data-analysis — community data-analysis, claude-econ-paper-template, community, ide skills, Claude Code, Cursor, Windsurf

v1.0.0
GitHub

About this Skill

Perfect for Statistical Analysis Agents needing advanced data analysis and visualization capabilities with Stata and R. Claude Code infrastructure template for empirical economics research papers

naj2r naj2r
[0]
[0]
Updated: 3/9/2026

Agent Capability Analysis

The data-analysis skill by naj2r is an open-source community AI agent skill for Claude Code and other IDE workflows, helping agents execute tasks with better context, repeatability, and domain-specific guidance.

Ideal Agent Persona

Perfect for Statistical Analysis Agents needing advanced data analysis and visualization capabilities with Stata and R.

Core Value

Empowers agents to perform end-to-end data analysis using Stata's areg and reghdfe commands, and R's fixest package, producing publication-ready output in .tex and .html formats with ggplot2 visualizations.

↓ Capabilities Granted for data-analysis

Automating data loading and inspection for empirical economics research papers
Generating summary statistics, distributions, and treatment/control comparisons with Stata and R
Producing publication-ready tables and figures using esttab and modelsummary libraries

! Prerequisites & Limits

  • Requires Stata or R installation and configuration
  • Limited to specific file formats (.dta, .csv, .tex, .html, .png, .pdf)
  • Dependent on relative paths to $RB/ directory
Labs Demo

Browser Sandbox Environment

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Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

data-analysis

Install data-analysis, an AI agent skill for AI agent workflows and automation. Works with Claude Code, Cursor, and Windsurf with one-command setup.

SKILL.md
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Data Analysis Workflow

Run an end-to-end data analysis: load, explore, analyze, and produce publication-ready output.

Input: $ARGUMENTS — a dataset path, analysis goal, or language preference.

Language Selection

  • If user says "stata" or "do-file" → write a .do file
  • If user says "R" or "Rscript" → write an .R file
  • If ambiguous → ask. Default to Stata for regressions, R for visualization.

Project Data

DatasetPathContents
Panel Adata_final/{{panel_A}}.dta{{description}}
Panel Bdata_final/{{panel_B}}.dta{{description}}
Panel Cdata_final/{{panel_C}}.dta{{description}}
Results CSVoutput/results/{{regression_results}}.csv{{description}}
Electionsdata_final/{{elections_panel}}.dta{{description}}

Workflow Phases

Phase 1: Setup

  • Follow conventions in .claude/rules/stata-r-conventions.md
  • Create script with proper header
  • Load data and inspect

Phase 2: Exploratory Analysis

  • Summary statistics, distributions, missingness
  • Treatment/control comparisons
  • Time trends

Phase 3: Main Analysis

  • Stata: areg or reghdfe with county+year FE, vce(cluster {{cluster_var}})
  • R: fixest::feols() with cluster = ~{{cluster_var}}
  • Start simple, progressively add controls
  • Report standardized effects (β/ȳ and β/σ_w)

Phase 4: Publication-Ready Output

  • Stata: esttab → .tex tables
  • R: modelsummary → .tex and .html tables
  • Figures: ggplot2 with explicit dimensions, export PDF+PNG

Phase 5: Verify

  • Run the code and check for errors
  • Cross-check against {{regression_results}}.csv if applicable
  • Save all outputs to output/

Important

  • New analysis → new numbered do-file (09+) or script in scripts/
  • Never modify 01–08 do-files without explicit permission
  • All paths relative to $RB/
  • Match existing specifications before extending

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is data-analysis?

Perfect for Statistical Analysis Agents needing advanced data analysis and visualization capabilities with Stata and R. Claude Code infrastructure template for empirical economics research papers

How do I install data-analysis?

Run the command: npx killer-skills add naj2r/claude-econ-paper-template/data-analysis. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for data-analysis?

Key use cases include: Automating data loading and inspection for empirical economics research papers, Generating summary statistics, distributions, and treatment/control comparisons with Stata and R, Producing publication-ready tables and figures using esttab and modelsummary libraries.

Which IDEs are compatible with data-analysis?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for data-analysis?

Requires Stata or R installation and configuration. Limited to specific file formats (.dta, .csv, .tex, .html, .png, .pdf). Dependent on relative paths to $RB/ directory.

↓ How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add naj2r/claude-econ-paper-template/data-analysis. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use data-analysis immediately in the current project.

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