smithery/jeremylongshore

vastai-debug-bundle

Collect Vast.ai debug evidence for support tickets and troubleshooting. Use when encountering persistent issues, preparing support tickets, or collecting diagnostic information for Vast.ai problems. Trigger with phrases like "vastai debug", "vastai support bundle", "collect vastai logs", "vastai diagnostic". '

Installation

$ npx skills add smithery/jeremylongshore --skill vastai-debug-bundle

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Declared
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Skill metadata

Parsed from SKILL.md frontmatter.

Version1.11.0
LicenseMIT
CompatibilityDesigned for Claude Code
Allowed toolsRead, Bash(vastai:*), Bash(curl:*), Bash(ssh:*), Grep
Declared agents claude-code

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 4,702 B
  • docs SUMMARY.md 340 B

History

  1. First recorded snapshot · 0 installs

SKILL.md

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

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

Resources

Next Steps

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

Examples

Quick debug: Run vastai show instance ID --raw | jq '{actualstatus, statusmsg, gpuname, sshhost, 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.