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 mikelix · Claude Skill · ★ 0
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is gstack-tutorial-5-agi-race-v2 safe to install? View the security audit →
gstack Tutorial #5: from YouTube analytics to a re-engineered Short with CSR-RAP, Claude Opus 5.5 and HyperFrames (EN/ZH)
| Stars | 0 |
| Forks | 0 |
| Language | JavaScript |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 60.2806942747245/100 |
| Last Updated | 2026-09-29 |
| Created | 2026-09-29 |
| Platforms | claude-code, node |
| Est. Tokens | ~13k |
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gstack-tutorial-5-agi-race-v2 is gstack Tutorial #5: from YouTube analytics to a re-engineered Short with CSR-RAP, Claude Opus 5.5 and HyperFrames (EN/ZH). It is categorized as a Claude Skill with 0 GitHub stars.
gstack-tutorial-5-agi-race-v2 is primarily written in JavaScript. It covers topics such as claude-code, csr-rap, gstack.
You can find installation instructions and usage details in the gstack-tutorial-5-agi-race-v2 GitHub repository at github.com/mikelix/gstack-tutorial-5-agi-race-v2. The project has 0 stars and 0 forks, indicating an active community.
gstack-tutorial-5-agi-race-v2 is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to gstack-tutorial-5-agi-race-v2 on Agent Skills Hub include mcp-video, gstack-game, youtube-marketing-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: