Agent Monitor
by @openlark
Agent work status monitoring and automatic activation system. Triggers when monitoring subagent runtime status, detecting prolonged unresponsive "stalled" st...
clawhub install agent-monitorπ About This Skill
name: agent-monitor description: Agent work status monitoring and automatic activation system. Triggers when monitoring subagent runtime status, detecting prolonged unresponsive "stalled" states, and automatically activating them to resume operation. Suitable for long-running task monitoring, automated operations, agent health checks, and similar scenarios.
Agent Monitor - Agent Work Status Monitoring
Overview
This skill provides subagent work status monitoring and automatic activation capabilities:
1. Status Monitoring - Real-time monitoring of agent runtime status 2. Stall Detection - Detecting "stalled" states where an agent has been unresponsive for over 5 minutes 3. Automatic Activation - Automatically sending activation messages to resume agent operation
Core Capabilities
1. Monitor Agent Status
Use the subagents tool to obtain a list of currently running agents:
# List recently running agents
subagents(action="list", recentMinutes=30)
2. Detect Stalled Status
Detection logic:
3. Automatically Activate Agents
Use the steer action of the subagents tool to send an activation message:
# Send an activation message to a specified agent
subagents(action="steer", target="", message="Continue working")
Workflow
βββββββββββββββββββββββ
β Get Agent List β
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βΌ
βββββββββββββββββββββββ
β Check Each Agent's β
β Last Activity Time β
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βΌ
ββββββββββ
β >5min? βββNoβββ
ββββββ¬ββββ β
Yesβ β
βΌ β
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β Determine as ββ
β Stalled Status ββ
ββββββββββββ¬ββββββββββββ
βΌ β
ββββββββββββββββββββββββ
β Send Activation ββ
β Message to Resume ββ
ββββββββββββββββββββββββ
β β
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βΌ
βββββββββββββββββββ
β Continue Monitoringβ
βββββββββββββββββββ
Usage Examples
Example 1: Monitor All Agents
# 1. Get agent list
result = subagents(action="list", recentMinutes=30)2. Check each agent's status
for agent in result.agents:
idle_time = calculate_idle_time(agent.lastActivity)
if idle_time > 300: # Over 5 minutes
# 3. Automatically activate
subagents(action="steer", target=agent.id, message="Please continue executing the task")
Example 2: Monitor a Specific Agent
# Monitor an agent with a specified ID
agent_id = "builder-agent-001"
result = subagents(action="list", recentMinutes=10)Find the target agent
for agent in result.agents:
if agent.id == agent_id:
if is_stalled(agent, threshold=300):
activate_agent(agent_id)
Script Tool
monitor_agents.py
Located at scripts/monitor_agents.py, provides complete monitoring functionality:
# Monitor and automatically activate stalled agents
python scripts/monitor_agents.py --threshold 300 --auto-activateDetect only, without automatic activation
python scripts/monitor_agents.py --threshold 300 --dry-runMonitor a specific agent
python scripts/monitor_agents.py --target agent-id-001
Parameter descriptions:
--threshold: Stall determination threshold (seconds), default 300 (5 minutes)--auto-activate: Automatically activate stalled agents--dry-run: Detect only, do not execute activation--target: Specify a specific agent ID to monitorIntegration into Scheduled Tasks
The monitoring script can be integrated into cron scheduled tasks for continuous monitoring:
# Check every 2 minutes
*/2 * * * * python /path/to/monitor_agents.py --auto-activate
Notes
1. Threshold Setting: Adjust the stall determination threshold based on the task type; complex tasks may require longer thresholds 2. Activation Message: Activation messages sent should be concise and clear, prompting the agent to continue working 3. Avoid False Activation: Ensure the agent is genuinely stalled before activating to avoid interfering with normal thought processes 4. Logging: It is recommended to log each detection and activation operation for subsequent analysis
π Tips & Best Practices
1. Threshold Setting: Adjust the stall determination threshold based on the task type; complex tasks may require longer thresholds 2. Activation Message: Activation messages sent should be concise and clear, prompting the agent to continue working 3. Avoid False Activation: Ensure the agent is genuinely stalled before activating to avoid interfering with normal thought processes 4. Logging: It is recommended to log each detection and activation operation for subsequent analysis