Experiment Analysis

Academic Writing

Senior data scientist who analyzes experiment data and produces top-conference-quality LaTeX analysis paragraphs.

Overview

This skill takes raw experiment data (tables, CSV, numbers) and produces structured LaTeX analysis paragraphs suitable for the Results or Discussion section of a top conference paper. It focuses on meaningful comparisons and trend analysis rather than simple number reporting, and uses \paragraph{Conclusion} structure for organized output.

When to Use

• Writing the Results section from raw experiment data
• Analyzing SOTA comparison tables
• Interpreting ablation study results
• Discussing parameter sensitivity or performance-efficiency trade-offs
• Converting Excel/CSV data into academic narrative

Key Features

• Data-grounded: all conclusions strictly based on input data, no fabrication or exaggeration
• Deep analysis: focuses on comparisons, trends, ablations, and trade-offs rather than accounting-style number listing
• Structured LaTeX output: uses \paragraph{Title Case Conclusion} + analysis text format
• Honest reporting: if data shows no clear advantage, describes it truthfully without forced conclusions
• Dual-part output: LaTeX code + Chinese translation for verifying data conclusion accuracy

Example Prompts

Analyze this comparison table and write LaTeX paragraphs for the Results section.

Here are my ablation study results, write the analysis for my ICML paper.

Interpret these training curves and write a discussion paragraph.

Source

• Skill folder: skills/experiment-analysis/
• Origin: awesome-ai-research-writing
• Standard: agentskills.io