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Create SVG illustrations of active figures using one continuous black line and offset color patches that resemble misaligned printing. The skill guides poses, colors, composition, rendering, and visual checks for product pages and announcement cards.
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Write mathematical modeling competition papers from existing analysis reports, results, and figure PDFs. Use competition templates in Typst or LaTeX, tools for document layout, to organize sections, place figures, and prepare references and summaries.
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Draft or restructure scientific manuscripts using Nature-style argument patterns, starting from supplied results, figures, notes, or Chinese drafts. It organizes sections, connects claims to evidence, and identifies missing inputs while keeping conclusions within the research's demonstrated limits.
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Create charts in Python with detailed control over colors, axes, labels, legends, and layouts. Use it to build scientific figures, arrange multiple plots, and export results as PNG, PDF, or SVG files for papers and presentations.
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Develop and check research code in MATLAB/Octave or Python for signal processing, image analysis, statistics, and simulations. This skill supports reproducible workflows, checks units and assumptions, and prepares figures for papers and presentations.
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Check and improve existing English LaTeX papers, from compilation errors and bibliography issues to grammar, figures, tables, and pseudocode. Receive focused review comments and suggested fixes, with checks tailored to specific sections or publication venues.
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Write and review R analysis scripts for a sewage research project using its established conventions. Estimate requested regression models, add specifications, and save LaTeX tables, figures, and model objects for use in the research paper.
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Analyze datasets in R or Python, from exploring distributions and missing values to fitting regressions. Produce tables and figures for publication, save scripts and model results, and review the analysis for common problems.
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Draft English sections of a finance or economics paper from tables and figures supplied in a PDF. Confirm section plans and word counts, describe empirical findings, and develop research design, literature discussion, introduction, and conclusion in LaTeX.
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Generate code for economics paper figures, including event studies that show effects over time and coefficient comparisons. Adjust fonts, colors, dimensions, and export settings, with consistent file naming for use in manuscripts.
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Create Chinese academic presentation slides with Beamer, a LaTeX slide system, using a fixed CUFE template. Organizes research arguments, tables, and figures, with spacing and slide-splitting rules to address overflow, and supports updating existing decks.
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Build a reproducible Stata analysis from data cleaning through modeling, diagnostic checks, and robustness tests. Generate runnable .do files, regression tables, and figures for empirical papers, with additional workflows for epidemiology and machine learning approaches to causal inference.
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Build a Python workflow for empirical research, from data cleaning and statistical checks to estimation, robustness checks, and paper-ready tables and figures. Economics is the default, with additional modes for epidemiology, public health, and machine learning for causal inference.
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Draft and revise scientific manuscripts by organizing evidence into outlines, then developing connected paragraphs. Guides paper structure, citation formatting, figures and tables, and study-specific reporting requirements for research papers and journal submissions.
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Turn academic papers or written content into slide images, then combine them into PowerPoint and PDF files. The workflow extracts figures from PDFs and offers outline choices, visual styles, audience settings, and output languages.
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Build research slides from text sources using Slidev, Marp, Reveal.js, or Quarto. Keep source files manageable, reuse exported figures, and produce reproducible PDF presentations with a clear sequence and one conclusion per slide.
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Organize manuscript text, figures, and references with version control and repeatable builds. Track how each figure was produced, separate source files from generated outputs, and use automated checks to prepare submission artifacts.
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Generates publication-quality figures for ML papers from research context. Given a paper section or description, extracts system components and relationships to generate architecture diagrams via Gemini. Given experiment results or data, auto-selects chart type and generates data-driven figures via matplotlib/seaborn. Use when creating any figure for a conference paper.
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Use when designing or auditing figures for an Advanced Materials manuscript, including the lead figure, multi-panel characterization figures, and the Table-of-Contents graphic, where visual quality is a house expectation. Designs figure strategy; does not run the analysis or write prose.
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Compose multi-panel publication figures with patchwork, cowplot, gridExtra (R), or matplotlib GridSpec/subfigures (Python) including shared axes/legends/guides collection, panel labels in Nature/Cell convention, and journal-spec sizing. Covers patchwork ≥1.2.0 axes='collect' feature, Type-42 font embedding, and the cairo_pdf save path. Use when composing 2+ subpanels into a single figure for journal submission.
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Create, polish, and troubleshoot figures4papers-style publication-ready matplotlib figures, including grouped bars, trends, radar charts, heatmaps, concept diagrams, manifolds, and high-DPI/vector export workflows.
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Parse complex documents with IBM's open-source Docling library, which turns PDFs and Office files into structured Markdown or JSON. Use when a user asks to parse a document with tables, extract figures from a document, handle multi-column layouts, convert a complex PDF to structured data, extract content from academic papers, or process documents with mixed layouts. Handles tables, figures, headers, footers, and multi-column text.
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Use this when creating, modifying, reviewing, or saving charts, figures, plots, or visual summaries — including matplotlib/seaborn code, EDA figures, report figures, dashboards, or any task involving Japanese chart labels, color palettes, or figure styling.
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Compose multi-panel publication figures with patchwork, cowplot, gridExtra (R), or matplotlib GridSpec/subfigures (Python) including shared axes/legends/guides collection, panel labels in Nature/Cell convention, and journal-spec sizing. Covers patchwork ≥1.2.0 axes='collect' feature, Type-42 font embedding, and the cairo_pdf save path. Use when composing 2+ subpanels into a single figure for journal submission.
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