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paper-analysis

Execute paper-outline-driven statistical analysis and modeling to produce chart-ready JSON/CSV datasets.

1|Updated May 14, 2026
Search Tags:#data modeling#paper-analysis#statistical inference#robustness testing#JSON reporting#Python automation#simulation data
One-click install
npx skills add https://github.com/lix965996-art/MMM --skill paper-analysis-lix965996-art
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: paper-analysis
Source: https://github.com/lix965996-art/MMM/tree/main/resources/app/skills/paper-analysis
Command: npx skills add https://github.com/lix965996-art/MMM --skill paper-analysis-lix965996-art

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill turns a paper outline into structured, reproducible data analysis outputs, so you can validate methods and produce chart-ready JSON results instead of manually stitching statistics together.

Core Features & Use Cases

  • Paper-outline-driven analysis: Extracts research questions, hypotheses, variables, and an expected figure checklist from PAPER_PLAN.md (and optionally TOPIC_PLAN.md), then executes the corresponding statistical modeling pipeline.
  • Real-data-first or high-quality simulation: Uses real files from user_data/ or data/ when present; otherwise generates simulation data that matches typical domain ranges, patterns, and minimum sample-size quality rules for common empirical modeling scenarios.
  • Reproducible result artifacts for plotting: Produces machine-readable outputs in figures/*.json (e.g., descriptive_stats.json, analysis_N_results.json, robustness_results.json) and prepares RESULTS.md as the summary interface for the downstream paper-figure stage.

Quick Start

Ask the assistant to run the paper-analysis workflow using the provided PAPER_PLAN.md and generate figures/descriptive_stats.json plus the analysis_N_results.json outputs.

Frequently Asked Questions about paper-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate reproducible statistical analysis outputs from a paper outline?▼

You can use real datasets from user_data/ or data/ directories; if absent, the Skill generates quality-controlled simulation data using deterministic seeds to ensure reproducible statistical inference results.

How do I produce chart-ready JSON data for research figures?▼

You produce chart-ready JSON data by running the analysis pipeline, which outputs machine-readable files like descriptive_stats.json and analysis_N_results.json into a figures directory for downstream paper-figure charting.

Do I need to provide my own data files to run statistical modeling?▼

Robustness testing is supported through the generation of robustness_results.json outputs, applying rigorous data preparation checks and statistical inference steps specified in your PAPER_PLAN.md requirements.

Can I automate regression and robustness testing for empirical modeling?▼

You can automate regression, classical statistics, and ML evaluation steps through Python automation that computes metrics from actual model results rather than hard-coded values, ensuring deterministic execution and reproducible seeds.

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