monitor-experiment

Monitors running experiments and collects results via SSH, screen sessions, wandb workflows, and remote JSON retrieval.

Updated Apr 29, 2026
One-click install
npx skills add https://github.com/jkfee/Auto-Research --skill monitor-experiment-jkfee
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: monitor-experiment
Source: https://github.com/jkfee/Auto-Research/tree/main/skills/monitor-experiment
Command: npx skills add https://github.com/jkfee/Auto-Research --skill monitor-experiment-jkfee

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Monitor running experiments and collect results to track progress and outcomes.

Core Features & Use Cases

  • Real-time checks of active experiments across servers, cloud instances, and container environments
  • Centralized collection of outputs, logs, and final results for reporting
  • Use Case: When you run multiple experiments, you can monitor their status and pull summarized results for decision making

Quick Start

Start monitoring the active experiments on the target server and report status updates.

Frequently Asked Questions about monitor-experiment

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

FAQPage Schema
How do I monitor running experiments on a remote server via SSH?

To monitor running experiments via SSH, you can check the status of active processes within screen sessions on remote servers. This allows you to interrogate screen sessions directly to track experiment progress and gather real-time status updates from your terminal.

Can I extract wandb metrics from active experiments?

Yes, you can extract wandb metrics from active experiments. The skill applies wandb metric extraction to workflows, enabling you to pull summarized results and track progress outcomes directly from your wandb environments for decision making.

What is the best way to collect remote JSON results from cloud instances?

The best way to collect remote JSON results is to use a centralized monitoring approach that retrieves data from cloud instances and container environments. This enables remote JSON result retrieval and centralized collection of outputs for summary reporting.

Does this experiment monitoring approach work with modal apps and screen sessions?

Yes, this experiment monitoring approach works with modal apps and screen sessions. It is designed for remote servers, cloud instances, and container environments, allowing you to perform real-time checks across these different platforms.

How do I report experiment status updates across multiple container environments?

To report experiment status updates across multiple container environments, you can perform real-time checks and centralized collection of outputs. This gathers logs and final results, satisfying summary reporting requirements for tracking multiple experiments.