/exp-status

Monitor experiment screen sessions and classify status as running, anomaly, or completed.

Updated May 23, 2026
One-click install
npx skills add https://github.com/duany049/multi-skill-orchestration --skill exp-status
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: /exp-status
Source: https://github.com/duany049/multi-skill-orchestration/tree/main/.claude/skills/exp-status
Command: npx skills add https://github.com/duany049/multi-skill-orchestration --skill exp-status

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It solves the problem of not knowing which experiments are still running, which ones have anomalies, and which ones have finished but still need collection, so you can confidently decide the next action.

Core Features & Use Cases

  • Live experiment status monitoring: Scans running experiments and checks local screen sessions or remote sessions to classify them as running, anomaly, or completed pending collect.
  • Optional auto-collection for finished runs: With --collect-ready, it automatically triggers /exp-run --collect for experiments whose sessions have ended but are not yet collected in the wiki.
  • Pipeline-aware reporting and advancement: With --pipeline <slug>, it reports pipeline progress and, with --auto-advance, advances to Stage 4 only when all pipeline experiments are completed.

Use case example: After a research pipeline runs for hours, use this skill to identify which experiments are stuck or crashed (anomalies) and which are done but not yet collected, then either collect them immediately or let the pipeline auto-advance when everything is complete.

Quick Start

Ask: Run /exp-status --collect-ready to automatically collect all completed experiments whose sessions have ended.

Frequently Asked Questions about /exp-status

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

FAQPage Schema
How do I monitor experiment pipeline status and detect anomalies in screen sessions?

Experiment pipeline monitoring scans local and remote screen sessions to classify running experiments, detect anomalies, and identify completed runs pending collection. It reads wiki experiment pages to perform non-blocking health checks and report pipeline progress.

What is the best way to collect results from completed experiments without blocking active runs?

Use the auto-collection feature with the collect-ready flag to trigger collection for finished runs. It automatically identifies experiments whose sessions have ended but are not yet collected in the wiki, invoking collection commands without interrupting active pipeline stages.

Can I automatically advance research pipeline stages when all experiments finish?

Yes, pipeline-aware reporting with the auto-advance flag advances to Stage 4 only when all pipeline experiments are completed. It checks the pipeline slug to ensure every experiment is finished before triggering coordinated research stage transitions.

Does experiment monitoring work with cron scheduling for periodic health checks?

Experiment monitoring applies to periodic cron-based status checks by classifying running, anomaly, or completed pending collect states. It performs non-blocking health checks during scheduled intervals to help you decide whether to collect results or advance research stages.

How does wiki automation update experiment pipeline progress after status checks?

Wiki automation updates pipeline progress by reading experiment pages, checking session health, and recording classified results. It synchronizes pipeline status in the wiki so you can confidently coordinate research stage transitions based on collected experiment outcomes.