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Generate publication-quality figures and tables from experiment results.
Passed 15 of 18 test cases with the skill, and 10 of 18 without it.
and 5 more in the full report
6 fixed12 passed either way4 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 5 test cases the skill fixed. Same model, same prompt, with and without the skill.
We already spent hours creating `figures/fig1_overview.pdf` using Figma. When executing the automated figure workflow, what should happen to this existing file?
| Checked | Without skill | With skill |
|---|---|---|
| Preserves existing manually created figure files in figures/ | Passed | Passed |
| Generates LaTeX inclusion code referencing the existing figure | Missed | Passed |
The instructions your model reads when the skill loads.
Generate all figures and tables for a paper based on: $ARGUMENTS
| Category | Can auto-generate? | Examples |
|---|---|---|
| Data-driven plots | ✅ Yes | Line plots (training curves), bar charts (method comparison), scatter plots, heatmaps, box/violin plots |
| Comparison tables | ✅ Yes | LaTeX tables comparing prior bounds, method features, ablation results |
| Multi-panel figures | ✅ Yes | Subfigure grids combining multiple plots (e.g., 3×3 dataset × method) |
| Architecture/pipeline diagrams | ❌ No — manual | Model architecture, data flow diagrams, system overviews. At best can generate a rough TikZ skeleton, but expect to draw these yourself using tools like draw.io, Figma, or TikZ |
| Generated image grids | ❌ No — manual | Grids of generated samples (e.g., GAN/diffusion outputs). These come from running your model, not from this skill |
| Photographs / screenshots | ❌ No — manual | Real-world images, UI screenshots, qualitative examples |
In practice: For a typical ML paper, this skill handles ~60% of figures (all data plots + tables). The remaining ~40% (hero figure, architecture diagram, qualitative results) need to be created manually and placed in figures/ before running /paper-write. The skill will detect these as "existing figures" and preserve them.
publication — Visual style preset. Options: publication (default, clean for print), poster (larger fonts), slide (bold colors)pdf — Output format. Options: pdf (vector, best for LaTeX), png (raster fallback)tab10 — Default matplotlib color cycle. Options: tab10, Set2, colorblind (deuteranopia-safe)figures/ — Output directory for generated figuresgpt-5.4 — Model used via a secondary Codex agent for figure quality review./paper-plan)figures/ or project rootIf no PAPER_PLAN.md exists, scan for data files and ask the user which figures to generate.
Parse the Figure Plan table from PAPER_PLAN.md:
test cases passed, vs 10 / 18 without
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