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 niuz257470-ctrl/natureskills --skill nature-paper2pptgit clone --depth 1 https://github.com/niuz257470-ctrl/natureskillsWrote 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/niuz257470-ctrl/natureskills/nature-paper2ppt)<a href="https://agentmods.dev/skills/niuz257470-ctrl/natureskills/nature-paper2ppt"><img src="https://agentmods.dev/badge/skills/niuz257470-ctrl/natureskills/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/niuz257470-ctrl/natureskills/nature-paper2ppt"><img src="https://agentmods.dev/badge/skills/niuz257470-ctrl/natureskills/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 | $0.00130 | $0.04984 |
| Opus 5.5 | $0.00052 | $0.01994 |
| Sonnet 5.5 | $0.00026 | $0.00997 |
| Haiku 4.5 | $0.00013 | $0.00498 |
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 2mo ago.
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.
This is a copy
98% identical to nature-paper2ppt — 12 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 496 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,
- 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.
What ships with it
1 file 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.
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.
- 2mo ago First seen · 496 lines · 130 tokens per session scan A 9d2fd9d953d5
nature-paper2ppt is a skill published in the GitHub repository niuz257470-ctrl/natureskills (72 stars, last pushed 5mo ago), licensed MIT. It adds 130 tokens to every session and 4,984 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 98% identical to nature-paper2ppt, differing in 12 lines, and is treated as a copy.
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