lingzhi227/table-generation
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 skills add https://github.com/lingzhi227/agent-research-skills --skill table-generation
Convert experimental results into publication-ready LaTeX tables.
$0 — Table type: comparison, ablation, descriptive, custom$1 — Data source: JSON file, CSV file, or inline datapython ~/.claude/skills/table-generation/scripts/results_to_table.py \
--input results.json --type comparison \
--bold-best max --caption "Performance comparison" \
--label tab:main_results
Supports: comparison, ablation, descriptive, multi-dataset table types.
Additional flags: --type multi-dataset for methods x datasets x metrics layout, --significance for p-value stars, --underline-second for second-best results.
~/.claude/skills/table-generation/references/table-templates.mdcomparison — Main results table\multirow for method categories (Supervised, Self-supervised, etc.)ablation — Ablation study tabledescriptive — Dataset/statistics tablecustom — Free-form table\usepackage{booktabs} % \toprule, \midrule, \bottomrule
\usepackage{multirow} % \multirow
\usepackage{multicol} % multi-column layouts
\usepackage{threeparttable} % table notes
Always generate tables with:
booktabs rules (\toprule, \midrule, \bottomrule)\caption{} and \label{tab:...}\textbf{}threeparttable when neededl for text, c or r for numbers)$\pm$ for standard deviations\underline{} for second-best results when appropriatetable* for wide tables spanning two columnsTake lingzhi227/table-generation from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.