skills.rest
bert-berkers
bert-berkersCOMMUNITY
Explore all skills by this author →
GitHub

vitals

Monitor AI agent liveness, context budget, and recent failures via Python script.

Updated Aug 23, 2026
Search Tags:#debugging#monitoring#agent#health check#resource management#vitals
One-click install
npx skills add https://github.com/bert-berkers/UrbanRepML --skill vitals
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: vitals
Source: https://github.com/bert-berkers/UrbanRepML/tree/main/.claude/skills/vitals
Command: npx skills add https://github.com/bert-berkers/UrbanRepML --skill vitals

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires Bash, and includes scripts (resource) components.

What problem does it solve?

This Skill provides essential visibility into the operational status of the AI agent, including which agents are active, their remaining context budget, and any recent agent failures.

Core Features & Use Cases

  • Agent Status Monitoring: Track the "liveness" of all agents within the system.
  • Resource Management: Keep an eye on the context budget to prevent overload.
  • Error Tracking: Identify and review recent agent deaths or critical failures.
  • Use Case: For long-running autonomous operations, use /loop 5m /vitals to continuously monitor the system's health and be alerted to any issues.

Quick Start

Run the agent timer monitor and display results.

Frequently Asked Questions about vitals

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I monitor AI agent health and check liveness during continuous operation?▼

You can monitor AI agent health by running a Python script that tracks agent liveness, remaining context budget, and recent failures. This provides essential visibility into operational status during continuous autonomous operation.

What is the best way to track agent context budget and prevent overload?▼

Tracking agent context budget is handled by a monitoring script that displays remaining context limits for all active agents. This resource management approach keeps system health visible and helps prevent context overload.

Can I check recent agent failures and deaths automatically in a long-running loop?▼

Yes, you can check recent agent failures automatically by running the monitor within a continuous loop. Using a command like `/loop 5m /vitals` alerts you to agent deaths and critical issues every five minutes.

Do I need Bash to run agent liveness monitoring and display operational status?▼

Yes, Bash is required as a dependency to run the Python monitoring script. The script executes via Bash to calculate agent timers and display the current operational status of your system.

Why does an autonomous agent stop responding during long-running operations?▼

An autonomous agent may stop responding due to context budget exhaustion or critical failures. Monitoring liveness and tracking recent agent deaths diagnoses these issues by revealing which agents are inactive or have failed.

Does agent health monitoring work for diagnosing issues in continuous autonomous operations?▼

Yes, agent health monitoring is designed specifically for diagnosing issues during continuous autonomous operations. It displays liveness status and recent failures, making it essential for maintaining system health over long periods.

Related Skills

Explore More Software Engineering Skills→
bhutanobhutano
24

usage-bar

Install and configure a persistent Claude Code usage bar across platforms.

Community
Intermediate
dfpalhanodfpalhano

Daily Report

Generate automated daily, weekly, and end-of-day reports for AI agents.

Community
Intermediate
MarcelMichauMarcelMichau
1

aspire-monitoring

Capture and correlate logs, traces, metrics, and resource state for Aspire apps.

Community
Intermediate
chicanoandres702chicanoandres702

grafana-dashboards

Design and deploy production Grafana dashboards for system and application metrics.

Community
Advanced