algorithm-design
Design algorithms with LaTeX pseudocode and UML diagrams. Generate algorithmic environments,…
Generate publication-quality LaTeX tables from experimental results. Convert JSON/CSV data to booktabs-styled tables with bold best results, multi-row layouts, and proper captions. Use when creating result tables, comparison tables, or ablation tables for papers.
$ npx -y skills add lingzhi227/agent-research-skills --skill table-generation --agent claude-codeHow it fires
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Generate publication-quality LaTeX tables from experimental results. Convert JSON/CSV data to booktabs-styled tables with bold best results, multi-row layouts, and proper captions. Use when creating result tables, comparison tables, or ablation tables for papers.
name: table-generation description: Generate publication-quality LaTeX tables from experimental results. Convert JSON/CSV data to booktabs-styled tables with bold best results, multi-row layouts, and proper captions. Use when creating result tables, comparison tables, or ablation tables for papers. argument-hint: [data-source]
Convert experimental results into publication-ready LaTeX tables.
python ~/.claude/skills/table-generation/scripts/results_to_table.py \ --input results.json --type comparison \ --bold-best max --caption "Performance comparison" \ --label tab:main_results
Supports: `comparison`, `ablation`, `descriptive`, `multi-dataset` table types. Additional flags: `--type multi-dataset` for methods x datasets x metrics layout, `--significance` for p-value stars, `--underline-second` for second-best results.
\usepackage{booktabs} % \toprule, \midrule, \bottomrule
\usepackage{multirow} % \multirow
\usepackage{multicol} % multi-column layouts
\usepackage{threeparttable} % table notesAlways generate tables with: 1. `booktabs` rules (`\toprule`, `\midrule`, `\bottomrule`) 2. `\caption{}` and `\label{tab:...}` 3. Bold best results using `\textbf{}` 4. Table notes via `threeparttable` when needed 5. Proper alignment (`l` for text, `c` or `r` for numbers)
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