vizra-adk — security grade SAFE, quality 67/100

Security audit verdict: SAFE · quality 67/100

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 vizra-ai · Agent Tool · ★ 297

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

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About vizra-adk

Vizra ADK - AI Agent Development Kit for Laravel Build intelligent AI agents with Laravel's elegant syntax Vizra ADK is a comprehensive Laravel package for building autonomous AI agents that can reason, use tools, and maintain persistent memory. Create intelligent, interactive agents that integrate seamlessly with your Laravel application. ✨ Key Features 🤖 Multi-Model AI Support - Works with OpenAI, Anthropic, and Google Gemini + more, thanks to prism PHP 🎯 Sub-Agent Delegation - Ag

agent-frameworkaiai-agentsai-toolsanthropicautonomous-agentsgeminilaravellaravel-packagellm

Quick Facts

Stars297
Forks38
LanguagePHP
CategoryAgent Tool
LicenseMIT
Quality Score67.2500578351073/100
Last Updated2026-08-24
Created2025-05-31
Platformsgemini
Est. Tokens~18k

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Frequently Asked Questions

What is vizra-adk?

vizra-adk is Build, test, and deploy intelligent AI agents the Laravel way. It is categorized as a Agent Tool with 297 GitHub stars.

What programming language is vizra-adk written in?

vizra-adk is primarily written in PHP. It covers topics such as agent-framework, ai, ai-agents.

How do I install or use vizra-adk?

You can find installation instructions and usage details in the vizra-adk GitHub repository at github.com/vizra-ai/vizra-adk. The project has 297 stars and 38 forks, indicating an active community.

What license does vizra-adk use?

vizra-adk is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to vizra-adk?

The top alternatives to vizra-adk on Agent Skills Hub include sre, pydantic-ai-todo, tools. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

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:

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