Q-EDA Exploratory Analysis
TyrealQ/q-skills
Runs exploratory data analysis on tabular data after you confirm each column's measurement level, then writes CSV tables and a narrative summary.
Writes statistical analysis code for experimental data, runs it through a four-round review, and reports effect sizes, p-values and confidence intervals.
Install Statistical Data Analysis
$ npx skills add lingzhi227/agent-research-skills --skill data-analysis -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install lingzhi227/agent-research-skills data-analysis --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/lingzhi227/agent-research-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/data-analysis .claude/skills/data-analysis && 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 "data-analysis" agent skill from https://github.com/lingzhi227/agent-research-skills/tree/main/skills/data-analysis into .claude/skills/data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-analysis", 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/lingzhi227/agent-research-skills/tree/main/skills/data-analysisType 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 lingzhi227/agent-research-skills --skill data-analysis -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install lingzhi227/agent-research-skills data-analysis --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/lingzhi227/agent-research-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/data-analysis .agents/skills/data-analysis && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "data-analysis" agent skill from https://github.com/lingzhi227/agent-research-skills/tree/main/skills/data-analysis into .agents/skills/data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-analysis", 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 lingzhi227/agent-research-skills --skill data-analysis -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install lingzhi227/agent-research-skills data-analysis --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/lingzhi227/agent-research-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/data-analysis .cursor/skills/data-analysis && 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 "data-analysis" agent skill from https://github.com/lingzhi227/agent-research-skills/tree/main/skills/data-analysis into .cursor/skills/data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-analysis", 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/lingzhi227/agent-research-skills.git --path skills/data-analysis--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 lingzhi227/agent-research-skills --skill data-analysis -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install lingzhi227/agent-research-skills data-analysis --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/lingzhi227/agent-research-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/data-analysis .gemini/skills/data-analysis && 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 "data-analysis" agent skill from https://github.com/lingzhi227/agent-research-skills/tree/main/skills/data-analysis into .gemini/skills/data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-analysis", 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 lingzhi227/agent-research-skills data-analysisInstalls 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 lingzhi227/agent-research-skills --skill data-analysis -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/lingzhi227/agent-research-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/data-analysis .github/skills/data-analysis && 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 "data-analysis" agent skill from https://github.com/lingzhi227/agent-research-skills/tree/main/skills/data-analysis into .github/skills/data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-analysis", 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 lingzhi227/agent-research-skills --skill data-analysis -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install lingzhi227/agent-research-skills data-analysis --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/lingzhi227/agent-research-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/data-analysis .opencode/skills/data-analysis && 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 "data-analysis" agent skill from https://github.com/lingzhi227/agent-research-skills/tree/main/skills/data-analysis into .opencode/skills/data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-analysis", 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
data-analysis- GitHub stars
- 384
- Token cost
- ~886 tokens
- SKILL.md length
- 299 words
- Files
- 4 (incl. scripts, references)
- Skills in repo
- 31
- Repo updated
- First seen
- Licence
- None found
At a glance
Writes statistical analysis code for experimental data, runs it through a four-round review, and reports effect sizes, p-values and confidence intervals.
- Works in 3 steps: Generate Analysis Code → 4-Round Code Review → Produce Results
- Analyzing experiment results for a research paper
- SKILL.md covers Input, References, Scripts and Workflow, plus 4 more sections
- Runs Python scripts from its folder; calls python
What it does
You give it a data source (CSV, JSON, pickle or experiment logs) and a research goal or hypothesis. The agent writes analysis code in a fixed section order, from imports and data loading through dataset preparation, descriptive statistics, preprocessing, the statistical tests and extra results, using pandas, numpy, scipy, statsmodels and sklearn.
That code goes through four review rounds: code flaws, data handling, per-table checks and cross-table consistency. Two bundled Python scripts help. stat_summary.py detects data types, recommends and runs comparisons and reports effect sizes with significance stars, and needs numpy and scipy. format_pvalue.py formats p-values as stars, LaTeX or plain text using only the standard library. A table maps data types to tests such as the t-test, Mann-Whitney U, Wilcoxon, ANOVA and Kruskal-Wallis.
Reported results must carry an uncertainty measure such as a confidence interval, standard deviation or p-value, the chosen tests have to suit the data type, and every number has to come from the actual data rather than being made up.
When your agent uses it
- Analyzing experiment results for a research paper
- Choosing the right statistical test for two or more groups
- Formatting p-values as stars or LaTeX for a results table
- Reviewing analysis code for statistical or data-handling mistakes
Example prompts
- “Compare accuracy across the methods in results.csv and report effect sizes with significance.”
- “Write the analysis script for survey.json to test whether the treatment group scored higher.”
- “Format the p-values 0.001, 0.05 and 0.23 as LaTeX.”
Requirements
- Python with numpy and scipy for stat_summary.py
- pandas, statsmodels and scikit-learn for the generated analysis code
Workflow steps
3 steps, taken from the step headings in SKILL.md.
- Generate Analysis Code
- 4-Round Code Review
- Produce Results
What it can do on your machine
Read from SKILL.md and the folder at commit 9e6c085. 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 2 files in scripts/ (Python), 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
Statistical Data Analysis loads about 886 tokens when it runs, and up to ~1.9k if it reads all its reference files. Until then it costs about 65 tokens; SKILL.md has 299 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
Without a licence we can't republish the file, so here is its outline and opening line. It has 299 words (~886 tokens).
“Generate rigorous statistical analysis code with multi-round review.”
- name
- data-analysis
- argument-hint
- data-source
Files
SKILL.md and 3 other files (scripts, references) in skills/data-analysis of lingzhi227/agent-research-skills.
- SKILL.md
- references/review-prompts.md
- scripts/format_pvalue.py
- scripts/stat_summary.py
Open the folder on GitHubat commit 9e6c085
Compare with similar skills
Statistical Data Analysis 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 Data Analysis this skilllingzhi227/agent-research-skills | 384 | — | ~886 | Automated safety check: Pass | None | |
| Q-EDA Exploratory AnalysisTyrealQ/q-skills | 108 | — | ~1.1k | Automated safety check: Pass | MIT | |
| Tooluniverse Epigenomicswu-yc/LabClaw | 1.1k | 2 repos | ~14k | Automated safety check: Pass | None | |
| PyMC Bayesian Modelingdavila7/claude-code-templates | 32k | 12 repos | ~3.9k | Automated safety check: Pass | MIT | |
| Senior Data ScientistRaidriar7170/hermes-skilleval | 125 | 6 repos | ~1.4k | Automated safety check: Pass | MIT | |
| Python Executorcortega26/chile-hub | 113 | 2 repos | ~1.5k | Automated safety check: Pass | MIT |
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Related
Works with
Categories
Questions about Statistical Data Analysis
What does Statistical Data Analysis do?
Writes statistical analysis code for experimental data, runs it through a four-round review, and reports effect sizes, p-values and confidence intervals. You give it a data source (CSV, JSON, pickle or experiment logs) and a research goal or hypothesis. The agent writes analysis code in a fixed section order, from imports and data loading through dataset preparation, descriptive statistics, preprocessing, the statistical tests and extra results, using pandas, numpy, scipy, statsmodels and sklearn.
When should I use Statistical Data Analysis?
Statistical Data Analysis fits situations like: analyzing experiment results for a research paper; choosing the right statistical test for two or more groups; formatting p-values as stars or LaTeX for a results table; reviewing analysis code for statistical or data-handling mistakes.
How do I install Statistical Data Analysis in Claude Code?
Run `npx skills add lingzhi227/agent-research-skills --skill data-analysis -a claude-code`. Or copy the skill folder (skills/data-analysis in lingzhi227/agent-research-skills) into .claude/skills/data-analysis in your project. Claude Code loads it when a task matches its description.
How do I install Statistical Data Analysis in Codex?
Run `npx skills add lingzhi227/agent-research-skills --skill data-analysis -a codex`. Or copy the skill folder (skills/data-analysis in lingzhi227/agent-research-skills) into .agents/skills/data-analysis in your project. Codex loads it when a task matches its description.
Can I use Statistical Data Analysis 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 lingzhi227/agent-research-skills --skill data-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/data-analysis, .gemini/skills/data-analysis, .github/skills/data-analysis and .opencode/skills/data-analysis in your project.
What does Statistical Data Analysis need to run?
Going by SKILL.md and its folder, Statistical Data Analysis needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python with numpy and scipy for stat_summary.py; pandas, statsmodels and scikit-learn for the generated analysis code.
Does Statistical Data Analysis 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 Data Analysis 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 Statistical Data Analysis use?
No licence was found for Statistical Data Analysis or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.
How many tokens does Statistical Data Analysis use?
About 886 tokens (SKILL.md is roughly 3.5k 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 1k tokens, read only when the agent opens those files.
What are the alternatives to Statistical Data Analysis?
Skills that share tags, products or a category with Statistical Data Analysis: Q-EDA Exploratory Analysis (TyrealQ/q-skills, 108 stars), Tooluniverse Epigenomics (wu-yc/LabClaw, 1.1k stars), PyMC Bayesian Modeling (davila7/claude-code-templates, 32k stars) and Senior Data Scientist (Raidriar7170/hermes-skilleval, 125 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Statistical Data Analysis?
lingzhi227 (a GitHub user) maintains it in lingzhi227/agent-research-skills, which has 384 GitHub stars. The repository holds 31 skills in this directory. The repository was last updated on February 27, 2026.
Source: lingzhi227/agent-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.