| name | academic-figure |
| description | Create or review publication-ready academic figures that meet journal submission specs (IEEE / Elsevier / Nature, plus Springer and chinese-thesis presets) using matplotlib(+seaborn) or plotly; in industrytslib projects it drives that library's built-in visualization system. Use for 论文配图, 期刊图, 科研绘图, 中文学位论文配图, "publication-ready figure". Do NOT use to reproduce a specific paper's figure or style — that is paper-plot.
|
| category | academic-research-tools |
| tags | ["academic-figures","matplotlib","seaborn","plotly","ieee","elsevier","nature","publication"] |
| version | 0.1.0 |
Academic Figure
Route a "make me a journal-compliant figure" request across two axes — journal
style (ieee / elsevier / nature, plus springer / chinese-thesis) and
library (matplotlib(+seaborn) / plotly) — then either drive an industrytslib
project's built-in visualization system or generate a standalone spec-compliant
figure. Argue the figure first; write code last.
<skill-dir> below is this skill's directory — substitute the absolute path
announced when the skill loads. On Windows, prefix Python runs with
PYTHONUTF8=1.
Routing protocol
Work the six steps in order.
- Figure contract. Read
references/figure-contract.md and lock the claim
before plotting: core conclusion (one sentence) → evidence chain / panel
mapping → prototype class (quantitative grid / schematic-led / image+quant /
asymmetric) → journal export contract.
- Journal-style axis. Resolve in priority order: explicit request >
submission context (target journal) > saved preference
(
python <skill-dir>/scripts/academic_figure_pref.py get journal_style) >
ask once ("Target journal style? ieee / elsevier / nature, or springer /
chinese-thesis"). After the user answers, persist it with the matching set.
- Library axis. Resolve: explicit request > project context (libraries
already imported; an industrytslib project uses its matplotlib/plotly
backend) > saved preference
(
python <skill-dir>/scripts/academic_figure_pref.py get library) > default
matplotlib (recommend plotly only when interactive/web output is needed).
seaborn is not a separate axis — it is a matplotlib-layer API and specs still
resolve down to rcParams.
- industrytslib integration check. If the user names industrytslib, or the
project's dependencies/imports include
industrytslib, read
references/industrytslib-integration.md and drive figures through
create_plotter(...) / plotter.set_style(...) — call the library, never
modify it. Otherwise take the standalone path (journal specs + a library
recipe).
- Load references on demand. Read only what the resolved axes need: the
matched card in
references/journal-specs.md, one library recipe
(references/matplotlib-recipes.md or references/plotly-recipes.md), and
the matched family section in references/chart-recipes.md.
- Export & QA. Export per the spec card (vector-first,
fonttype=42,
colorblind-safe default palette), then walk every item in
references/qa-checklist.md before delivering.
Route elsewhere
| Request | Route to |
|---|
| Reproduce a specific paper's figure, name a paper-plot style folder, or "照着这个图画" | paper-plot (skills/research-learning-knowledge/paper-plot) |
| Deep-read or summarize a single paper | literature-mentor (skills/research-learning-knowledge/literature-mentor) |
| Intake or synthesize across many papers | paper-workbench (skills/research-learning-knowledge/paper-workbench) |
Resources
- Contract & QA:
references/figure-contract.md, references/qa-checklist.md
- Journal specs:
references/journal-specs.md — IEEE / Elsevier / Nature cards + springer / chinese-thesis extensions
- Library recipes:
references/matplotlib-recipes.md, references/plotly-recipes.md
- Chart families:
references/chart-recipes.md
- industrytslib:
references/industrytslib-integration.md
- Preference CLI:
scripts/academic_figure_pref.py — persists library and journal_style
References and scripts are populated in later build phases; the filenames above are the stable contract.
