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 bfly123 · Codex Skill · ★ 2.4k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is claude_code_bridge safe to install? View the security audit →
Claude Code Bridge (ccb) v5.2.6 Multi-Model Collaboration via Split-Pane Terminal Claude · Codex · Gemini · OpenCode · Droid Lightweight async messaging — full CLI power, every interaction visible []() []() English | Chinese Demo animations Introduction: Multi-model collaboration avoids model bias, cognitive blind spots, and context limits. Unlike
| Stars | 2,380 |
| Forks | 228 |
| Language | Python |
| Category | Codex Skill |
| Quality Score | 61.1345081880163/100 |
| Open Issues | 67 |
| Last Updated | 2026-04-28 |
| Created | 2025-10-25 |
| Platforms | claude-code, cli, codex, gemini, python |
| Est. Tokens | ~1302k |
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claude_code_bridge is Real-time multi-AI collaboration: Claude, Codex & Gemini with persistent context, minimal token overhead. It is categorized as a Codex Skill with 2.4k GitHub stars.
claude_code_bridge is primarily written in Python. It covers topics such as ai-collaboration, ai-tools, claude-code.
You can find installation instructions and usage details in the claude_code_bridge GitHub repository at github.com/bfly123/claude_code_bridge. The project has 2.4k stars and 228 forks, indicating an active community.
The top alternatives to claude_code_bridge on Agent Skills Hub include agent-of-empires, hcom, emdash. 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: