stall-tuner

Calibrate heartbeat intervals and stall thresholds in the Health Monitor harness.

Updated May 11, 2026

Search Tags:#automation #performance #latency #tuning #harness #health-monitor

Ready to run

npx skills add https://github.com/AesopScott/mojo --skill stall-tuner

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: stall-tuner
Source: https://github.com/AesopScott/mojo/tree/main/harnesses/skills/stall-tuner
Command: npx skills add https://github.com/AesopScott/mojo --skill stall-tuner

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill resolves performance bottlenecks and false-positive stall detections in the Health Monitor harness by providing a structured framework for calibrating heartbeat intervals and anomaly thresholds.

Core Features & Use Cases

Performance Calibration: Fine-tune heartbeat intervals and stall-detection thresholds to ensure system responsiveness.
Harness Optimization: Provides a systematic runbook for adjusting operational boundaries without manual inspection overhead.
Use Case: Use this when your system is incorrectly flagging healthy workers as stalled, or when you need to reduce latency in your health monitoring loop.

Quick Start

Use the stall-tuner skill to analyze the current Health Monitor performance and propose a configuration change to reduce false-positive stall detections.

Frequently Asked Questions about stall-tuner

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

FAQPage Schema

How do I reduce false-positive stall detections in a health monitor harness?▼

To reduce false-positive stall detections, you calibrate heartbeat intervals and anomaly thresholds to match operational boundaries. This structured tuning approach verifies control changes against current performance metrics to ensure healthy workers are not incorrectly flagged.

Why does my health monitoring loop have high latency during unattended sessions?▼

Health monitoring loop latency often stems from uncalibrated stall thresholds and anomaly windows. Adjusting these operational parameters systematically improves system throughput and responsiveness without requiring manual inspection overhead.

How to tune heartbeat intervals for better stall detection accuracy?▼

Tuning heartbeat intervals for stall detection accuracy requires analyzing current configuration files and performance metrics to define control changes. This calibration improves detection accuracy while maintaining system throughput in unattended sessions.

Do I need access to logs and metrics to calibrate health monitor performance parameters?▼

Yes, calibrating health monitor performance parameters requires access to current configuration files, logs, and performance metrics. These inputs are necessary to define and verify control changes for heartbeat intervals and stall thresholds.

What is the best way to optimize health monitor performance without manual inspection?▼

The best way to optimize health monitor performance without manual inspection is applying a systematic runbook for adjusting operational boundaries. This framework provides structured calibration of heartbeat intervals and anomaly thresholds to resolve bottlenecks.