experiment-status

Check status of running autonomous experiment loops

View SKILL.md on GitHub Repository

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Install this agent skill to your Project

npx add-skill https://github.com/Xiangyue-Zhang/auto-deep-researcher-24x7/tree/main/skills/experiment-status

SKILL.md

/experiment-status

Check the current status of your autonomous experiment agent.

Usage

/experiment-status
/experiment-status --project /path/to/project

Behavior

Read PROJECT_BRIEF.md — show the research goal
Read MEMORY_LOG.md — show key results and recent decisions
Read .cycle_counter — show how many cycles completed
Check for running training processes (via PID files or pgrep)
If training is running, tail the log file for latest output
Show GPU utilization for the project's GPUs
Check if HUMAN_DIRECTIVE.md exists (pending directive)

Output Format

markdown

# Experiment Status — my-project

## Goal
Train ViT-B/16 on ImageNet to 78%+ accuracy

## Progress
- Cycles completed: 4
- Current best: 78.3% (Exp004, ViT-B/16 + cosine + mixup)
- Status: TRAINING (PID 12345, GPU 0, running 3.2h)

## Latest Training Log
Epoch 45/90 | loss: 2.134 | acc: 77.1% | lr: 1.2e-4

## Recent Decisions
1. [04-08 14:45] Target reached with mixup, trying stronger augmentation
2. [04-08 06:00] Cosine schedule helped, adding regularization

## Pending Directive
None (drop a file at workspace/HUMAN_DIRECTIVE.md to intervene)

Maintainer

Xiangyue-Zhang Core maintainer

Source details

Full Name: Xiangyue-Zhang/auto-deep-researcher-24x7
Branch: main
Path in repo: skills/experiment-status
License: Apache License 2.0
Topics: claude-code ai-agent machine-learning mlops autonomous-agent llm-agent deep-learning gpu pytorch research-automation experiment-automation hyperparameter-tuning