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 →
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is jevmeter safe to install? View the security audit →
Every sentence scored. Every dodge flagged. Rendered as a 16:9 edit you can post. 🐣 New here? 3 steps, no coding 1. Install (macOS or Linux, needs Python 3.9+): 2. Paste your API key when the installer asks. Get one at console.typesafe.ai/keys. It's saved in your user settings, never in this folder, so it can't end up on GitHub. 3. Make a
| Stars | 72 |
| Forks | 5 |
| Language | Python |
| Category | AI Tool |
| License | MIT |
| Quality Score | 59.8530525099903/100 |
| Open Issues | 1 |
| Last Updated | 2026-09-17 |
| Created | 2026-09-17 |
| Platforms | python |
| Est. Tokens | ~16k |
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jevmeter is Put a live Jev (TypeSafe) meter on any video: every sentence scored, rendered as a 16:9 edit. It is categorized as a AI Tool with 72 GitHub stars.
jevmeter is primarily written in Python. It covers topics such as debate, jev, typesafe.
You can find installation instructions and usage details in the jevmeter GitHub repository at github.com/ChetasLua/jevmeter. The project has 72 stars and 5 forks, indicating an active community.
jevmeter is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to jevmeter on Agent Skills Hub include Sora-FullStack, pi-jev, awesome-jev. 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: