paper2slides

paper2slides is a skill for Claude Code, Codex from inhyeoklee/paper2slides-skill. It costs 28 tokens per session (4,992 once invoked), scanned A, original, MIT.

A skill that turns a scientific paper PDF into a presentation for a journal club, a meeting where researchers discuss and evaluate a published study. It creates Reveal.js slides with figures, captions, and speaker notes.

In plain words
What is it for?
Use it to extract and arrange figures from a paper, summarize its science, write slide titles and captions, and prepare a research presentation.
Why use it?
It combines figure extraction with an explanation of the paper, so the result is more useful than a deck that merely lists images. The presenter gets a structured talk and notes to guide discussion.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to extract and arrange figures from a paper, summarize its science, write slide titles and captions, and prepare a research presentation.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/inhyeoklee/paper2slides-skill/skill
Install

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.

Any agent
npx skills add inhyeoklee/paper2slides-skill --skill skill
Clone the repo
git clone --depth 1 https://github.com/inhyeoklee/paper2slides-skill

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for paper2slides

README.md
[![agentmods](https://agentmods.dev/badge/skills/inhyeoklee/paper2slides-skill/skill/github.svg)](https://agentmods.dev/skills/inhyeoklee/paper2slides-skill/skill)
Your own site
<a href="https://agentmods.dev/skills/inhyeoklee/paper2slides-skill/skill"><img src="https://agentmods.dev/badge/skills/inhyeoklee/paper2slides-skill/skill/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.

agentmods 80×15 button for paper2slides

Your own site · 80×15
<a href="https://agentmods.dev/skills/inhyeoklee/paper2slides-skill/skill"><img src="https://agentmods.dev/badge/skills/inhyeoklee/paper2slides-skill/skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 28 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,992 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00028 $0.04992
Opus 5.5 $0.00011 $0.01997
Sonnet 5.5 $0.00006 $0.00998
Haiku 4.5 $0.00003 $0.00499

Measured 1mo ago against content hash 1590a9a0f5b6, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

paper2slides 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 1mo 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.

skill/SKILL.md · 469 lines

How it starts

The opening of the file, as written. The whole thing — 469 lines — stays where its author put it; the contents beside it link to each section on GitHub.

paper2slides — Agent-Driven Journal Club Presentations

Overview

This skill transforms a scientific paper PDF into a show-ready, curated Reveal.js presentation with speaker notes. It combines two layers:

  1. Mechanical layer — the paper2slides Python library extracts figures, segments panels, and scaffolds a raw Reveal.js deck.
  2. Intelligence layer — you, the agent, read the paper, understand the science, curate the slide deck, write titles/captions, and compose speaker notes.

The mechanical extraction alone produces a figure dump. The agent's job is to turn that into a coherent, PhD-level journal club talk.


Prerequisites

The paper2slides library must be installed. If the library source is available locally:

cd <path_to_paper2slides_library> && pip install -e .

Otherwise install from the packaged distribution:

pip install paper2slides

Required Python packages (auto-installed): pymupdf, pillow, numpy, jinja2, click


Workflow (5 Phases)

Phase 1: Extract & Segment (Mechanical)

Run the paper2slides CLI to extract figures and segment panels:

paper2slides "<path/to/paper.pdf>" -o "<output_dir>"

This produces:

  • <output_dir>/assets/img/panels/fig1a.png, fig1b.png, ... — individual panel images
  • <output_dir>/index.html — a raw, uncurated Reveal.js deck (figure dump)
  • <output_dir>/assets/css/style.css — slate + accented theme with expanded font choices, high-contrast body text, per-aim color tokens, feature-family badge colors, and ready-made component classes for aim-flow / info-row-3 / taxonomy-grid / compare-grid / criteria-grid / badges / schematics

Verify: Check the terminal output for the number of figures and panels extracted. If zero figures found, the PDF may use vector graphics — consider alternatives like screenshots.

Phase 2: Read & Comprehend the Paper

Use PyMuPDF to extract and read the paper text programmatically:

import fitz
doc = fitz.open("<path/to/paper.pdf>")
for i in range(len(doc)):
    page = doc[i]
    text = page.get_text('text')
    print(f'=== PAGE {i+1} ===')
    print(text)
doc.close()

Read the full file on GitHub · 469 lines

Files

What ships with it

4 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.

Changes

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.

  1. 1mo ago First seen · 469 lines · 28 tokens per session scan A 1590a9a0f5b6

Subscribe to this mod's changes

paper2slides is a skill published in the GitHub repository inhyeoklee/paper2slides-skill (6 stars, last pushed 5mo ago), licensed MIT. It adds 28 tokens to every session and 4,992 once invoked, about $0.0001 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 2026-08-31.

Related

Other skills, from other repositories

academic-pdf-translation

A workflow for translating academic PDF papers and rebuilding them as readable, searchable PDFs in another language. It also checks page layout, figures, captions, and meaning.

ezra-y/academic-pdf-translation · 126 tokens

pydicom

Reads, inspects, writes, transforms, and preflights local DICOM datasets and pixel data. Applies to DICOM metadata, transfer syntaxes, compression plugins, frames, private elements, JSON, and bounded de-identification review.

K-Dense-AI/scientific-agent-skills · 52 tokens

pptx-posters

Creates and audits editable scientific posters in macro-free PowerPoint (.pptx) from author-approved local content and assets. Used when the requested deliverable is a PowerPoint research/conference poster and exact physical, printer, accessibility, provenance, and package-security checks are required.

K-Dense-AI/scientific-agent-skills · 59 tokens

nature-paper-trans

A workflow for translating selected pages or a complete English research-paper PDF into a simplified-Chinese, image-based PDF. bioRxiv is not mentioned in the provided details; the workflow applies to research-paper PDFs generally.

Yuan1z0825/nature-skills · 68 tokens

xberg-extracting-tables

Use when extracting tabular data from PDFs, spreadsheets, or images. Covers layout-aware table detection, table model selection, output formats (markdown / JSON cells), and known limits.

xberg-io/xberg · 36 tokens

extracting-lab-tables

Detects and extracts tabular laboratory panels from PDFs, scans, and images into structured rows ready for OpenMed and FHIR. Use when the user has a CBC, CMP, lipid panel, or other lab report as a scanned image / PDF / spreadsheet and needs the test name, value, unit, reference range, and abnormal flag as clean rows.…

maziyarpanahi/openmed · 210 tokens