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Found 4 Skills
Stata statistical analysis for publication-ready sociology research. Guides you through phased workflows for DiD, IV, matching, panel methods, and more. Use when doing quantitative analysis in Stata for academic papers.
Academic-first Draw.io figure skill for papers, theses, IEEE-style diagrams, architecture figures, workflows, roadmaps, formulas, and publication-ready visualizations. Use when users ask to draw, redraw, replicate, edit, or export diagrams for academic papers or technical documents. Creates offline .drawio + .spec.yaml + .arch.json bundles, exports SVG locally, uses draw.io Desktop CLI for embedded SVG/PNG/PDF/JPG, supports style presets, self-check review loops, and diagrams.net URL fallback without requiring MCP.
Generate publication-ready scientific figures in Python/matplotlib with a consistent figures4papers house style. Use when creating or refining academic bar/trend/heatmap/scatter/multi-panel figures, enforcing visual consistency, or exporting paper-ready PNG/PDF/SVG outputs.
Prepare, audit, or revise Nature-ready Data Availability statements, data repository plans, dataset citations, and FAIR metadata checklists for manuscripts. Use when the user asks about Nature data availability, research data sharing, repository selection, accession numbers, restricted or sensitive data, source data, supplementary datasets, DataCite-style dataset references, FAIR metadata for academic publication, or Chinese-to-English data availability wording for Chinese-speaking authors preparing Nature-family submissions.