Individual skill

ts-paper-figure

Stage 6 of the ts-paper suite. Fill a Traitement du Signal paper's figure placeholders with real diagrams. Claude DESIGNS a concrete, rich figure and GROUNDS it on a real on-topic top/mid-journal MAIN figure (Claude **WebSearches** for it, then `fetch_reference_figures.py` pulls that paper's MAIN figure, passed to the image model as an image-condition — grounding is MANDATORY, no silent skip); the render comes from the **official PaperBanana** pipeline (`ts-figure-svg/scripts/setup_paperbanana.py`, its own Retriever→Planner→Stylist→Visualizer→Critic) or, unconfigured, the built-in `gen_image.py`; Claude then LOOKS at the PNG with its own vision and critiques/refines it over ≥2 ENFORCED rounds. The approved PNG is then **redrawn as a native editable SVG by ts-figure-svg** — its design language learned, its content re-derived from the paper, audited and repaired over ≥4 measured rounds (never a pixel trace); if that is impossible the ts-figure-optimize DrawAI HYBRID or the approved PNG is kept — never a lossy redraw, PNG always kept. Engine is routed by SECTION: only real measured-data results plots (data-aware mode, results section) use matplotlib; EVERY other figure — architecture/pipeline/concept/math-geometry/schematic — is image-model rendered (so in proposal mode every figure is image-model). In proposal mode quantitative results plots are SKIPPED (no real data — drawing one fabricates results). Use to turn the empty \fbox placeholders into publication-quality figures.

skills/ts-paper-figure/SKILL.md

Source commit c17149def034bc777462de612926c8e3b6d01b8c

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