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 firecrawl · Agent Tool · ★ 2.6k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is open-agent-builder safe to install? View the security audit →
Open Agent Builder Build, test, and deploy AI agent workflows with a visual no-code interface Documentation • Examples What is Open Agent Builder? Open Agent Builder is a visual workflow builder for creating AI agent pipelines powered by Firecrawl. Design complex agent workflows with a drag-and-drop interface, then execute them with real-time streaming updates. Perfect for: Web scraping and data extraction workflows Multi-step AI agent pipelines Automated research and content generation Data transformation and analysis Web automation with human-in-the-loop approvals Note: This project is actively under development. Some features are still in progress and we welcome contributions and PRs! Key Features Visual Workflow Builder Drag-and-drop interface for building agent workflows Real-time execution with streaming updates 8 core node types: Start, Agent, MCP Tools, Transform,
| Stars | 2,635 |
| Forks | 508 |
| Language | TypeScript |
| Category | Agent Tool |
| Quality Score | 73.7902019559729/100 |
| Open Issues | 16 |
| Last Updated | 2025-10-20 |
| Created | 2025-10-16 |
| Platforms | browser, node |
| Est. Tokens | ~17k |
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open-agent-builder is 🔥 Visual workflow builder for AI agents powered by Firecrawl - drag-and-drop web scraping pipelines with real-time execution. It is categorized as a Agent Tool with 2.6k GitHub stars.
open-agent-builder is primarily written in TypeScript.
You can find installation instructions and usage details in the open-agent-builder GitHub repository at github.com/firecrawl/open-agent-builder. The project has 2.6k stars and 508 forks, indicating an active community.
The top alternatives to open-agent-builder on Agent Skills Hub include notebooklm-skill, agent-skills, excalidraw-diagram-skill. 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: