by monid-ai · Agent Tool · ★ 5.8k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
git clone https://github.com/monid-ai/monid.gitTaken from the project's README on GitHub. Check the security audit before running it.
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. Full audit →
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 | 5,767 |
| Forks | 704 |
| Language | TypeScript |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 69/100 |
| Open Issues | 114 |
| Last Updated | 2026-10-22 |
| Created | 2026-08-26 |
| Platforms | node |
| Est. Tokens | ~16k |
monid.ai · Docs · Tool catalog · Quickstart · Development guide Monid (OpenRouter for agent tools) OpenRouter, but for agent tools.
These tools work well together with monid for enhanced workflows:
Looking for a monid alternative? If you're comparing monid 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.
Semi-automated research assistant for academic research and software development. Supports Claude Code, Codex
Klavis AI: MCP integration platforms that let AI agents use tools reliably at any scale
ACI.dev is the open source tool-calling platform that hooks up 600+ tools into any agentic IDE or custom AI ag
everything-claude-code 中文翻译项目：完整的 Claude Code 配置集合（agents, skills, hooks, commands, rules, MCPs）。源自 Anthropic
AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with M
Trigger.dev – build and deploy durable AI agents and workflows
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: