research-figure-studio

name

research-figure-studio

description

Generate scientific figures from papers, LaTeX manuscripts, patent drafts, method descriptions, and technical notes by routing requests to the correct backend. Use when Codex needs to create an editable architecture diagram, a publication-style method figure, a visual abstract, a teaser illustration, a patent figure, or a quantitative plot, and when backend selection, scientific content extraction, and figure verification matter as much as the final rendering.

Research Figure Studio

Route scientific figure requests to the right backend and normalize them into a shared figure plan.

Use this skill as the top-level orchestrator. Do not force every figure through one rendering path.

Workflow

For the normal one-click path, prefer:

python3 scripts/run_figure_pipeline.py --source-file paper.tex --request "生成投稿用方法图" --output-dir out

This wrapper will:

• route the figure request
• build figure_intent.yaml
• compile backend-ready artifacts
• invoke the installed backend skill
• verify the result
• compile a paper-ready caption file, with source-aware fallback when the intent is thin
• write bundle.yaml

1. Route The Figure

Determine the figure class first.

Use:

• editable-diagram
• method-overview
• visual-abstract
• teaser
• system-concept
• chart-or-plot
• patent-figure
• hybrid-figure

Then choose the backend:

• drawio for strict structure and editable topology
• banana for image-first paper illustrations
• plot for quantitative charts and metrics
• hybrid when structure and visual polish are both required

Use:

python3 scripts/route_figure_backend.py --request "根据这篇论文生成方法图" --source-file paper.tex

Read:

• references/figure-classes.md
• references/backend-routing.md

2. Extract Scientific Structure

Extract only the figure-relevant scientific content:

• title
• task
• inputs
• outputs
• main stages
• branches
• feedback loops
• must-keep terms

Do not dump the entire paper into a prompt.

Use:

python3 scripts/extract_scientific_figure_content.py --source-file paper.tex

3. Build The Shared Figure Intent

Convert the routed task and extracted content into figure_intent.yaml.

This file is the shared contract between understanding and rendering.

Use:

python3 scripts/build_figure_intent.py --source-file paper.tex --request "生成投稿方法图" -o figure_intent.yaml

Read:

• references/figure-intent-schema.md

4. Compile For The Chosen Backend

If backend is banana, compile a tightly-scoped image prompt:

python3 scripts/compile_banana_prompt.py figure_intent.yaml -o figure.prompt.txt

If backend is drawio, delegate to drawio-architecture-diagram.

If backend is plot, compile a plot spec and render both an SVG chart and a polished PNG preview:

python3 scripts/compile_plot_package.py figure_intent.yaml -o figure.plot_spec.yaml
python3 scripts/render_plot_svg.py figure.plot_spec.yaml -o figure.svg
python3 scripts/render_plot_png.py figure.plot_spec.yaml -o figure.png

The plot backend is intended for:

• Markdown tables
• CSV tables
• common LaTeX tabular tables
• line, grouped-bar, stacked-bar, and scatter plots
• time-series charts with dense-label reduction and preview-ready layout
• error bars, dual-axis plots, and request-driven log scales

If backend is hybrid, generate both the editable structure and the quantitative panel:

python3 scripts/run_figure_pipeline.py \
  --source-file examples/hybrid/corridor_results_hybrid.md \
  --request "generate a hybrid figure with structure and result chart" \
  --output-dir out/hybrid_demo

The hybrid backend currently outputs:

• a .drawio architecture file
• plot SVG + PNG artifacts
• a composed preview PNG for GitHub, papers, or demos

Read:

• references/scientific-figure-prompt-patterns.md
• references/caption-guidelines.md

5. Verify Before Finalizing

Verify:

• required stages are present
• the backend matches the figure need
• labels are not overloaded
• the result did not drift away from the scientific story

Use:

python3 scripts/verify_figure_result.py --intent figure_intent.yaml --artifact output.png --backend banana

Read:

• references/verification-rules.md
• references/failure-cookbook.md

6. Iterate Or Switch Backend

If verification fails:

• reduce text
• reduce modules
• tighten composition
• strengthen forbidden details

If the image backend still drifts on a structure-heavy figure:

• stop retrying image generation
• switch to drawio

Practical Rules

• Prefer one clear scientific story per figure.
• Keep visible labels short.
• Treat figure_intent.yaml as the source of truth.
• Use drawio when exact module placement matters.
• Use banana when communication value matters more than exact topology.
• Use plot for metrics, charts, and ablations.
• Use hybrid when the source includes both stages and quantitative evidence.

Bundled Scripts

• scripts/route_figure_backend.py
• scripts/extract_scientific_figure_content.py
• scripts/build_figure_intent.py
• scripts/compile_figure_caption.py
• scripts/compile_banana_prompt.py
• scripts/compile_drawio_package.py
• scripts/compile_plot_package.py
• scripts/plot_render_utils.py
• scripts/render_plot_png.py
• scripts/render_plot_svg.py
• scripts/render_hybrid_preview.py
• scripts/verify_figure_result.py
• scripts/run_figure_pipeline.py

Output Contract

Return:

1. chosen figure class
2. chosen backend and reason
3. figure_intent.yaml
4. backend-ready artifact such as a prompt or diagram package
5. generated caption file
6. verification summary
7. fallback recommendation when needed

Failure Handling

If the figure type is unclear:

• emit the top two candidate figure classes
• explain the tradeoff
• default to the more controllable backend

If the extracted structure is too weak:

• produce a best-effort figure_intent.yaml
• mark assumptions explicitly

If the user asks for a chart but provides no data:

• stop and state the missing quantitative inputs