels (K-Dense-AI/scientific-agent-skills, 48k stars) and Automl Skill (LeoYeAI/openclaw-master-skills, 2.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Statsmodels?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Auto-Empirical-Research-Skills, which has 4,517 GitHub stars. The repository holds 369 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.