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 0xS4N4TG · Claude Skill · ★ 6
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is papercut-explainer safe to install? View the security audit →
Claude Code skills + a Remotion library for short vertical cut-paper explainer reels: strategy, hook, script, storyboard, voice, build, QA.
| Stars | 6 |
| Forks | 0 |
| Language | TypeScript |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 67.3884088260487/100 |
| Last Updated | 2026-10-13 |
| Created | 2026-10-13 |
| Platforms | claude-code, node |
| Est. Tokens | ~18k |
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papercut-explainer is Claude Code skills + a Remotion library for short vertical cut-paper explainer reels: strategy, hook, script, storyboard, voice, build, QA.. It is categorized as a Claude Skill with 6 GitHub stars.
papercut-explainer is primarily written in TypeScript. It covers topics such as agent-skills, claude-code, claude-code-skills.
You can find installation instructions and usage details in the papercut-explainer GitHub repository at github.com/0xS4N4TG/papercut-explainer. The project has 6 stars and 0 forks, indicating an active community.
papercut-explainer is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to papercut-explainer on Agent Skills Hub include youtube-marketing-skills, ComfyUI-Expert, dev-agent-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: