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 crimeacs · Codex Skill · ★ 30
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is product-demo-director safe to install? View the security audit →
Turn product evidence and raw footage into narration-paced, source-bound demo films—with Codex or Claude Code directing cuts, zooms, render, and QA.
| Stars | 30 |
| Forks | 7 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 62.9633693243167/100 |
| Open Issues | 1 |
| Last Updated | 2026-09-27 |
| Created | 2026-07-23 |
| Platforms | claude-code, codex, gemini, python |
| Est. Tokens | ~19k |
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product-demo-director is Turn product evidence and raw footage into narration-paced, source-bound demo films—with Codex or Claude Code directing cuts, zooms, render, and QA.. It is categorized as a Codex Skill with 30 GitHub stars.
product-demo-director is primarily written in Python. It covers topics such as ai-agents, claude-code, codex.
You can find installation instructions and usage details in the product-demo-director GitHub repository at github.com/crimeacs/product-demo-director. The project has 30 stars and 7 forks, indicating an active community.
product-demo-director is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to product-demo-director on Agent Skills Hub include Monet, MarkuprPlus, mcp-video. 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: