nature-paper2ppt

Yuan1z0825/nature-skills · Agent Skill

自動從科學論文、PDF或筆記中生成Nature風格的簡報。構建內容結構,選擇圖表,並用中文撰寫幻燈片文字和演講者備註。

前往安裝 ↓

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發布者Yuan1z0825社群
儲存庫Yuan1z0825/nature-skills ↗
技能資料夾nature-paper2ppt
星39,583
附帶檔案2
授權Apache-2.0
最近更新2026年8月2日
連結技能原始碼 ↗ · 儲存庫 ↗

Mozgi 檢查

我們在技能檔案中發現的內容。詳細資訊需訂閱。

安全性
低風險 · 未發現明顯風險 — 完整報告會顯示細節
相容性
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安裝

技能就是一個含 SKILL.md 的資料夾。選擇你的代理,在專案根目錄的終端機(macOS、Linux 或 Windows 的 Git Bash)執行指令。

把提示貼到 Claude、Codex 或其他助理:它會自行檢查並安裝技能。

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.

技能檔案

2 個檔案 下載 ZIP

安裝前請先檢視 SKILL.md 與相關檔案。點擊檔案即可預覽。

SKILL.md 內容

作者原文 · 唯讀

Paper-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, and nature-reader so shared content lives in nature-shared/.

常見問題

nature-paper2ppt 技能有什麼用途?

自動從科學論文、PDF或筆記中生成Nature風格的簡報。構建內容結構,選擇圖表,並用中文撰寫幻燈片文字和演講者備註。

如何安裝 nature-paper2ppt?

打開本頁的「安裝」區塊並選擇你的代理 — Claude Code、Codex、Cursor 或 Gemini CLI:那裡有把技能資料夾複製到正確位置的現成指令。也可以複製「透過助理」分頁中的提示,讓助理自行檢查並安裝技能。

nature-paper2ppt 適用哪些 AI 模型?

技能是純 Markdown 指示(Agent Skills 格式),因此 nature-paper2ppt 適用任何讀取 SKILL.md 的代理:Claude Code、Codex、Cursor、Gemini CLI、GitHub Copilot、OpenCode 等。只有在任務符合技能描述時,模型才會載入指示。

nature-paper2ppt 是免費的嗎?

此技能由 Yuan1z0825 公開發布,採用 Apache-2.0 授權。技能本身免費 — 你只需向 AI 供應商支付實際使用的 token 費用。

安裝技能安全嗎?

技能是代理會遵循的指示,安裝前請閱讀 SKILL.md 及相關檔案。技能資料夾中的腳本只有在代理執行時才會運行 — 留意它的動作,不要授予多餘權限。

技能和 MCP 伺服器或外掛有何不同?

MCP 伺服器或外掛為模型提供新工具 — 會執行並回傳結果的程式碼。技能提供的是知識與流程:如何處理任務、要遵循哪些步驟、好的成果長什麼樣子。它不需要伺服器或 API 金鑰。

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