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 shawn0728 · Agent Tool · ★ 264
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is OpenSearch-VL safe to install? View the security audit →
An Open Recipe for Frontier Multimodal Search Agents Cold-Start Agentic SFT · Multi-Turn Fatal-Aware GRPO · Visual Tool Use  using comman
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OpenSearch-VL is 🔍 OpenSearch-VL provides a fully open recipe for training strong multimodal deep search agents through high-quality data curation, diverse visual/search tools, and fatal-aware agentic reinforcement l. It is categorized as a Agent Tool with 264 GitHub stars.
OpenSearch-VL is primarily written in Python. It covers topics such as deep-research-agent, multimodal, opensource.
You can find installation instructions and usage details in the OpenSearch-VL GitHub repository at github.com/shawn0728/OpenSearch-VL. The project has 264 stars and 29 forks, indicating an active community.
OpenSearch-VL is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to OpenSearch-VL on Agent Skills Hub include LeanType, mcpcan, Agently-Daily-News-Collector. 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.
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