Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add YuanyuanMa03/academic-research-skills --skill nature-paper2pptgit clone --depth 1 https://github.com/YuanyuanMa03/academic-research-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/yuanyuanma03/academic-research-skills/nature-paper2ppt)<a href="https://agentmods.dev/skills/yuanyuanma03/academic-research-skills/nature-paper2ppt"><img src="https://agentmods.dev/badge/skills/yuanyuanma03/academic-research-skills/nature-paper2ppt/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/yuanyuanma03/academic-research-skills/nature-paper2ppt"><img src="https://agentmods.dev/badge/skills/yuanyuanma03/academic-research-skills/nature-paper2ppt.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00146 | $0.07908 |
| Opus 5.5 | $0.00058 | $0.03163 |
| Sonnet 5.5 | $0.00029 | $0.01582 |
| Haiku 4.5 | $0.00015 | $0.00791 |
Grade A, and why
nature-paper2ppt scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 699 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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:
- Why does this problem matter?
- What gap or bottleneck does the paper address?
- What did the authors do?
- What is the key evidence?
- Why should we trust the result?
- What is new, reusable, or broadly meaningful?
- 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,
- design slides with varied, evidence-led composition rather than rigid AI-looking card templates,
- prevent text overflow by writing shorter on-slide copy, using larger text boxes, and splitting slides when needed,
- run at least one self-audit and correction pass on the generated PPTX,
- run lightweight structural checks on the PPTX package after revision,
- 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.
What ships with it
15 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- manifest.yaml 2.5 KB
- README.md 5.2 KB
- references/design-and-layout.md 11 KB
- references/figure-assets.md 3.1 KB
- references/self-review.md 5.5 KB
- static/core/output-and-quality.md 4.2 KB
- static/core/principles.md 2.9 KB
- static/core/toolchain.md 2.5 KB
- static/core/workflow.md 5.3 KB
- static/fragments/paper_type/clinical.md 1.2 KB
- static/fragments/paper_type/discovery.md 1.3 KB
- static/fragments/paper_type/materials.md 1.2 KB
- static/fragments/paper_type/methods.md 1.2 KB
- static/fragments/paper_type/resource.md 1.1 KB
- static/fragments/paper_type/review.md 1.0 KB
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- today First seen · 699 lines · 146 tokens per session scan A 69b5d9daa685
nature-paper2ppt is a skill published in the GitHub repository YuanyuanMa03/academic-research-skills (75 stars, last pushed today), licensed MIT. It adds 146 tokens to every session and 7,908 once invoked, about $0.0006 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-29.
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manuscript-optimizer
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review-article-architecture
Use when writing, restructuring, or auditing a Review, survey, or Perspective rather than a research article, especially a commissioned one written across many sessions. Covers the governing plan document, drift detection, single-definition thesis and field judgements, section-owns-figure allocation, display-item…
write-scientific-manuscript
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Referee-side skill for Nature Portfolio manuscripts: write a referee report, inventory every ask and sub-ask in received comments, grade drafted replies, and test reply readability. Check methodology, statistics, reporting, reproducibility and data/code availability. Preserve referee wording, numbering and order…
figure-planner
Use when designing, restructuring, or auditing manuscript figures and you need to define one main claim per figure, assign panel roles, align legends with the text, or decide what belongs in main figures versus supplement.