菜单
Use when analyzing experimental results, validating comparisons, generating paper-ready results text, or turning model-evaluation outputs into figures, tables, and defensible claims.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/Boom5426/Nature-Paper-Skills --skill results-analysis命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
Use when auditing, restructuring, or revising a research manuscript whose scientific question, claim hierarchy, evidence chain, section logic, figures, terminology, or prose may be unclear or out of sync. Apply before sentence-level polishing, especially for whole drafts, major revisions, resubmissions, overclaiming, experiment-by-experiment Results, inaccessible narratives, or manuscripts that need a claim-driven architecture.
Entry point for any manuscript request that does not name a specific skill. Load this FIRST whenever the ask is general, then run the chain it prescribes. Covers optimize my paper, improve the manuscript, polish this draft, make this better, clean it up, help with my paper, review my writing, get this ready to submit, work on the paper, and the Chinese equivalents 优化论文, 改论文, 润色论文, 帮我看看论文, 论文写作, 学术写作, 把论文弄好, 论文修改, 投稿前检查. Also decides which skill applies and how to sequence manuscript work from project setup through submission and rebuttal, including the separate path for a Review, survey, or Perspective. A general manuscript request is never served well by one skill alone; this file decides which chain to run.
Analyze, draft, revise, or audit scientific peer-review response letters and point-by-point rebuttals. Use for reviewer comments, response letters, rebuttals, revision summaries, quoted manuscript changes, replies that must align with a manuscript or Supplementary Information, and submission-ready checks of direct question-answer alignment, evidence, figures, tables, notes, panels, terminology, numbers, and internal citations. Especially useful when replies must reuse the reviewer's terms, map every sub-question to an explicit answer, report new analyses or experiments, identify exact revision locations, or distinguish mandatory fixes from optional polishing.
基于 SOC 职业分类
正在显示 SKILL.md
| name | results-analysis |
| description | Use when analyzing experimental results, validating comparisons, generating paper-ready results text, or turning model-evaluation outputs into figures, tables, and defensible claims. |
A systematic experimental results analysis workflow connecting experimental data to paper writing.
This skill provides three core capabilities:
Use this skill when you need to:
Data Loading → Data Validation → Statistical Analysis → Visualization → Writing → Quality Check
Supported Data Formats:
Data Validation Checks:
Select appropriate tools for data loading and preliminary validation based on data format.
Basic Statistics:
Significance Tests:
Select appropriate statistical tests based on data characteristics.
Key Principles:
See references/statistical-methods.md for the complete statistical methods guide.
Comparison Dimensions:
Comparison Methods:
Systematically compare performance across different methods, ensuring fair comparison.
Publication-Quality Visualization Requirements:
Common Chart Types:
Use appropriate visualization tools to generate publication-quality figures.
See references/visualization-best-practices.md for the visualization guide.
Results Section Structure:
## Results
### Overview of Main Findings
[1-2 paragraphs summarizing core results]
### Experimental Setup
[Brief description of experimental configuration; details in appendix]
### Performance Comparison
[Comparison with baseline methods, including tables and figures]
### Ablation Study
[Validate contributions of each component]
### Statistical Significance
[Report statistical test results]
### Qualitative Analysis
[Case studies, visualization examples]
Writing Principles:
See references/results-writing-guide.md for the complete writing guide.
Checklist:
❌ Wrong approach:
✅ Correct approach:
❌ Wrong approach:
✅ Correct approach:
❌ Wrong approach:
✅ Correct approach:
See references/common-pitfalls.md for the complete error patterns and fixes.
This skill focuses on experimental results analysis and works in tandem with the writing skills in this repository:
results-analysis handles:
scientific-writing or conference-paper-writing handle:
Workflow Integration:
Experiments complete → results-analysis analyzes
↓
Generate analysis report and visualizations
↓
scientific-writing or conference-paper-writing integrates into paper
↓
Complete Results section
After analysis, the following are generated:
Analysis Report (analysis-report.md)
Visualization Files (figures/)
Results Draft (results-draft.md)
Refer to the examples/ directory for complete examples:
example-analysis-report.md - Complete analysis report exampleexample-results-section.md - Paper Results section exampleThe complete analysis pipeline includes:
See the guides in the references/ directory for detailed methods and best practices.
references/statistical-methods.md - Complete statistical methods guidereferences/results-writing-guide.md - Results section writing standardsreferences/visualization-best-practices.md - Visualization best practicesreferences/common-pitfalls.md - Common errors and fixes✅ Recommended:
❌ Prohibited:
✅ Recommended:
❌ Prohibited:
✅ Recommended:
❌ Prohibited:
This skill provides a systematic experimental results analysis workflow:
Following these principles produces high-quality, reproducible experimental results analysis that meets top conference standards.