Generate statistical analysis code with 4-round review. Select appropriate statistical tests, interpret results, and produce analysis reports with p-values, effect sizes, and confidence intervals. Use when analyzing experimental data for a paper.
Quickly install data-analysis AI skill to your development environment via command line
Source: lingzhi227/agent-research-skills.
Detects data types, recommends tests, runs comparisons, outputs effect sizes and significance stars. Requires numpy, scipy.
Formats p-values with stars, LaTeX notation, or plain text. Stdlib-only.
Step 1: Generate Analysis Code Structure the code with these sections:
Generate statistical analysis code with 4-round review. Select appropriate statistical tests, interpret results, and produce analysis reports with p-values, effect sizes, and confidence intervals. Use when analyzing experimental data for a paper. Source: lingzhi227/agent-research-skills.
Stable fields and commands for AI/search citations.
npx skills add https://github.com/lingzhi227/agent-research-skills --skill data-analysisGenerate statistical analysis code with 4-round review. Select appropriate statistical tests, interpret results, and produce analysis reports with p-values, effect sizes, and confidence intervals. Use when analyzing experimental data for a paper. Source: lingzhi227/agent-research-skills.
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/lingzhi227/agent-research-skills --skill data-analysis Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code, Cursor, or OpenClaw
https://github.com/lingzhi227/agent-research-skills