nature-paper2ppt
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.
Install / Use
npx skills add Yuan1z0825/nature-skills --skill nature-paper2pptInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Education & ResearchSupported Platforms
Tags
Our assessment of nature-paper2ppt
nature-paper2ppt scores 86/100 on our quality scale, 281st of 441 Education & Research skills we index.
Its SKILL.md is 4.1 KB long, split into 7 sections and no code examples: a solid amount of guidance for an agent.
With 44,346 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated about 2 months ago, so nature-paper2ppt is actively maintained.
- Our last check on 2026-11-03 found the source still online.
- It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.
AI review by kimi-k2.7-code on 2026-09-25. Automated pattern scan on 2026-09-25. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
nature-paper2ppt compared with similar skills
All 4 of these similar skills score higher than nature-paper2ppt; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| nature-paper2ppt (this skill)by Yuan1z0825 | 86 | 44.3k | 46d ago | SKILL.md |
| last30days-skillby mvanhorn | 100 | 67.0k | today | CLAUDE.md |
| algorithmic-artby anthropics | 100 | 177.9k | 47d ago | SKILL.md |
| pptxby anthropics | 100 | 177.9k | 47d ago | SKILL.md |
| designby nextlevelbuilder | 100 | 143.4k | 8d ago | SKILL.md |
Frequently asked questions
- How do I install nature-paper2ppt?
- Run
npx skills add Yuan1z0825/nature-skills --skill nature-paper2ppt. The install tabs above show the steps for each supported agent. - Which AI agents does nature-paper2ppt work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is nature-paper2ppt safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It is Apache-2.0-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is nature-paper2ppt still maintained?
- The repository was last updated about 2 months ago, so nature-paper2ppt is actively maintained.
Skill content
View source on GitHubname: 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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Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
