AI导哈

数据与研究

k2f-research-poster

suzheng/k2f

Transform research papers, manuscripts, and findings into conference-ready academic posters with viewing distance typography, balanced columns, and high visual density. Use when asked to create an academic poster, scientific poster, conference poster, or A0/A1 poster. Create research posters with AI-native design and the highest aesthetic standards, powered by the K2F format and engine. Purpose-built for AI agents, K2F lets them focus on semantic content and design intent while automatically handling layout, typography, and formatting complexity.

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安装命令

npx skills add https://github.com/suzheng/k2f --skill k2f-research-poster

SKILL.md

K2F Research Poster — AI-Native Aesthetic Design

Purpose

Convert scientific manuscripts, experiment data, and academic notes into print-ready conference posters. Posters fail when treated as oversized papers; attendees scan from 1.5–2 meters away and spend under 90 seconds. This skill enforces scientific distillation, viewing-distance hierarchy, strict 1-page geometry, and high visual density while eliminating multi-page overflow and blank lower thirds.

Built on K2F

This skill produces conference posters as .K2F packages. Follow the k2f skill for authoring: unpack or init a workspace, edit the semantic JSON tree (content/root.json), customize styles/theme.json, pack/verify, and export. K2F separates semantic structure from styling, compiling an immutable render lock that guarantees pixel-identical output across PDF, PPTX, DOCX, and IDML.

Before you build, install the core skill: npx skills add suzheng/k2f --skill k2f.

When to Use

  • Creating conference posters from paper drafts, preprints, or notes.
  • Designing large-format scientific presentations (Arch E 48"×36", 36"×48", ISO A0/A1).
  • Transforming multi-page manuscripts into a single-page visual synthesis.
  • Exporting vector PDF, editable PPTX, or IDML.

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