Figmirror
FigMirror mirrors the visual style of a top-conference paper figure (NeurIPS / ICML /...
Install
npx skills add VILA-Lab/FigMirror --skill figmirror -g -a claude-code -y- Repository
- VILA-Lab/FigMirror558
- Category
- Documents
- Updated
- 1mo ago
- License
- See repository
- Context cost
- Mediumabout 2,414 tokens
- Runs scripts
- Yes, review before use
What it does
FigMirror mirrors the visual style of a top-conference paper figure (NeurIPS / ICML / ICLR / Nature family) onto the user's own data. Takes dirty data plus a reference figure screenshot (cropped or uncropped), preprocesses the reference crop, runs a Drawer/Reviewer loop, and outputs a camera-ready PDF plus a self-contained matplotlib script with an inline DATA SECTOR.
FigMirror (figmirror)
Use this skill when the user wants to:
- Transfer the visual style of a top-conference paper figure to their own data.
- Produce a camera-ready matplotlib figure matching a reference screenshot in style, not in data.
- Mirror 3D paper-figure references such as surfaces, scatter, trajectories, bars, layered waterfalls, or plane projections when the reference or data is actually 3D.
- Receive a self-contained
.pyscript with editable inline data plus PNG/PDF outputs.
Required Inputs
- A reference figure screenshot (
PNG/JPG). It may include margins, captions, neighboring panels, or page text; Stage 0 preprocesses it. - The user's data in any parseable form: pasted table, CSV, TSV, markdown table, or dirty terminal text.
- A working directory for iteration artifacts.
3D Insert Gate
Enable references/three-d-prompting.md only when the user asks for a 3D
figure, the reference is visibly 3D, or the parsed data requires a 3D encoding
such as x/y/z, surfaces, trajectories, layered profiles, closed objects, 3D
small multiples, 3D bars, or plane projections. Do not use this insert to turn
an ordinary 2D task into 3D.
