No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by zsyggg · Claude Skill · ★ 998
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is paper-craft-skills safe to install? View the security audit →
paper-craft-skills English | 中文 Turn academic papers into polished method figures and in-depth articles — zero config, one command. From arxiv link to publication-ready visuals and deep-dive articles. Drop a paper, pick a style, get output that looks like a human expert made it. How to install Copy this into Codex or Claude Code: That's it. The agent handles clone, symlink, and registration. No API keys. No accounts. If you prefer a terminal: Works with: Codex · Claude Code · Cursor · Windsurf What's inside 🎨 paper-comic Paper → Method Figures Transformer architecture — generated from Attention Is All You Need Reads your paper → proposes what to draw → you confirm → generates. Bright, warm hand-
| Stars | 998 |
| Forks | 63 |
| Language | Python |
| Category | Claude Skill |
| Quality Score | 69.9005151986075/100 |
| Open Issues | 5 |
| Last Updated | 2026-05-29 |
| Created | 2026-01-23 |
| Platforms | claude-code, python |
| Est. Tokens | ~3224k |
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paper-craft-skills is Claude Code skills for academic papers: deep analysis, comics, summaries | 论文工艺：深度解读、漫画生成、速览总结. It is categorized as a Claude Skill with 998 GitHub stars.
paper-craft-skills is primarily written in Python. It covers topics such as academic, ai-tools, arxiv.
You can find installation instructions and usage details in the paper-craft-skills GitHub repository at github.com/zsyggg/paper-craft-skills. The project has 998 stars and 63 forks, indicating an active community.
The top alternatives to paper-craft-skills on Agent Skills Hub include phd-skills, claude-prism, research-units-pipeline-skills. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: