by GoogleCloudPlatform · Agent Tool · ★ 123
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 123 |
| Forks | 28 |
| Language | Python |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 61/100 |
| Open Issues | 42 |
| Last Updated | 2026-07-10 |
| Created | 2025-02-11 |
| Platforms | python |
| Est. Tokens | ~367k |
Multi-Agent Quest Introduction Multi-Agent Quest (aka Agent Bar v2) is a robust multi-agent runtime designed to facilitate the orchestration, execution, and management of complex multi-agent systems. It provides the underlying infrastructure for agent communication, dynamic state management, tool integration, and industry-specific use cases.
Looking for a agentsmithy alternative? If you're comparing agentsmithy with other agent tool tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
This is the public release of MIRA OS. Discrete memories decay through momentum loss, tools auto-configure whe
Aser is a lightweight, self-assembling AI Agent frame.
An introduction to the world of AI Agents
Web app for teams of 20+ members. In-built connections to major LLMs via API. Share chats, prompts, and agents
A handy lib for smooth interaction with large language models (LLMs) and crafting AI apps.
The A2A x402 Extension brings cryptocurrency payments to the Agent-to-Agent (A2A) protocol, enabling agents to
Explore other popular agent tool tools:
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: