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minni-health-check

Detect stalled processes, stale lock files, model server outages, and database anomalies in the Minni consolidation pipeline.

2|Updated Mar 31, 2026
Search Tags:#diagnostics#alerting#consolidation#cron#health-check#pipeline-monitoring#minni
One-click install
npx skills add https://github.com/infektyd/minni --skill minni-health-check
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: minni-health-check
Source: https://github.com/infektyd/minni/tree/main/plugins/minni/skills/minni-health-check
Command: npx skills add https://github.com/infektyd/minni --skill minni-health-check

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The Minni consolidation pipeline can experience silent failures including stalled processes, stale lock files, unresponsive model servers, and database anomalies that disrupt AI agent memory operations, often only discovered after significant downtime or data loss. This skill automates proactive detection of these issues to prevent pipeline outages and ensure consistent memory consolidation.

Core Features & Use Cases

  • Rapid Health Scans: Run 1-minute checks that validate database statistics, model server availability, pipeline process status, and lock file freshness for routine monitoring.
  • Deep Diagnostics: Execute 5-minute full scans that analyze error logs, staging directory activity, detailed database metrics, and model server memory usage for in-depth troubleshooting.
  • Use Cases: Schedule hourly cron checks to catch issues early, run pre-consolidation verifications before triggering pipeline runs, diagnose stalled E4B consolidation or model server downtime, and track performance trends for capacity planning. Includes configurable alert thresholds and step-by-step troubleshooting guides for common failure scenarios.

Quick Start

Use the minni-health-check skill to run a full diagnostic of your Minni consolidation pipeline and identify any stalled processes, model server outages, or database issues requiring attention.

Frequently Asked Questions about minni-health-check

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

FAQPage Schema
How do I detect stalled processes and stale lock files in a consolidation pipeline?▼

Detect stalled processes and stale lock files in a consolidation pipeline by running automated health scans that validate process status and lock file freshness, preventing silent memory consolidation failures and data loss.

How do I troubleshoot model server outages and database anomalies for AI agent memory systems?▼

Troubleshoot model server outages and database anomalies for AI agent memory systems by executing deep diagnostic scans that analyze error logs, detailed database metrics, and model server memory usage to pinpoint failure modes.

Can I schedule automated cron health checks for pipeline monitoring?▼

You can schedule automated cron health checks for pipeline monitoring by configuring routine 1-minute rapid scans to validate database statistics, model server availability, and pipeline process status, catching issues early before downtime.

Does minni-health-check require external dependencies to run pre-consolidation verification?▼

Minni-health-check requires no external dependencies to run pre-consolidation verification, allowing you to validate pipeline readiness and identify potential outages before triggering consolidation runs.

What is the best way to diagnose a stalled E4B consolidation pipeline?▼

The best way to diagnose a stalled E4B consolidation pipeline is running full 5-minute deep diagnostics that analyze staging directory activity, error logs, and model server memory to generate structured JSON health reports with troubleshooting guidance.

Why does my AI agent memory consolidation silently fail and how do I prevent pipeline outages?▼

AI agent memory consolidation silently fails due to unresponsive model servers, stale lock files, or database anomalies. Prevent pipeline outages by applying configurable alert thresholds and proactive monitoring to detect issues before significant downtime.

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