/experiment-status
Check status of running autonomous experiment loops
$ npx -y skills add Xiangyue-Zhang/auto-deep-researcher-24x7 --skill experiment-status --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/experiment-status
Context preview
The summary Claude sees to decide when to auto-load this skill.
Check status of running autonomous experiment loops
SKILL.md
experiment-status.SKILL.mdname: experiment-status
description: "Check status of running autonomous experiment loops"
experiment-status
Check the current status of your autonomous experiment agent.
Usage
Claude Code: /experiment-status
Claude Code: /experiment-status --project /path/to/project
Codex: $experiment-status
Behavior
1. Read `PROJECT_BRIEF.md` — show the research goal 2. Read `MEMORY_LOG.md` — show key results and recent decisions 3. Read `.cycle_counter` — show how many cycles completed 4. Check for running training processes via the configured execution backend 5. If training is running, tail the log file for latest output 6. Show GPU utilization through the configured backend 7. Check if `HUMAN_DIRECTIVE.md` exists (pending directive)
If `execution.mode=ssh`, controller state still comes from the local project directory, but PID checks, training logs, and GPU status come from the configured remote host.
Output Format
# 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)
Read more
name: experiment-status description: "Check status of running autonomous experiment loops"
experiment-status
Check the current status of your autonomous experiment agent.
Usage
Claude Code: /experiment-status Claude Code: /experiment-status --project /path/to/project Codex: $experiment-status
Behavior
1. Read `PROJECT_BRIEF.md` — show the research goal 2. Read `MEMORY_LOG.md` — show key results and recent decisions 3. Read `.cycle_counter` — show how many cycles completed 4. Check for running training processes via the configured execution backend 5. If training is running, tail the log file for latest output 6. Show GPU utilization through the configured backend 7. Check if `HUMAN_DIRECTIVE.md` exists (pending directive)
If `execution.mode=ssh`, controller state still comes from the local project directory, but PID checks, training logs, and GPU status come from the configured remote host.
Output Format
# 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)
🔥 An autonomous AI agent that runs your deep learning experiments 24/7 while you sleep. Zero-cost monitoring, Leader-Worker architecture, constant-size memory.
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