nature-paper2ppt
yuan1z0825/nature-skills
Transform scientific papers into polished Chinese academic presentations with figures and speaker notes.
What is nature-paper2ppt?
Converts research papers or reading notes into structured PPTX presentations optimized for Chinese academic contexts. Detects paper type (discovery, methods, resource, clinical, materials, or review), applies a narrative arc suited to that category, and generates slides with embedded figures and speaker notes ready for group meetings, literature reviews, or defense presentations.
- Automatically classifies paper type and applies matching narrative structure
- Extracts and embeds source figures with quality validation
- Generates speaker notes aligned to each slide's argument
- Maintains consistent terminology across all slides via a shared ledger
- Edits existing decks by reusing paper context and assets without full rebuild
- Audits final PPTX output against quality gates before delivery
How to install nature-paper2ppt
npx skills add https://github.com/yuan1z0825/nature-skills --skill nature-paper2ppt- Node.js and npm installed to run the skill installer
- A scientific paper (PDF, text, or notes) as source material
- Python environment available for running quality-audit scripts
How to use nature-paper2ppt
- 1.Install the skill using: npx skills add https://github.com/yuan1z0825/nature-skills --skill nature-paper2ppt
- 2.Provide the paper source (PDF, text excerpt, or reading notes) and specify the paper type if known
- 3.The skill will detect the paper type (discovery, methods, resource, clinical, materials, or review) and confirm it with you
- 4.Review the generated PPTX, which includes slides structured for the detected paper type, embedded figures, and speaker notes
- 5.For edits, request specific slide changes; the skill will update only those slides and re-audit the deck
Use cases
- Preparing a literature review presentation (文献汇报) for a research group meeting
- Converting a methods paper into a defense or conference talk with embedded algorithm diagrams
- Building a group-meeting slide deck (组会PPT) from recent research notes with consistent citations
- Refining an existing presentation by updating specific slides while preserving narrative flow
- Creating a discovery-paper presentation that traces the question-to-evidence arc
- Graduate students and postdocs preparing thesis defenses or group presentations
- Researchers presenting at conferences or seminars in Chinese-speaking institutions
- Lab groups conducting regular literature reviews or journal clubs
- Academic teams needing rapid, consistent slide decks from published papers
nature-paper2ppt FAQ
Six types: discovery (question-to-evidence), methods (problem-to-solution), resource (workflow-to-validation), clinical (design-to-inference), materials (property-to-mechanism), and review (evidence-map). The skill auto-detects the type from your source.
Yes. Provide the existing PPTX and specify which slides to change. The skill reuses the paper context, terminology, and assets, updating only the requested slides.
Yes, it identifies and embeds source figures from the paper. It validates figure quality and can crop or adjust them as needed.
Chinese by default, matching the skill's design for Chinese academic contexts. English or bilingual output can be requested if needed.
The skill runs an automated audit (audit_pptx_quality.py) on the final PPTX, checking layout, typography, figure embedding, and consistency. High-severity issues trigger revision before delivery.
Full instructions (SKILL.md)
Source of truth, from yuan1z0825/nature-skills.
name: nature-paper2ppt description: Create or improve a Chinese academic PPTX from a scientific paper or research reading notes, with source figures and speaker notes. Use for 论文做PPT、文献汇报、组会PPT and paper-based conference or defense presentations.
Paper-to-PPTX — Router
Routing protocol
For an edit to an existing deck, reuse its paper source, narrative, terminology, and assets. Change the requested slides and any affected cross-slide references; do not rerun paper intake or rebuild the deck's story unless the request requires it. Inspect changed slides and run the existing final PPTX audit before delivery. A requested outline or explanation alone does not require creating a deck.
For a new task, load the core and matching resources below. Reuse already loaded guidance on follow-ups; load more only when the task needs it.
1. Load the manifest and the core layer
Read manifest.yaml. It declares the paper_type axis, the allowed values, and the file paths each value maps to.
Also read every file listed under always_load. These hold the purpose and core principle, the lean operating mode and toolchain policy, the 9-step workflow spine, and the output/quality rules that apply to every deck, plus the shared Terminology Ledger used to keep technical terms consistent across slides.
2. Classify the paper type
Decide the paper_type value using the manifest's detect: hint and the source:
discovery— discovery / mechanism papers (question-to-evidence arc). Default.methods— methods / AI / tool / algorithm papers (problem-to-solution arc).resource— resource / dataset / atlas / omics / benchmark papers (workflow-to-validation arc).clinical— clinical / population / intervention studies (design-to-inference arc).materials— materials / chemistry / physics / engineering papers (property-to-mechanism / design-to-performance arc).review— reviews / perspectives / commentaries / meta-analyses (evidence-map arc).
State the detected value in one short line to the user before designing slides, so they can correct you cheaply.
3. Load the matching fragment
Read the file mapped for the detected paper_type. It gives the presentation arc and how to adapt the default slide structure for this type. Do not read every fragment in static/.
4. Build the deck using the loaded material
Apply the loaded fragments in this priority order:
- Core principles (
core/principles.md) — the argument is the spine; lean operating mode; accepted inputs; Chinese-by-default language rule. - Toolchain policy and fast path (
core/toolchain.md) — cross-platform Python-first stack, default fast path. - Paper-type arc (the loaded
paper_typefragment) — narrative order and slide structure for this paper. - Workflow (
core/workflow.md) — run the 9 steps end to end. - Output and quality rules (
core/output-and-quality.md) — deliverables, quality gates, fallbacks.
Build the Terminology Ledger (../nature-shared/core/terminology-ledger.md) while reading the source, so model names, gene/protein names, datasets, metrics, and abbreviations stay identical across every slide and speaker note.
When a deck is requested, the end product is a real .pptx, not only an outline or script. Do not fabricate results, numbers, or figure details.
5. Reach for references only when needed
The files under references/ are deep references, not defaults. Open them on demand per the references.on_demand table in the manifest:
- composing/auditing slide layout, visual rhythm, typography, anti-template design, archetypes, on-slide text budget →
references/design-and-layout.md. - selecting, extracting, cropping, and quality-checking figure/table assets →
references/figure-assets.md. - running the self-review/corrective revision loop, severity grading, programmatic PPTX checks, rendered-preview policy, and final verification →
references/self-review.md.
When a real PPTX has been generated, run scripts/audit_pptx_quality.py unless the file is unavailable. Treat high-severity findings as blockers, revise the deck, then re-run the audit and record the final result in output/qa_report.md.
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