health-probe — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited health-probe (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Triggers: "health", "probe", "is everything ok", "check stack", "gateway health", "arifos health", "container health", "is arifos sick", "system status"
curl -sf http://arifosmcp:8080/health | jq '{status, tools_loaded, version, uptime}'Expected: status: "healthy", tools_loaded: 13 Alert if: tools_loaded < 13 or status != "healthy"
curl -sf http://localhost:18789/ | head -c 200 2>/dev/null && echo "GATEWAY_UP" || echo "GATEWAY_UNREACHABLE"docker ps --format "table {{.Names}}\t{{.Status}}\t{{.Ports}}" | grep -v "^NAME"Flag any container NOT showing healthy or Up:
unhealthy → CRITICALExited / Restarting → CRITICALUp X minutes without healthy → WARNING (check if has healthcheck)df -h / | awk 'NR==2 {
used=$5+0
if (used > 85) print "DISK_CRITICAL: " used "% used"
else if (used > 75) print "DISK_WARNING: " used "% used"
else print "DISK_OK: " used "% used"
}'free -h | awk '/^Mem:/ {
total=$2; avail=$7
print "RAM: total=" total " available=" avail
}'
docker stats --no-stream --format "{{.Name}}: {{.MemUsage}}" | sort -t'/' -k1 -rh | head -5docker exec ollama_engine ollama list 2>/dev/null | tail -n +2echo "{\"ts\":\"$(date -u +%Y-%m-%dT%H:%M:%SZ)\",\"event\":\"health_probe\",\"agent\":\"arifOS_bot\"}" \
>> ~/.openclaw/workspace/logs/audit.jsonl| Metric | WARNING | CRITICAL | Action |
|---|---|---|---|
| Disk usage | >75% | >85% | Notify Arif on Telegram |
| RAM available | <3 GiB | <1.5 GiB | Notify + pause heavy tasks |
| tools_loaded | <13 | <10 | Restart arifosmcp |
| Container state | Restarting | Exited/unhealthy | docker compose up -d <name> |
| Model count | 0 | — | docker exec ollama_engine ollama pull qwen2.5:3b |
# Restart unhealthy arifOS
docker compose -f /mnt/arifos/docker-compose.yml restart arifosmcp
# Restart unhealthy openclaw (from host — self-restart)
docker compose -f /mnt/arifos/docker-compose.yml restart openclaw
# Clear disk if >80%
docker builder prune -f
docker image prune -f --filter "dangling=true"Run this skill on every session start to establish baseline. Alert Arif via Telegram if CRITICAL.
# Send alert to Arif via Telegram bot
send_telegram_alert() {
local MESSAGE="$1"
if [ -n "${TELEGRAM_BOT_TOKEN:-}" ] && [ -n "${TELEGRAM_CHAT_ID:-}" ]; then
curl -s -X POST "https://api.telegram.org/bot${TELEGRAM_BOT_TOKEN}/sendMessage" \
-d "chat_id=${TELEGRAM_CHAT_ID}" \
-d "text=⚠️ arifOS_bot: ${MESSAGE}" \
-d "parse_mode=Markdown" > /dev/null
fi
}
# Example alerts:
# send_telegram_alert "🔴 arifosmcp UNHEALTHY — tools_loaded=$(curl ...)"
# send_telegram_alert "💿 Disk ${DISK_PCT}% — run: docker builder prune -f"
# send_telegram_alert "🧠 RAM critical — available: ${RAM_AVAIL}MiB"Note: TELEGRAM_CHAT_ID is the numeric chat ID of Arif's chat with @arifOS_bot. To get it: message the bot, then check https://api.telegram.org/bot${TELEGRAM_BOT_TOKEN}/getUpdates
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.