by xdmlxdml · Codex Skill · ★ 180
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is beamer2pptx safe to install? View the security audit →
beamer2pptx Left: the original Beamer PDF. Right: the converted PPTX opened in Microsoft PowerPoint, shown without retouching. Fidelity varies by document, but the objects are always real, not a picture of the page. An agent Skill that rebuilds a Beamer PDF as an editable PowerPoint deck: real text boxes, shapes and native equations, not a screenshot of each slide pasted into a wrapper. The compiled PDF is the reference for layout; verified LaTeX supplies the math. Use it to revise a LaTeX presentation in PowerPoint: update wording, move slide elements, or fix an equation without rebuilding the deck from source. What you can expect Editable characters where extraction permits, with reduc
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 →
| Stars | 180 |
| Forks | 8 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 60.296058887572/100 |
| Open Issues | 1 |
| Last Updated | 2026-09-11 |
| Created | 2026-08-28 |
| Platforms | codex, python |
| Est. Tokens | ~14k |
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beamer2pptx is A Codex Skill for converting Beamer PDFs into editable PowerPoint decks with native equations.. It is categorized as a Codex Skill with 180 GitHub stars.
beamer2pptx is primarily written in Python.
You can find installation instructions and usage details in the beamer2pptx GitHub repository at github.com/xdmlxdml/beamer2pptx. The project has 180 stars and 8 forks, indicating an active community.
beamer2pptx is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to beamer2pptx on Agent Skills Hub include ai-maestro, upskill, 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: