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 →
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make-slide 🎯 AI-powered presentation skill that generates stunning single-file HTML slide decks. AI 코딩 에이전트가 단일 HTML 파일로 고품질 프레젠테이션을 생성하는 범용 스킬. What is make-slide? make-slide is a skill (instruction set) for AI coding agents — like Claude Code, Gemini CLI, Codex, Cursor, and others — that enables them to generate professional presentation slides as a single HTML file. Instead of crafting designs from scratch every time (wasting tokens and producing inconsistent results), the AI references pre-built theme templates from this repository. The result is: Token-efficient — AI fetches a reference file instead of inventing layouts Consistent quality — every presentation follows a polished, tested design system Zero dependencies — output is one file you can open anywhere Think of it as a design system for AI-generated presentations. ✨ Features One file, no build step, no framework — j
| Stars | 132 |
| Forks | 20 |
| Language | HTML |
| Category | AI Skill |
| License | MIT |
| Quality Score | 67.0970498710427/100 |
| Last Updated | 2026-04-10 |
| Created | 2026-03-18 |
| Est. Tokens | ~18k |
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make-slide is Universal AI skill for generating standalone HTML slide decks. It is categorized as a AI Skill with 132 GitHub stars.
make-slide is primarily written in HTML.
You can find installation instructions and usage details in the make-slide GitHub repository at github.com/Kuneosu/make-slide. The project has 132 stars and 20 forks, indicating an active community.
make-slide is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to make-slide on Agent Skills Hub include claude-code-now, claude-bootstrap, branchlet. 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: