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 hr98w · Agent Tool · ★ 163
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Jev Visual English · 简体中文 A small, runnable project for learning vision-language model inference on Apple Silicon. Use Qwen3.5-0.8B with MLX to answer multiple questions about one image: choose an option, judge yes/no, or score ordered levels. Includes a local browser UI, CLI and HTTP API. This project explores a Jev-like inference pattern for open multimodal language models. It avoids autoregressive structured generation by reusing shared multimodal context and directly scoring candidate outputs from model logits. This is an independent community implementation and does not claim to reproduce TypeSafe Jev's proprietary model architecture, RLCD training, calibration, or serving system. Visual game demos AI sorting factory https://github.com/user-attachments/assets/c87c09d8-30d2-4392-b981-d0b5cf1879ae The factory classifies screenshots of objects on a moving conveyor and selects a sorting lane. The sidebar shows the actual input and candidate probabilities. Breakout https://github.com/user-attachments/assets/a642a6d6-c138-4c02-8378-f2981be22aad Breakout exposes the limits of Qwen3.5-0.8B-4bit in our non-thinking, direct-scoring setup.
| Stars | 163 |
| Forks | 21 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 65.1363546339495/100 |
| Last Updated | 2026-09-18 |
| Created | 2026-09-17 |
| Platforms | python |
| Est. Tokens | ~14k |
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jev-visual is An educational Jev-like visual inference experiment on Apple Silicon: shared context, direct candidate scoring, and local visual demos.. It is categorized as a Agent Tool with 163 GitHub stars.
jev-visual is primarily written in Python.
You can find installation instructions and usage details in the jev-visual GitHub repository at github.com/hr98w/jev-visual. The project has 163 stars and 21 forks, indicating an active community.
jev-visual is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to jev-visual on Agent Skills Hub include claude-plugins, tutor-skills, repren. 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: