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.
How do I install this agent skill?
npx skills add https://github.com/lingzhi227/agent-research-skills --skill table-generationIs this agent skill safe to install?
- Gen Agent Trust Hubpass
This skill is a specialized utility for generating publication-quality LaTeX tables from experimental data. It operates locally using a bundled Python script to process user-provided JSON or CSV files and does not exhibit any malicious behaviors such as data exfiltration, remote code execution, or privilege escalation.
- Socketpass
No alerts
- Snykpass
Risk: LOW · No issues
- Runlayerpass
1/3 files flagged
- ZeroLeakspass
Score: 93/100 · 2 sections analyzed
What does this agent skill do?
Table Generation
Convert experimental results into publication-ready LaTeX tables.
Input
$0— Table type:comparison,ablation,descriptive,custom$1— Data source: JSON file, CSV file, or inline data
Scripts
Generate LaTeX table from JSON/CSV
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.
References
- LaTeX table templates and examples:
~/.claude/skills/table-generation/references/table-templates.md
Table Types
comparison — Main results table
- Rows = methods (baselines + ours), Columns = metrics/datasets
- Bold the best result in each column
- Include mean +/- std when available
- Use
\multirowfor method categories (Supervised, Self-supervised, etc.)
ablation — Ablation study table
- Rows = variants (full model, minus component A, minus component B, ...)
- Columns = metrics
- Bold the full model result
- Use checkmarks for component presence
descriptive — Dataset/statistics table
- Dataset characteristics, hyperparameters, or summary statistics
- Clean formatting with proper units
custom — Free-form table
- User specifies layout and content
Required Packages
\usepackage{booktabs} % \toprule, \midrule, \bottomrule
\usepackage{multirow} % \multirow
\usepackage{multicol} % multi-column layouts
\usepackage{threeparttable} % table notes
Output Format
Always generate tables with:
booktabsrules (\toprule,\midrule,\bottomrule)\caption{}and\label{tab:...}- Bold best results using
\textbf{} - Table notes via
threeparttablewhen needed - Proper alignment (
lfor text,corrfor numbers)
Rules
- Only include numbers from actual experimental logs — never hallucinate results
- All numbers must match the data source exactly
- Use
$\pm$for standard deviations - Use
\underline{}for second-best results when appropriate - Keep tables compact — avoid unnecessary columns
- Use
table*for wide tables spanning two columns - Add glossary/notes for abbreviated column headers
Related Skills
- Upstream: data-analysis, experiment-code
- Downstream: paper-writing-section, paper-compilation
- See also: figure-generation
How can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
<a href="https://skillzs.dev/skills/lingzhi227/agent-research-skills/table-generation">View table-generation on skillZs</a>