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by avivsinai · Codex Skill · ★ 82
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Agent Message Queue (AMQ) A local, file-based interoperability bus for agent sessions and adapters. AMQ manages the conversation: agent-to-agent messaging, thread continuity, cross-session and cross-project routing, handoff state, and operational visibility. It does not try to own task decomposition, worktree management, dependency scheduling, or scheduler execution; Claude Code teams, Codex, Kanban, Symphony, and similar orchestrators stay one layer above it. Why AMQ? Modern AI-assisted development often involves multiple agents working on the same codebase. But without coordination: Agents duplicate work or create conflicts Reviews require human intermediation Context switching kills productivity AMQ gives agents a local interoperability bus: they can send messages, reply in threads, share status, and optionally consume adapter-emitted events through the same queue primitives. The core product stays intentionally small: file-based messages first, lightweight adapters second. Key Features Zero infrastructure — Pure file-
| Stars | 82 |
| Forks | 10 |
| Language | Go |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 73.8514347340042/100 |
| Open Issues | 2 |
| Last Updated | 2026-08-26 |
| Created | 2025-12-25 |
| Platforms | claude-code, cli, codex, go |
| Est. Tokens | ~18k |
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agent-message-queue is File-based message queue for local agent-to-agent communication (Maildir-style). It is categorized as a Codex Skill with 82 GitHub stars.
agent-message-queue is primarily written in Go. It covers topics such as agent-skills, agents, ai-agents.
You can find installation instructions and usage details in the agent-message-queue GitHub repository at github.com/avivsinai/agent-message-queue. The project has 82 stars and 10 forks, indicating an active community.
agent-message-queue is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to agent-message-queue on Agent Skills Hub include aiwg, AgenticGoKit, gob. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.