/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 -y skills add lingzhi227/agent-research-skills --skill table-generation --agent claude-codeHow it fires
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/table-generation
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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.
SKILL.md
table-generation.SKILL.mdname: 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]
Table Generation
Convert experimental results into publication-ready LaTeX tables.
Input
- `$0` — Table type: `comparison`, `ablation`, `descriptive`, `custom`
- `$1` — Data source: JSON file, CSV file, or inline data
Scripts
Generate LaTeX table from JSON/CSV
python ~/.claude/skills/table-generation/scripts/results_to_table.py \
--input results.json --type comparison \
--bold-best max --caption "Performance comparison" \
--label tab:main_results
Supports: `comparison`, `ablation`, `descriptive`, `multi-dataset` table types. Additional flags: `--type multi-dataset` for methods x datasets x metrics layout, `--significance` for p-value stars, `--underline-second` for second-best results.
References
- LaTeX table templates and examples: `~/.claude/skills/table-generation/references/table-templates.md`
Table Types
`comparison` — Main results table
- Rows = methods (baselines + ours), Columns = metrics/datasets
- Bold the best result in each column
- Include mean +/- std when available
- Use `\multirow` for method categories (Supervised, Self-supervised, etc.)
`ablation` — Ablation study table
- Rows = variants (full model, minus component A, minus component B, ...)
- Columns = metrics
- Bold the full model result
- Use checkmarks for component presence
`descriptive` — Dataset/statistics table
- Dataset characteristics, hyperparameters, or summary statistics
- Clean formatting with proper units
`custom` — Free-form table
- User specifies layout and content
Required Packages
\usepackage{booktabs} % \toprule, \midrule, \bottomrule
\usepackage{multirow} % \multirow
\usepackage{multicol} % multi-column layouts
\usepackage{threeparttable} % table notesOutput Format
Always generate tables with: 1. `booktabs` rules (`\toprule`, `\midrule`, `\bottomrule`) 2. `\caption{}` and `\label{tab:...}` 3. Bold best results using `\textbf{}` 4. Table notes via `threeparttable` when needed 5. Proper alignment (`l` for text, `c` or `r` for numbers)
Rules
- Only include numbers from actual experimental logs — never hallucinate results
- All numbers must match the data source exactly
- Use `$\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
- Upstream: [data-analysis](../data-analysis/), [experiment-code](../experiment-code/)
- Downstream: [paper-writing-section](../paper-writing-section/), [paper-compilation](../paper-compilation/)
- See also: [figure-generation](../figure-generation/)
Read more
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]
Table Generation
Convert experimental results into publication-ready LaTeX tables.
Input
- `$0` — Table type: `comparison`, `ablation`, `descriptive`, `custom`
- `$1` — Data source: JSON file, CSV file, or inline data
Scripts
Generate LaTeX table from JSON/CSV
python ~/.claude/skills/table-generation/scripts/results_to_table.py \ --input results.json --type comparison \ --bold-best max --caption "Performance comparison" \ --label tab:main_results
Supports: `comparison`, `ablation`, `descriptive`, `multi-dataset` table types. Additional flags: `--type multi-dataset` for methods x datasets x metrics layout, `--significance` for p-value stars, `--underline-second` for second-best results.
References
- LaTeX table templates and examples: `~/.claude/skills/table-generation/references/table-templates.md`
Table Types
`comparison` — Main results table
- Rows = methods (baselines + ours), Columns = metrics/datasets
- Bold the best result in each column
- Include mean +/- std when available
- Use `\multirow` for method categories (Supervised, Self-supervised, etc.)
`ablation` — Ablation study table
- Rows = variants (full model, minus component A, minus component B, ...)
- Columns = metrics
- Bold the full model result
- Use checkmarks for component presence
`descriptive` — Dataset/statistics table
- Dataset characteristics, hyperparameters, or summary statistics
- Clean formatting with proper units
`custom` — Free-form table
- User specifies layout and content
Required Packages
\usepackage{booktabs} % \toprule, \midrule, \bottomrule
\usepackage{multirow} % \multirow
\usepackage{multicol} % multi-column layouts
\usepackage{threeparttable} % table notesOutput Format
Always generate tables with: 1. `booktabs` rules (`\toprule`, `\midrule`, `\bottomrule`) 2. `\caption{}` and `\label{tab:...}` 3. Bold best results using `\textbf{}` 4. Table notes via `threeparttable` when needed 5. Proper alignment (`l` for text, `c` or `r` for numbers)
Rules
- Only include numbers from actual experimental logs — never hallucinate results
- All numbers must match the data source exactly
- Use `$\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
- Upstream: [data-analysis](../data-analysis/), [experiment-code](../experiment-code/)
- Downstream: [paper-writing-section](../paper-writing-section/), [paper-compilation](../paper-compilation/)
- See also: [figure-generation](../figure-generation/)
31 skills for Claude Code covering the full academic research paper lifecycle — from literature search to slide generation — plus GitHub repository analysis for research topics. Extracted from 17 GitHub repos studying LLM-agent-driven research automation.
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