nature-paper2ppt
Yuan1z0825/nature-skills · Agent Skill
Automatically generates Nature-style presentations from scientific papers, PDFs, or notes. Structures content, selects figures, and writes slide text and speaker notes in Chinese.
Jump to install ↓Overview
| Publisher | |
|---|---|
| Repository | Yuan1z0825/nature-skills ↗ |
| Skill folder | nature-paper2ppt |
| Stars | 39,583 |
| Bundled files | 2 |
| License | Apache-2.0 |
| Last updated | August 2, 2026 |
| Links | Skill source ↗ · Repository ↗ |
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Installation
A skill is a folder with a SKILL.md file. Pick your agent and run the commands in a terminal (macOS, Linux or Git Bash on Windows) from your project root.
Copy the prompt into Claude, Codex or another assistant: it will review the skill and install it for you.
Install the “nature-paper2ppt” skill from mozgi.io (https://mozgi.io/skills/nature-paper2ppt/) for me. 1. Download the archive: https://mozgi.io/skills/nature-paper2ppt/download If it fails, take the skill folder from the source: https://github.com/Yuan1z0825/nature-skills/tree/main/skills/nature-paper2ppt 2. Read SKILL.md and the other files. Check the skill is safe: no hidden commands, no sending data elsewhere, no scripts doing something other than described. If anything looks suspicious, stop and tell me. 3. Put the “nature-paper2ppt” folder into your agent's skills folder: .claude/skills/ for Claude Code, .agents/skills/ for Codex, .cursor/skills/ for Cursor, .gemini/skills/ for Gemini CLI. Inside the project if we are in one, otherwise in the home folder (~/.claude/skills/ etc.). 4. Make sure <skills folder>/nature-paper2ppt/SKILL.md exists. 5. Briefly tell me what this skill does and offer to try it on my task. If you cannot do a step yourself, tell me what to click or type.
git clone --depth 1 --branch main https://github.com/Yuan1z0825/nature-skills.git /tmp/nature-skills mkdir -p .claude/skills cp -r /tmp/nature-skills/skills/nature-paper2ppt .claude/skills/nature-paper2ppt
Restart Claude Code — the skill appears in the list; call it manually with /nature-paper2ppt. For all projects use ~/.claude/skills.
git clone --depth 1 --branch main https://github.com/Yuan1z0825/nature-skills.git /tmp/nature-skills mkdir -p .agents/skills cp -r /tmp/nature-skills/skills/nature-paper2ppt .agents/skills/nature-paper2ppt
Codex looks for skills in .agents/skills from the current folder up to the repo root; call one with /skills or $nature-paper2ppt. For all projects use ~/.agents/skills.
git clone --depth 1 --branch main https://github.com/Yuan1z0825/nature-skills.git /tmp/nature-skills mkdir -p .cursor/skills cp -r /tmp/nature-skills/skills/nature-paper2ppt .cursor/skills/nature-paper2ppt
Cursor picks the skill up on start; call it with “/” in Agent chat. Cursor also reads .claude/skills and .agents/skills. For all projects use ~/.cursor/skills.
git clone --depth 1 --branch main https://github.com/Yuan1z0825/nature-skills.git /tmp/nature-skills mkdir -p .gemini/skills cp -r /tmp/nature-skills/skills/nature-paper2ppt .gemini/skills/nature-paper2ppt
Gemini CLI offers to activate the skill when a task matches — you approve it. For all projects use ~/.gemini/skills.
Read SKILL.md and any companion files before deciding whether to install. Click a file to preview it.
SKILL.md contents
Original author text · read-onlyPaper-to-PPTX — Router
This skill is split into two layers:
- A static layer under
static/that holds versioned, reusable content fragments (core principles, toolchain policy, the 9-step workflow, output/quality rules, and per-paper-type presentation arcs). - A dynamic layer (this file plus
manifest.yaml) that detects the paper type and loads only the fragments needed for the current job. Deep design, figure, and self-review material lives in on-demand references.
Do not try to apply the deck-building logic from memory or from this router. Always load fragments from disk as described below.
Routing protocol
Follow these five steps every time the skill is invoked.
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:
1. Core principles (core/principles.md) — the argument is the spine; lean operating mode; accepted inputs; Chinese-by-default language rule.
2. Toolchain policy and fast path (core/toolchain.md) — cross-platform Python-first stack, default fast path.
3. Paper-type arc (the loaded paper_type fragment) — narrative order and slide structure for this paper.
4. Workflow (core/workflow.md) — run the 9 steps end to end.
5. 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.
The end product is a real .pptx deck, not 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.
Why this split
- The static layer is versioned and reviewable. Adding a new paper-type arc is one new fragment plus one manifest line.
- The dynamic layer keeps each invocation cheap: only the arc for this paper enters context up front; heavy design and QA material loads only when that step runs.
- The router itself is short on purpose. Update fragments, not this file, when adding scope.
- This structure mirrors
nature-writing,nature-polishing, andnature-readerso shared content lives innature-shared/.
Frequently asked questions
What does the nature-paper2ppt skill do?
Automatically generates Nature-style presentations from scientific papers, PDFs, or notes. Structures content, selects figures, and writes slide text and speaker notes in Chinese.
How do I install nature-paper2ppt?
Open the “Installation” block on this page and pick your agent — Claude Code, Codex, Cursor or Gemini CLI — for ready-made commands that copy the skill folder to the right place. Or copy the prompt from the “Via assistant” tab and let the assistant review and install the skill.
Which AI models work with nature-paper2ppt?
Skills are plain Markdown instructions (the Agent Skills format), so nature-paper2ppt works with any agent that reads SKILL.md: Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and more. The model loads the instructions only when a task matches the skill's description.
Is nature-paper2ppt free?
The skill is published openly by Yuan1z0825 under the Apache-2.0 license. The skill itself costs nothing — you only pay your AI provider for the tokens you use.
Is it safe to install skills?
A skill is a set of instructions your agent will follow, so read SKILL.md and its companion files before installing. Scripts in the skill folder only run if your agent runs them — keep an eye on what it does and do not grant unnecessary permissions.
How is a skill different from an MCP server or a plugin?
An MCP server or plugin gives the model new tools — code that runs and returns a result. A skill gives it knowledge and process: how to approach a task, which steps to follow and what good output looks like. It needs no server or API key.