From vastai-pack
Collects Vast.ai diagnostic bundle: account balance, instance status/logs/details, remote GPU checks via SSH/nvidia-smi. For troubleshooting GPU rentals and support tickets.
How this skill is triggered — by the user, by Claude, or both
Slash command
/vastai-pack:vastai-debug-bundleThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
!`vastai --version 2>/dev/null || echo 'vastai CLI not installed'`
!vastai --version 2>/dev/null || echo 'vastai CLI not installed'
!python3 --version 2>/dev/null || echo 'Python not available'
Collect comprehensive diagnostic information for Vast.ai GPU instance issues. Covers account verification, instance inspection, log collection, GPU diagnostics, and network testing.
#!/bin/bash
set -euo pipefail
echo "=== Vast.ai Debug Bundle ==="
echo "Timestamp: $(date -u +%Y-%m-%dT%H:%M:%SZ)"
echo -e "\n--- Account Info ---"
vastai show user --raw | python3 -c "
import sys, json
u = json.load(sys.stdin)
print(f'Username: {u.get(\"username\", \"?\")}')
print(f'Balance: \${u.get(\"balance\", 0):.2f}')
print(f'API Key (first 8): {u.get(\"api_key\", \"?\")[:8]}...')
"
echo -e "\n--- All Instances ---"
vastai show instances --raw | python3 -c "
import sys, json
instances = json.load(sys.stdin)
for i in instances:
print(f'ID: {i[\"id\"]} | Status: {i.get(\"actual_status\", \"?\")} | '
f'GPU: {i.get(\"gpu_name\", \"?\")} | '
f'\$/hr: {i.get(\"dph_total\", 0):.3f} | '
f'SSH: {i.get(\"ssh_host\", \"?\")}:{i.get(\"ssh_port\", \"?\")}')
"
# Collect logs from a specific instance
INSTANCE_ID="${1:-}"
if [ -n "$INSTANCE_ID" ]; then
echo -e "\n--- Instance $INSTANCE_ID Logs ---"
vastai logs "$INSTANCE_ID" --tail 100 2>/dev/null || echo "No logs available"
echo -e "\n--- Instance $INSTANCE_ID Details ---"
vastai show instance "$INSTANCE_ID" --raw | python3 -c "
import sys, json
i = json.load(sys.stdin)
for key in ['actual_status', 'status_msg', 'gpu_name', 'gpu_ram',
'cuda_max_good', 'disk_space', 'ssh_host', 'ssh_port',
'image_uuid', 'onstart', 'reliability2']:
print(f'{key}: {i.get(key, \"?\")}')
"
fi
if [ -n "$SSH_HOST" ] && [ -n "$SSH_PORT" ]; then
echo -e "\n--- GPU Diagnostics (remote) ---"
ssh -p "$SSH_PORT" -o StrictHostKeyChecking=no "root@$SSH_HOST" << 'REMOTE'
nvidia-smi
echo "---"
nvidia-smi --query-gpu=name,memory.total,memory.used,temperature.gpu,utilization.gpu --format=csv
echo "---"
python3 -c "import torch; print(f'PyTorch CUDA: {torch.cuda.is_available()}, Device: {torch.cuda.get_device_name(0) if torch.cuda.is_available() else \"N/A\"}')" 2>/dev/null || echo "PyTorch not available"
echo "---"
df -h /workspace
free -h
REMOTE
fi
echo -e "\n--- API Connectivity ---"
curl -s -o /dev/null -w "HTTP %{http_code} in %{time_total}s" \
-H "Authorization: Bearer $VASTAI_API_KEY" \
"https://cloud.vast.ai/api/v0/users/current"
echo ""
| Issue | Diagnostic | Solution |
|---|---|---|
Instance shows error | Check status_msg in details | Destroy and reprovision on different host |
| SSH unreachable | Instance may still be loading | Wait for running status |
| GPU not detected | CUDA driver mismatch | Use image matching host CUDA version |
| Disk full | Check df -h /workspace | Increase disk or clean artifacts |
For rate limit handling, see vastai-rate-limits.
Quick debug: Run vastai show instance ID --raw | jq '{actual_status, status_msg, gpu_name, ssh_host, ssh_port}' for a one-line status summary.
Support ticket: Collect the full debug bundle output, include vastai logs ID, and attach nvidia-smi output from the instance.
5plugins reuse this skill
First indexed Jul 10, 2026
npx claudepluginhub luxdevnet/claude-plus-lux --plugin vastai-packCollects Vast.ai diagnostic evidence including account info, instance status, logs, and GPU diagnostics for support tickets and troubleshooting.
Guides collaborative design exploration before implementation: explores context, asks clarifying questions, proposes approaches, and writes a design doc for user approval.
Creates structured, bite-sized implementation plans from specs or requirements before writing code. Useful for breaking down multi-step tasks into testable steps with file structure and task boundaries.