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/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.

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agent-research-skills
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Install
$ npx -y skills add lingzhi227/agent-research-skills --skill table-generation --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/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.md
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 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

  • 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
Ships withagent-research-skills

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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Repo: lingzhi227/agent-research-skills

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