Agent skill · Data & Analytics

research-presentation

Create, revise, and quality-check source-grounded research presentations from papers, research notes, data, or manuscripts. Use for paper-to-slides, research presentation, scientific presentation, journal club, lab meeting, conference talk, seminar, thesis defense, dissertation defense, PPT/PPTX, 学术PPT, 科研汇报, 论文汇报, 组会汇报, 答辩PPT, and related slide-deck tasks.

Yila-AIgithub.com/Yila-AIGitHub ↗
claude-codecodexships scriptsApache-2.0
Install
npx skills add Yila-AI/sci-ssci-skills --skill research-presentation --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 11
SKILL.md size: 10 KB
Bundled scripts: yes
Path: skills/research-presentation/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 78
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Research Presentation Turn a paper or research corpus into a presentation that an audience can follow, verify, and discuss. The core promise is **paper to slides without losing the evidence**: preserve source meaning, choose a cumulative narrative, make figures legible, keep claims bounded, and deliver an editable deck with notes and a rendered QA trail. This Skill owns the workflow from source inspection through final slide QA. It does not replace the author's scientific judgment, invent results, or silently strengthen a claim. ## Route the request Choose the narrowest route that satisfies the request: | Input / request | Route | |---|---| | One or more PDFs, papers, or manuscripts | Full paper-to-slides workflow below; read `references/paper-extraction.md` first | | Research notes, tables, figures, or a protocol | Evidence-led presentation workflow; mark unsupported fields instead of filling them | | Existing PPTX to revise | Inspect the source deck, preserve its visual contract when requested, then run the same render/QA loop | | A presentation brief with no source document | Skip extraction, but still create a claim ledger, narrative outline, source/asset notes, and visual QA

What's inside
Steps it walks through
  1. Route the request
  2. Non-negotiable contracts
  3. Paper-to-Slides workflow
  4. 1. Inventory and extract
  5. 2. Choose the talk contract
  6. 3. Build the ghost deck
  7. 4. Select the visual system and layouts
  8. 5. Build the editable deck
  9. 6. Render and audit
  10. Output contract
  11. Bundled resources
Ships with 10 files
  • NOTICE
  • agents/openai.yaml
  • references/layouts.md
  • references/narrative-planning.md
  • references/paper-extraction.md
  • references/qa-contract.md
  • references/rendering.md
  • references/themes.md
  • scripts/audit_pptx.py
  • scripts/render_slides.py
Commands it runs
python scripts/render_slides.py deck.pptx --outdir rendered
python scripts/audit_pptx.py deck.pptx --rendered rendered --report qa-report.json
More from sci-ssci-skills
All skills →
About this skill
What does the research-presentation skill do?

Create, revise, and quality-check source-grounded research presentations from papers, research notes, data, or manuscripts. Use for paper-to-slides, research presentation, scientific presentation, journal club, lab meeting, conference talk, seminar, thesis defense, dissertation defense, PPT/PPTX, 学术PPT, 科研汇报, 论文汇报, 组会汇报, 答辩PPT, and related slide-deck tasks.

How do I install it?

Run `npx skills add Yila-AI/sci-ssci-skills --skill research-presentation --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From Yila-AI/sci-ssci-skills, a repository with 78 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going