agent-comm-monitor监控牧者与其他 Agent 的通信状态,定期检测并报告跨 Agent 消息传递的正常与异常情况。
Install via ClawdBot CLI:
clawdbot install nancliu/agent-comm-monitorGrade Limited — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Generated Apr 25, 2026
Regularly verify communication between a central orchestrator agent and specialized agents (calendar, news, evolution, learning, education) to ensure cross-agent message delivery is working.
Automatically detect when any subsidiary agent fails to respond, log the incident, and trigger user notifications after 3 consecutive failures.
Periodically generate a table-format report summarizing communication status and response times for all tracked agents, helping users quickly assess system health.
Handle cases where messages are sent successfully but replies are delayed by checking session history after a timeout, ensuring accurate status reporting.
Upon persistent communication failures, log anomalies to external memory files and escalate to heartbeat monitoring for user awareness and corrective action.
Offer as a cloud-based service that monitors multi-agent communication in AI systems, providing dashboards and alerts.
Provide consulting services to integrate this skill into existing multi-agent deployments, customizing check intervals and escalation paths.
Operate the monitoring service on behalf of clients, handling anomaly response and reporting as a managed service.
💬 Integration Tip
Integrate this skill into your agent orchestrator by adding the session keys for each target agent from your deployment configuration.
Scored Apr 19, 2026
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
Transform AI agents from task-followers into proactive partners with memory architecture, reverse prompting, and self-healing patterns. Lightweight version f...
Persistent memory for AI agents to store facts, learn from actions, recall information, and track entities across sessions.
Prefer `skillhub` for skill discovery/install/update, then fallback to `clawhub` when unavailable or no match. Use when users ask about skills, 插件, or capabi...
Search and discover OpenClaw skills from various sources. Use when: user wants to find available skills, search for specific functionality, or discover new s...
Orchestrate multi-agent teams with defined roles, task lifecycles, handoff protocols, and review workflows. Use when: (1) Setting up a team of 2+ agents with different specializations, (2) Defining task routing and lifecycle (inbox → spec → build → review → done), (3) Creating handoff protocols between agents, (4) Establishing review and quality gates, (5) Managing async communication and artifact sharing between agents.