VA

vastai-debug-bundle

Bundles diagnostic info including instance status, logs, and account details for Vast.ai troubleshooting.

Install

mkdir -p .claude/skills/vastai-debug-bundle && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/5332" && unzip -o skill.zip -d .claude/skills/vastai-debug-bundle && rm skill.zip

Installs to .claude/skills/vastai-debug-bundle

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Collect Vast.ai debug evidence for support tickets and troubleshooting.
71 charsno explicit “when” trigger
Beginner

Key capabilities

  • Collect account information and balance status
  • List all instances with GPU details and SSH connectivity
  • Retrieve instance logs for troubleshooting
  • Perform remote GPU diagnostics including nvidia-smi
  • Verify API connectivity

How it works

It aggregates system-level logs, API status, and remote hardware metrics into a single diagnostic report. It uses SSH to execute commands on the instance to verify driver and memory health.

Inputs & outputs

You give it
Instance ID or API credentials
You get back
Structured diagnostic bundle including logs and GPU status

When to use vastai-debug-bundle

  • Preparing support tickets
  • Investigating GPU instance issues
  • Collecting logs for diagnostics

About this skill

Vast.ai Debug Bundle

Current State

!vastai --version 2>/dev/null || echo 'vastai CLI not installed' !python3 --version 2>/dev/null || echo 'Python not available'

Overview

Collect comprehensive diagnostic information for Vast.ai GPU instance issues. Covers account verification, instance inspection, log collection, GPU diagnostics, and network testing.

Prerequisites

  • Vast.ai CLI installed and authenticated
  • Access to the problematic instance (if still running)

Instructions

Step 1: Account and Auth Diagnostics

#!/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]}...')
"

Step 2: Instance Status Collection

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\", \"?\")}')
"

Step 3: Instance Log Collection

# 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

Step 4: Remote GPU Diagnostics (if SSH accessible)

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

Step 5: Network Diagnostics

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 ""

Output

  • Account info (username, balance, key prefix)
  • All instance statuses with GPU details
  • Instance logs (last 100 lines)
  • Remote GPU diagnostics (nvidia-smi, CUDA, disk, memory)
  • API connectivity test

Error Handling

IssueDiagnosticSolution
Instance shows errorCheck status_msg in detailsDestroy and reprovision on different host
SSH unreachableInstance may still be loadingWait for running status
GPU not detectedCUDA driver mismatchUse image matching host CUDA version
Disk fullCheck df -h /workspaceIncrease disk or clean artifacts

Resources

Next Steps

For rate limit handling, see vastai-rate-limits.

Examples

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.

When not to use it

  • Automated instance recovery without manual intervention

Prerequisites

Vast.ai CLI installed and authenticatedAccess to the problematic instance

Limitations

  • Instance must be running to collect remote GPU diagnostics
  • Requires SSH access to the instance

How it compares

This method automates the collection of disparate diagnostic data points into a single bundle, replacing manual inspection of individual logs and status commands.

Compared to similar skills

vastai-debug-bundle side by side with the closest alternatives in the catalog.

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vastai-debug-bundle (this skill)127dReviewBeginner
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python-repl64moReviewBeginner
n8n-validation-expert64moNo flagsIntermediate

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