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monitor-experiment

Monitor running experiments via SSH and collect JSON results.

1|Updated Mar 26, 2026
Search Tags:#logs#ssh#experiments#monitor#results#wandb#screen
One-click install
npx skills add https://github.com/Lingrongye/federated-learning --skill monitor-experiment-lingrongye
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: monitor-experiment
Source: https://github.com/Lingrongye/federated-learning/tree/main/Auto-claude-code-research-in-sleep/skills/monitor-experiment
Command: npx skills add https://github.com/Lingrongye/federated-learning --skill monitor-experiment-lingrongye

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Monitor running experiments, check progress, and collect results across SSH servers and research instances, simplifying status tracking and result gathering.

Core Features & Use Cases

  • Real-time progress checks across multiple sessions
  • Collect latest outputs, logs, and JSON results from experiments
  • Integrate with vast.ai or cloud instances to monitor long-running jobs and report status to users

Quick Start

Run a quick check on current experiments and fetch latest results from your monitored servers.

Frequently Asked Questions about monitor-experiment

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

FAQPage Schema
How do I check the progress of running experiments across multiple SSH servers?▼

Yes, you can monitor vast.ai instances by connecting to cloud servers via SSH, inspecting screen sessions, and reporting the status of long-running jobs to compile latest outputs and results.

How do I collect logs and JSON results from active screen sessions?▼

You collect logs and JSON results by identifying running experiments, accessing their active screen sessions over SSH, and compiling the current outputs and structured results from those instances.

Can I pull Weights & Biases metrics when monitoring experiments over SSH?▼

Yes, you can optionally pull Weights & Biases metrics if configured, allowing you to integrate experiment tracking data with logs and JSON results gathered from your SSH sessions.

Does this tool work with distributed setups on vast.ai instances?▼

Yes, you can monitor vast.ai instances by connecting to cloud servers via SSH, inspecting screen sessions, and reporting the status of long-running jobs to compile latest outputs and results.

What is the best way to track long-running jobs on remote research instances?▼

The best way to track long-running jobs is to monitor experiments across SSH servers, inspect screen sessions in real-time, and collect JSON results and logs to compile current statuses.

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