Purpose

Transform a scientific paper or paper-derived notes into a complete Chinese, figure-integrated PPTX presentation package with a Nature-style reporting logic.

The skill must not stop at an outline or script. The expected end product is a real .pptx deck. Keep supporting files minimal unless the user asks for more traceability.

Use this skill for papers across scientific fields, including:

• life sciences and medicine
• chemistry and materials science
• environmental and earth sciences
• physics and engineering
• computational biology, AI, and methods papers
• interdisciplinary Nature-family style research
• reviews, perspectives, resources, datasets, and benchmark papers

Core Principle

Use the paper's scientific argument as the presentation spine.

The default slide logic should help the audience answer, in order:

1. Why does this problem matter?
2. What gap or bottleneck does the paper address?
3. What did the authors do?
4. What is the key evidence?
5. Why should we trust the result?
6. What is new, reusable, or broadly meaningful?
7. Where are the boundaries and open questions?

This is more important than copying the paper section order.

Lean Operating Mode

Default to the lowest-overhead workflow that still produces a usable PPTX.

Do:

• read only the source material needed to understand the paper's argument,
• extract only figures/tables that will actually appear in the deck,
• create the PPTX as the primary deliverable,
• run lightweight structural checks on the PPTX package,
• write a short QA report.

Avoid by default:

• exhaustive extraction of every figure, page, image, table, or supplement,
• full OCR unless normal text extraction fails or the PDF is scanned,
• saving full raw extracted paper text unless it is needed for debugging or reuse,
• installing new dependencies when an existing tool can complete the task,
• launching GUI apps or desktop automation just to render previews,
• generating long markdown scripts when the user only needs a deck,
• rendering every slide when no reliable headless renderer is available.

Toolchain Policy

Use a cross-platform Python-first stack unless the user explicitly asks for something else:

• PyMuPDF for metadata, text extraction, page rendering, and page-level crops,
• Pillow for figure crops, contact sheets, and lightweight preview images,
• python-pptx for slide authoring and PPTX-safe editing,
• zipfile plus a reopen pass through python-pptx for package validation.

This stack must work on macOS, Linux, and Windows. Use pathlib paths, project-local output directories, and Office-safe fonts or theme fonts. Do not hardcode OS font paths or platform-specific file locations. If Python packages are missing, create a local virtual environment and install the minimum packages only when policy permits; do not install broad document suites just to finish a normal deck.

Treat LibreOffice/soffice as optional, only when it is already available and a real rendered preview is worth the cost. Avoid Keynote, PowerPoint desktop automation, AppleScript, Preview, Finder, open, and any OS-specific font or path dependency in helper scripts. If a preview can be made from extracted slide objects or assets, prefer that over re-rendering the whole deck.

Ask or document the tradeoff before doing expensive extras such as full supplementary-material processing, high-resolution recreation of many figures, full slide-by-slide rendered QA, or very long decks.

Accepted Inputs

The skill may receive:

• a full paper PDF
• supplementary figures or tables
• Word or markdown converted paper text
• abstract + results + figure legends
• structured reading notes
• manually pasted article content
• an input/source.md file
• a user-provided PPTX template

Default output language is simplified Chinese unless the user requests otherwise. Preserve important technical terms, abbreviations, gene/protein names, model names, dataset names, equations, and statistical terms in English when needed.

Default Fast Path

For a normal selectable-text paper PDF, run the shortest complete path:

1. Extract metadata, abstract, headings, figure legends, and table captions with PyMuPDF.
2. Identify the paper type, argument, and candidate figures before rendering high-resolution pages.
3. Render low-resolution contact sheets only when figure locations are unclear.
4. Render high-resolution images only for selected figure/table pages and crop only assets that will appear in the deck.
5. Build the PPTX directly with python-pptx, using native tables/charts when values are explicit and figure crops when the original visual carries the evidence.
6. Verify by reopening the PPTX and inspecting package structure; render slide previews only if a reliable cross-platform headless renderer is already available.

OCR, full supplementary extraction, all-page high-resolution rendering, all-slide rendered QA, and long script files are opt-in or justified exceptions, not defaults.

Workflow

Step 1. Read and extract source material

Extract, when available:

• title, authors, journal/preprint server, year, DOI
• field and subfield
• paper type
• central problem and knowledge gap
• main claim or thesis
• study design, workflow, model, dataset, or experimental system
• key methods and controls
• main results and quantitative findings
• key figures, tables, and figure legends
• validation, robustness, ablation, or sensitivity analyses
• limitations and unresolved questions
• broader scientific, clinical, technical, environmental, or translational meaning

Do not invent missing numbers, mechanisms, datasets, or figure details. Use a two-pass reading strategy: first capture metadata, abstract, headings, figure legends, and table captions; then read only the result and methods pages needed to support the slides.

Step 2. Classify the paper before designing slides

Identify the primary paper type. Choose the closest fit:

• discovery / mechanism paper
• translational or applied science paper
• clinical or population study
• methods / algorithm / tool paper
• resource / dataset / atlas paper
• omics, single-cell, spatial, or multi-modal study
• materials / chemistry / engineering performance study
• environmental, ecological, or earth-system study
• benchmark / evaluation paper
• review / perspective / commentary
• meta-analysis / systematic review

Then identify the best presentation logic:

• claim-first: useful when the paper has one strong central claim
• question-to-evidence: useful for mechanism and discovery papers
• problem-to-solution: useful for methods, tools, and engineering papers
• workflow-to-validation: useful for datasets, atlases, omics, and benchmarks
• evidence-map: useful for reviews and perspectives

Step 3. Build the Chinese presentation plan

Default length: 12-16 slides for a 15-20 minute report.

The default structure is:

1. 标题页
2. 研究背景：为什么这个问题重要
3. 知识缺口 / 技术瓶颈
4. 论文核心问题与主张
5. 研究设计 / 技术路线 / 分析框架
6. 关键证据1
7. 关键证据2
8. 关键证据3
9. 验证、对照或稳健性证据
10. 机制模型 / 方法优势 / 综合框架
11. 创新点与可复用价值
12. 局限性与未解决问题
13. 总结与讨论

Adapt this structure to the paper type. Do not force every paper into the same template.

For a quick or unspecified request, prefer 10-14 slides. Expand beyond 16 slides only when the user asks for a detailed seminar deck or the paper genuinely needs the extra space to stay readable.

Step 4. Select figures as evidence, not decoration

Inspect the source for:

• graphical abstracts or summary models
• study design and workflow diagrams
• central result figures
• microscopy or imaging panels
• heatmaps, dimensionality reduction, networks, maps, or spatial plots
• survival curves, forest plots, calibration curves, or statistical result plots
• materials characterization and performance plots
• model architecture, benchmark, ablation, or error analysis figures
• key tables
• validation or control figures

Prioritize figures that carry the paper's argument:

1. design/workflow,
2. main evidence,
3. validation or robustne