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lingzhi227/agent-research-skills1.1k installs

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-generation
view source ↗

Is 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 \multirow for 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:

  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)

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

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>