Install OpenClaw to DigitalOcean

A wizard that takes a non-DevOps user from zero to a working OpenClaw bot on a fresh DigitalOcean Droplet in ~15 minutes. The user does exactly three-or-four things: paste a DigitalOcean API token, paste a Telegram bot token, paste an LLM API key (or say "Codex" for OAuth via ChatGPT subscription), press /start in Telegram once, and — only for Codex — confirm a device code on auth.openai.com. Everything else is silent.

This is the DigitalOcean sibling of install-openclaw-to-yc. The flow, the cloud-init, the hardening, the Telegram pairing and the verification are identical. What differs is the provider plumbing: doctl instead of yc, an API token instead of a Yandex OAuth dance, a Cloud Firewall instead of a security group, and no cheap "stop the VM" pause (DO bills powered-off Droplets — see Step 6 / references/04).

Operating principles (the "don't bother the user" rules)

These rules override the rest of the document. Read them first.

1. Three inputs. Total. The only things you ask the user for are the DigitalOcean API token (Step 0), the Telegram bot token, and the LLM access (one of three options — see Step 1). Everything else — Droplet name, region, image, size, SSH key, firewall ingress, chat_id — is decided silently from safe defaults or auto-detected.
2. Never ask "are you sure" for actions inside this wizard's own scope (creating its own Droplet, its own firewall, its own bot pairing). Only confirm if you're about to destroy something the user might want to keep (an existing Droplet with the same name).
3. Never show shell commands, flags, paths, or stack traces to the user unless they explicitly ask "what did you run?". Progress is plain language: "Создаю Droplet…", "Ставлю OpenClaw…", "Проверяю что бот отвечает…".
4. Validate inputs upfront with a one-call test (doctl account get, Telegram /getMe, LLM key probe). Don't burn 15 minutes on a Droplet bootstrap with a bad key.
5. Auto-fix prerequisites silently when it's safe — install doctl, generate an SSH key, upload it to the account. Only stop and ask the user when something can't be done without their input (the API token itself, no payment method on the account).
6. One language — and the bot speaks it too. If the user wrote to the agent in Russian, all wizard prompts are in Russian, and the OpenClaw bot itself is configured to reply in Russian. Detect the user's language from their first few messages, pass it through to cloud-init as {{USER_LANGUAGE}} (ISO 639-1: ru/en/kk/...), and the bootstrap script appends a localization block to the bot's USER.md. Default if you can't tell: ru (workshop audience).
7. No emojis in user-facing text unless the user used them first.

Do NOT ask the user for these (hard override)

If you catch yourself drafting a question outside the three allowed inputs, re-read this section. The wizard's whole point is autonomy.

When to invoke

Trigger on: "install OpenClaw on DigitalOcean", "deploy OpenClaw to a DO droplet", "set up my CEO bot on DigitalOcean", "spin up an OpenClaw droplet", "поставь openclaw на digitalocean", "разверни бота на DigitalOcean", "у меня есть DO токен, подними бота", and close paraphrases.

Do NOT use this skill for:

• Yandex Cloud Kazakhstan → use install-openclaw-to-yc (hard-coded for the kz1-a realm).
• Local-machine OpenClaw install → use openclaw/install.sh in the ceo-ai-os repo (the user runs it on their laptop).
• AWS / GCP / Azure → out of scope.
• Adding a second agent or a second bot to an existing OpenClaw Droplet → out of scope.

The "dangerous install" disclaimer — say this once, early

OpenClaw is an agent runtime with full shell access on the box it runs on, it stores provider credentials in plaintext under ~/.openclaw/, and the gateway executes whatever the LLM decides to run. That is the deal everywhere OpenClaw is installed — it is not specific to DigitalOcean. This wizard mitigates the blast radius (dedicated non-root user, key-only SSH auth + fail2ban brute-force defense, ufw, systemd sandboxing, loopback-only gateway) but it does not make the install "safe" in an absolute sense.

Surface this once, in plain language, the first time you create real infrastructure (right before Step 2), then move on — don't nag:

Небольшое предупреждение: OpenClaw — это агент с полным доступом к своей VM, ключи он хранит на диске в открытом виде. Я разверну его на отдельной изолированной машине, доступ по SSH только по ключу (паролей нет) + fail2ban против перебора, и захардижу систему — но держи на этой VM только то, что не страшно потерять. Не клади на неё доступы к проду или личные секреты. Продолжаю.

Full security rationale and the threat model live in references/02-network-and-security.md.

Inputs (the only three questions you ask)

LLM access options (the user picks one)

Order of recommendation in the prompt: A → C → B for first-timers.

Everything below is decided without asking the user:

Default models per LLM option

For C, the wizard probes the subscription tier after OAuth completes — if openai/gpt-5.5 isn't in openclaw models list --json, it uses openai/gpt-5.4 as primary. (Codex models live in the openai/ namespace, backed by the openai-codex OAuth profile — verified on a live 2026.5.27 bot.)

Wizard flow

Step 0 — Silent preflight + the one mandatory prompt (the API token)

Run in order. Each block has a silent auto-fix path; only fall through to a user prompt when no silent path exists.

DigitalOcean basics — much simpler than Yandex Cloud:

• DigitalOcean is a single global API — https://api.digitalocean.com. There is no per-region endpoint, no cloud-id / folder-id, no realm split. The entire "four properties must move together" complexity from the YC skill does not exist here. One API token scopes the whole account.
• doctl stores credentials in contexts (~/.config/doctl/config.yaml). Use a dedicated context openclaw so you never clobber the user's existing default context.
• A Droplet that is powered off still bills on DigitalOcean. There is no cheap "stopped" state like YC. To stop paying you must destroy the Droplet (optionally snapshot first). Tell the user this only at Step 6 / teardown — not upfront.

a. Companion skill openclaw-guide must be loaded. Probe the agent's skill loader. If absent, run npx skills add CodeAlive-AI/ceo-ai-os@openclaw-guide -g silently. If npx is unavailable, tell the user (one sentence) to install both skills manually, then stop.

b. doctl CLI installed. doctl version. If missing, install silently for the platform:

# macOS (Homebrew is the common case on a founder's laptop)
brew install doctl 2>/dev/null \
  || {
    # Fallback: download the release tarball for the arch
    OS=$(uname -s | tr '[:upper:]' '[:lower:]')      # darwin | linux
    ARCH=$(uname -m); case "$ARCH" in x86_64) ARCH=amd64;; arm64|aarch64) ARCH=arm64;; esac
    VER=$(curl -fsSL https://api.github.com/repos/digitalocean/doctl/releases/latest | jq -r .tag_name | sed 's/^v//')
    curl -fsSL "https://github.com/digitalocean/doctl/releases/download/v${VER}/doctl-${VER}-${OS}-${ARCH}.tar.gz" \
      | tar -xz -C "$HOME/.local/bin" 2>/dev/null || tar -xz -C /tmp && sudo mv /tmp/doctl /usr/local/bin/
  }
doctl version

c. Authenticate a dedicated openclaw context. This is the only mandatory user prompt in Step 0.

First, check whether a working context already exists (the user may have used doctl before):

if doctl account get --context openclaw --format Email,Status --no-header >/dev/null 2>&1; then
  DOCTL_CTX="--context openclaw"      # already good
elif doctl account get --format Email,Status --no-header >/dev/null 2>&1; then
  DOCTL_CTX=""                        # default context works — reuse it, don't clobber
else
  NEED_TOKEN=1                        # fresh — must ask
fi

If NEED_TOKEN=1, ask the user once. Say exactly:

Чтобы создать сервер на DigitalOcean, мне нужен API-токен (один раз).

Открой https://cloud.digitalocean.com/account/api/tokens → Generate New Token → назови openclaw, оставь Full Access, срок 90 дней → скопируй строку, начинается на dop_v1_… и пришли мне. Я её никуда не сохраняю и не показываю обратно.

After receiving the token, initialize the dedicated context non-interactively and validate it in one call:

doctl auth init --context openclaw --access-token "$DO_TOKEN" >/dev/null 2>&1 \
  || { say "Токен не подошёл — проверь, что скопировал целиком (начинается на dop_v1_)."; stop; }
DOCTL_CTX="--context openclaw"

# One read call confirms the token works AND the account can create Droplets.
ACCT=$(doctl account get $DOCTL_CTX --output json)
STATUS=$(echo "$ACCT" | jq -r '.status')        # expect "active"
LIMIT=$(echo  "$ACCT" | jq -r '.droplet_limit')  # 0 → no payment method on file
[[ "$STATUS" != "active" ]] && { say "Аккаунт DigitalOcean не активен (status=$STATUS). Проверь почту/биллинг на cloud.digitalocean.com."; stop; }
[[ "${LIMIT:-0}" == "0" ]] && { say "К аккаунту DigitalOcean не привязан способ оплаты — лимит Droplet'ов = 0. Добавь карту на cloud.digitalocean.com/account/billing и запусти меня снова."; stop; }

From here on, every doctl call carries $DOCTL_CTX so we never touch the user's default context.

d. SSH key — local. ls ~/.ssh/id_ed25519.pub. If missing: silently ssh-keygen -t ed25519 -f ~/.ssh/id_ed25519 -N "" -C "openclaw-do-$(date +%Y%m%d)".

e. SSH key — uploaded to the DO account (idempotent by fingerprint). Unlike Yandex Cloud (where you pass the pubkey file straight to instance create), DigitalOcean requires the key to be registered in the account first, then referenced by fingerprint at Droplet-create time.

# DO identifies keys by MD5 fingerprint (colon-hex). Compute the local key's.
FP=$(ssh-keygen -E md5 -lf ~/.ssh/id_ed25519.pub | awk '{print $2}' | sed 's/^MD5://')

# Already uploaded?
if doctl compute ssh-key list $DOCTL_CTX --format FingerPrint --no-header | grep -qx "$FP"; then
  SSH_FP="$FP"
else
  SSH_FP=$(doctl compute ssh-key import "openclaw-$(date +%Y%m%d)" \
            --public-key-file ~/.ssh/id_ed25519.pub \
            $DOCTL_CTX --format FingerPrint --no-header)
fi
# $SSH_FP is what we pass to `droplet create --ssh-keys`.

If ssh-key import errors with "SSH key is already in use on your account" (a 422 when the same key was uploaded under a different name), fall back to the fingerprint from the list — it's already there.

f. Existing Droplet with the same name. doctl compute droplet list $DOCTL_CTX --format Name --no-header | grep -qx openclaw-bot. If found, ask once: "У тебя уже есть Droplet 'openclaw-bot' — поставить новый под именем openclaw-bot-XXXX?" Default yes; pick a random 4-char suffix.

Do not print anything to the user about (a)-(f) if everything passed silently. Move to Step 1.

Step 1 — Ask the two remaining questions (Telegram + LLM)

In one message, in the user's language:

Отлично, доступ к DigitalOcean есть. Теперь две вещи для самого бота (~5 минут).

1) Telegram bot token. Открой @BotFather в Telegram → отправь /newbot → придумай имя → придумай username, заканчивающийся на bot → BotFather пришлёт токен. Пришли его мне.

2) Доступ к LLM — выбери ОДИН из трёх вариантов:

A) Anthropic API ключ (рекомендую первым, лучшее качество) https://console.anthropic.com/settings/keys → Create Key. Начинается на sk-ant-. На billing должно быть ≥$5.

B) OpenRouter API ключ (один ключ к 200+ моделям) https://openrouter.ai/keys → Create Key. Начинается на sk-or-. Баланс ≥$5.

C) OpenAI Codex через ChatGPT подписку (бесплатно если уже платишь Plus/Pro) Не нужен ключ. Просто напиши слово «Codex». После установки я попрошу ввести 8-символьный код на auth.openai.com — один раз.

Пришли токен Telegram и один из трёх. Хоть в одном сообщении, хоть по отдельности. Я никуда не сохраняю значения.

Detect the LLM provider from what the user pasted:

case "$LLM_INPUT" in
  sk-ant-*) LLM_PROVIDER=anthropic ;;
  sk-or-*)  LLM_PROVIDER=openrouter ;;
  Codex|codex|CODEX|ChatGPT|chatgpt|OpenAI*|"openai codex"|OAuth|oauth)
    LLM_PROVIDER=openai-codex; LLM_API_KEY="" ;;
  *) say "Не распознал — это Anthropic-ключ (sk-ant-), OpenRouter-ключ (sk-or-) или слово 'Codex'?" && reprompt ;;
esac

Validate the credentials (don't burn 15 minutes on a bad key):

# Telegram token — always validate
BOT_USERNAME=$(curl -fsS "https://api.telegram.org/bot${TELEGRAM_BOT_TOKEN}/getMe" | jq -er '.result.username') \
  || (say "Telegram токен не прошёл проверку. Скопируй его ещё раз из @BotFather." && stop)

case "$LLM_PROVIDER" in
  anthropic)
    curl -fsS https://api.anthropic.com/v1/messages \
      -H "x-api-key: ${LLM_API_KEY}" -H "anthropic-version: 2023-06-01" -H "content-type: application/json" \
      -d '{"model":"claude-haiku-4-5","max_tokens":1,"messages":[{"role":"user","content":"ok"}]}' \
      | jq -er '.content' >/dev/null \
      || (say "Anthropic ключ не работает или нет кредита. Проверь на console.anthropic.com." && stop) ;;
  openrouter)
    curl -fsS https://openrouter.ai/api/v1/auth/key -H "Authorization: Bearer ${LLM_API_KEY}" \
      | jq -er '.data.usage != null' >/dev/null \
      || (say "OpenRouter ключ не прошёл проверку. Перепроверь на openrouter.ai/keys." && stop)
    BAL=$(curl -fsS https://openrouter.ai/api/v1/auth/key -H "Authorization: Bearer ${LLM_API_KEY}" | jq -r '.data.limit_remaining // 0')
    [[ "$BAL" == "0" ]] && say "На OpenRouter $0 кредита. Бот не сможет отвечать. Пополни на openrouter.ai/credits." ;;
  openai-codex)
    say "Хорошо, после установки покажу 8-символьный код для https://auth.openai.com/codex/device. Это разовое действие." ;;
esac

BOT_USERNAME is captured here for the one-click chat link in Step 5.

Step 2 — Silent Droplet creation

Show the one-time "dangerous install" disclaimer (above) now, then proceed silently.

a. Render the cloud-init file. Substitute these placeholders (no TELEGRAM_CHAT_ID — auto-detected in Step 4):

• {{SSH_PUBLIC_KEY}} — content of ~/.ssh/id_ed25519.pub.
• {{TELEGRAM_BOT_TOKEN}} — from Step 1.
• {{USER_LANGUAGE}} — detected language code.

• {{LLM_ENV_LINE}} — depends on the chosen provider:

  Provider	Substituted line
  anthropic	ANTHROPIC_API_KEY=<key>
  openrouter	OPENROUTER_API_KEY=<key>
  openai-codex	(empty string — OAuth fills the profile after Step 3.5)

Write to /tmp/openclaw-cloud-init.yaml with mode 600.

b. Create the Droplet. --wait blocks until it's active, then we read the public IP. Try fra1; if the size/region pairing is unavailable, fall back to ams3.

DROPLET_ID=$(doctl compute droplet create "$VM_NAME" \
  --region fra1 \
  --image ubuntu-24-04-x64 \
  --size s-2vcpu-4gb \
  --ssh-keys "$SSH_FP" \
  --user-data-file /tmp/openclaw-cloud-init.yaml \
  --enable-monitoring \
  --tag-name openclaw \
  --wait \
  $DOCTL_CTX --format ID --no-header 2>/tmp/openclaw-droplet.err) \
  || true

# Region/size fallback
if [[ -z "$DROPLET_ID" ]] && grep -qiE "not available|can only be created|region" /tmp/openclaw-droplet.err; then
  DROPLET_ID=$(doctl compute droplet create "$VM_NAME" \
    --region ams3 --image ubuntu-24-04-x64 --size s-2vcpu-4gb \
    --ssh-keys "$SSH_FP" --user-data-file /tmp/openclaw-cloud-init.yaml \
    --enable-monitoring --tag-name openclaw --wait \
    $DOCTL_CTX --format ID --no-header)
fi
[[ -z "$DROPLET_ID" ]] && { say "Не удалось создать Droplet. Вот что вернул DigitalOcean:"; cat /tmp/openclaw-droplet.err; stop; }

IP=$(doctl compute droplet get "$DROPLET_ID" $DOCTL_CTX --format PublicIPv4 --no-header)

If the create errors with you are not authorized or a payment message — that's the billing case Step 0c should have caught; surface it: "Похоже, к аккаунту DigitalOcean не привязана карта. Открой cloud.digitalocean.com/account/billing, добавь способ оплаты и запусти меня снова." Stop.

c. Create + attach the Cloud Firewall. DigitalOcean firewalls are a separate resource attached by Droplet ID. Default-deny inbound except SSH; allow all outbound. SSH is intentionally open to all (0.0.0.0/0 + ::/0, no per-IP lock) because users and the automation AI agent connect from dynamic IPs and the agent makes frequent SSH calls that must never be IP-banned or throttled. The security controls are key-only auth + fail2ban (fail2ban bans only on FAILED auths, never an authenticated key user).

doctl compute firewall create \
  --name "${VM_NAME}-fw" \
  --inbound-rules "protocol:tcp,ports:22,address:0.0.0.0/0,address:::/0" \
  --outbound-rules "protocol:tcp,ports:all,address:0.0.0.0/0,address:::/0 protocol:udp,ports:all,address:0.0.0.0/0,address:::/0 protocol:icmp,address:0.0.0.0/0,address:::/0" \
  --droplet-ids "$DROPLET_ID" \
  $DOCTL_CTX --format ID --no-header

Note: the gateway port 18789 is not opened — it binds to loopback only and we reach it over SSH. The host-level ufw inside cloud-init is a second, independent layer behind this Cloud Firewall (defense in depth).

Then one sentence to the user:

Сервер создан. Ставлю OpenClaw — займёт около 10 минут. Можешь пока заварить чай.

Step 3 — Wait silently for cloud-init

Poll every 30 seconds (DO's stock image creates no ubuntu/root-only barrier; our cloud-init makes openclaw):

ssh -o StrictHostKeyChecking=accept-new -o ConnectTimeout=5 openclaw@$IP \
  'test -f /var/lib/openclaw-bootstrap-done && echo READY || echo PENDING'

Don't spam the user with raw log lines. Every ~3 minutes, emit one warm progress sentence based on the current phase from tail -1 /var/log/openclaw-bootstrap.log:

Cap at 15 minutes. If still not ready, surface to the user ("Что-то пошло не так на VM, проверяю логи") and jump to references/04-troubleshooting.md.

Step 3.5 — OAuth device-code flow (ONLY if LLM_PROVIDER=openai-codex)

Skip this entire step for anthropic and openrouter.

The provider id is openai-codex and the command openclaw models auth login --provider openai-codex --device-code is real and current (verified against OpenClaw docs/providers/openai.md — the device-code path exists specifically for headless/callback-hostile VMs; OpenClaw performs the OAuth itself and stores the profile as openai-codex:default). Do not rename the provider to codex (that is the agent-runtime id, a different concept) or shell out to a native codex login binary (not needed).

For openai-codex, first make sure the Codex provider is loadable, then run the device-code OAuth flow over SSH with a forced TTY:

# The openai-codex auth provider ships in the bundled `openai` extension, but on
# some builds the login errors with "No provider plugins found" until the Codex
# plugin is present. Ensure it once (idempotent, harmless if already there):
ssh openclaw@$IP "openclaw plugins install clawhub:@openclaw/codex 2>/dev/null || true"

ssh -tt -o ServerAliveInterval=30 openclaw@$IP \
  "openclaw models auth login --provider openai-codex --device-code" | tee /tmp/openclaw-oauth.log

The CLI prints a URL (https://auth.openai.com/codex/device) and an 8-char code (ABCD-1234). Extract both (match generously — formats shift across releases). Show the user one clean message:

Последний шаг — подключи бота к ChatGPT.

Открой: https://auth.openai.com/codex/device Введи код: ABCD-1234

Войди под аккаунтом ChatGPT (Plus или Pro) и разреши доступ. Жду до 15 минут.

The SSH session blocks until the user completes the flow. When it exits 0, OpenClaw wrote auth-profiles.json.

Known pitfall (issue #74212, 2026-05): in some SSH sessions OpenClaw masks the code as [shown on the local device only]. Retry with ssh -tt; if still masked, run the auth command in a fresh interactive ssh openclaw@$IP session, read the code there, resume.

After the profile is written, probe the subscription tier and set the model. Two things verified on a live OpenClaw 2026.5.27 bot: Codex subscription models are registered in the openai/ namespace (e.g. openai/gpt-5.5), not openai-codex/* — the openai-codex profile only backs the auth, so openclaw models list --provider openai-codex returns nothing; and the JSON flag for models list is --json, not --format json. So:

HAS_GPT55=$(ssh openclaw@$IP "openclaw models list --json 2>/dev/null" \
  | jq -r '.[]?.id // empty' 2>/dev/null | grep -Fx 'openai/gpt-5.5' || true)
if [[ -n "$HAS_GPT55" ]]; then
  # Pro tier — gpt-5.5 available
  ssh openclaw@$IP "openclaw config set agents.defaults.model.primary 'openai/gpt-5.5' && openclaw config set agents.defaults.model.fallbacks '[\"openai/gpt-5.4\"]'"
else
  # Plus tier (or gpt-5.5 not granted) — use the gpt-5.4 family
  ssh openclaw@$IP "openclaw config set agents.defaults.model.primary 'openai/gpt-5.4' && openclaw config set agents.defaults.model.fallbacks '[\"openai/gpt-5.4-mini\"]'"
fi
ssh openclaw@$IP "sudo systemctl restart openclaw-gateway"

If after 15 minutes there's still no openai-codex profile: tell the user "не получилось войти в ChatGPT, давай ещё раз" and re-run the auth command. Don't destroy the Droplet — only the OAuth step needs retrying.

Step 4 — One-click chat link + auto-pair

When /var/lib/openclaw-bootstrap-done exists, the gateway is up in pairing mode. This is where wizards historically fail silently — read this whole section.

What actually happens when the user presses /start

1. Telegram delivers /start to the bot.
2. OpenClaw enforces dmPolicy=pairing — it calls issuePairingChallenge(), records a pending request, and the bot replies to the user with the pairing code + instructions. The user sees this; they shouldn't reply to it.
3. The pending request lives in openclaw pairing list telegram --format json until approved or expired.

Pre-emptive heads-up (send BEFORE asking them to press /start)

Бот готов. Открой его в Telegram: https://t.me/{{BOT_USERNAME}} и нажми /start.

Бот пришлёт короткое сообщение с кодом — ничего с ним делать не надо, я подтвержу доступ автоматически за пару секунд. После этого пиши боту как обычно.

Poll for chat_id

for i in $(seq 1 150); do   # 150 × 2s = 5 minutes
  CHAT_ID=$(curl -fsS "https://api.telegram.org/bot${TELEGRAM_BOT_TOKEN}/getUpdates?timeout=2" \
    | jq -r '.result[0].message.chat.id // empty')
  [[ -n "$CHAT_ID" ]] && break
  sleep 2
done
[[ -z "$CHAT_ID" ]] && fail "Пользователь не нажал /start за 5 минут"

Approve the pairing (the part the old wizard broke)

The pending request schema (verified against src/gateway/protocol/schema/devices.ts) uses senderId for the Telegram user ID and requestId for the primary key — not chatId / code. A filter on .chatId always returns empty.

APPROVE_TOKEN=""
for i in $(seq 1 5); do
  APPROVE_TOKEN=$(ssh openclaw@$IP "openclaw pairing list telegram --format json 2>/dev/null" \
    | jq -r --arg cid "$CHAT_ID" '
        .[] | select((.senderId|tostring)==$cid or (.chatId|tostring)==$cid or (.sender // empty|tostring)==$cid)
            | (.requestId // .code // empty)' | head -n1)
  [[ -n "$APPROVE_TOKEN" ]] && break
  sleep 2
done
[[ -z "$APPROVE_TOKEN" ]] && fail "Запрос на pairing не появился — посмотри journalctl на VM"

ssh openclaw@$IP "openclaw pairing approve telegram '$APPROVE_TOKEN'" \
  || fail "openclaw pairing approve failed (token=$APPROVE_TOKEN)"

Lock down + persist chat_id

ssh openclaw@$IP "
  openclaw config set channels.telegram.dmPolicy allowlist
  openclaw config set channels.telegram.allowFrom '[${CHAT_ID}]'
  echo 'TELEGRAM_CHAT_ID=${CHAT_ID}' >> /home/openclaw/.openclaw/gateway.env
  sudo systemctl restart openclaw-gateway
"
# Wait for /health 200 before Step 5
for i in $(seq 1 30); do
  ssh openclaw@$IP 'curl -fsS -m 3 http://127.0.0.1:18789/health' >/dev/null 2>&1 && break
  sleep 2
done

If the user doesn't press /start within 5 minutes, poke them once. After 15 minutes of no signal, stop and tell them how to resume.

Step 5 — Verify the bot answers (do NOT skip), then hand off

The #1 historical failure mode was claiming "done" while the bot was silent. Verification below is mandatory — three signals, all must pass.

5a. Trigger a reply

case "$USER_LANGUAGE" in
  ru) PROBE="Скажи 'привет', чтобы я убедился, что ты отвечаешь." ;;
  kk) PROBE="Сәлем деп жаз — жауап беретіндігіңе көз жеткізейін." ;;
  *)  PROBE="Say 'hi' so I can confirm you're alive." ;;
esac
curl -fsS "https://api.telegram.org/bot${TELEGRAM_BOT_TOKEN}/sendMessage" -d "chat_id=${CHAT_ID}" -d "text=${PROBE}"

5b. Three checks, all required

Check 1 — Gateway logged an outgoing message within 90s:

ssh openclaw@$IP "timeout 90 sudo journalctl -u openclaw-gateway -f --no-pager 2>/dev/null \
  | grep -m1 -E 'telegram.*sent|outgoing.*telegram|sendMessage.*ok'"

If it times out: gateway accepted inbound but didn't reply. Most likely the LLM provider isn't configured (Codex OAuth didn't finish, or env key empty). Jump to references/04-troubleshooting.md §4c-e.

Check 2 — A bot reply appears in getUpdates within 90s (see YC-derived note in §04: this check can be unreliable in some test setups; fall back on Check 1 + Check 3).

Check 3 — User confirms. Ask once: "Бот должен был тебе ответить в Telegram. Ответил?" Wait for "да". If "нет" → references/04-troubleshooting.md §4. Never claim success unless all three pass.

5c. If language is wrong

LOCALE_PACK="/usr/local/share/openclaw-locale-${USER_LANGUAGE}.md"
ssh openclaw@$IP "
  test -f $LOCALE_PACK && cat $LOCALE_PACK >> ~/.openclaw/workspace/USER.md
  openclaw sessions reset --channel telegram --to ${CHAT_ID} 2>/dev/null || true
"

Then re-run the probe. If still wrong language, surface to the user — don't loop.

Step 5.5 — Onboarding (hand off to openclaw-user-onboarding)

The bot is alive but anonymous. Hand off to openclaw-user-onboarding, which collects five fields (identity, focus, style, tools, anti-patterns), writes USER.md on the Droplet, and resets the Telegram session.

Hand-off payload:

Trigger with one line: "Бот живой. Последний шаг — расскажи о себе коротко, чтобы я с первого сообщения был полезным." Then invoke openclaw-user-onboarding.

If the user says "пропусти"/"skip": write a minimal placeholder USER.md and proceed — onboarding is not a gate. If the skill isn't loaded: write a placeholder inline and mention it in the final summary.

Final hand-off message

Only after all three checks pass:

OpenClaw запущен на DigitalOcean.

  Droplet      : openclaw-bot  (fra1, 2 vCPU / 4 GB / 80 GB SSD)
  IP           : 159.x.x.x
  Бот          : @your_bot_name
  LLM          : <one of three lines below>
  Workspace    : CEO AI OS (48 CEO-скиллов)
  Стоимость    : ~$24/мес (Droplet) + LLM по тарифу провайдера

LLM line variants:

Что дальше:
  • Просто пиши боту в Telegram — он уже знает кто ты, попробуй: «что у меня сегодня важно?»
  • Стратегические скиллы: «Сделай weekly review» или «Помоги принять решение об X»
  • Обновить профиль: скажи мне «обнови мой профиль для бота»
  • ВАЖНО про деньги: на DigitalOcean выключенный Droplet ВСЁ РАВНО тарифицируется.
    Чтобы перестать платить — Droplet нужно удалить (по желанию — сделать snapshot).
    Поставить «на паузу» дёшево, как в облаках с почасовой остановкой, тут нельзя.
  • Удалить совсем (перестать платить):
    doctl compute droplet delete openclaw-bot --context openclaw --force
    doctl compute firewall delete <fw-id> --context openclaw --force

Если что-то сломается — просто скажи мне «бот молчит» или «openclaw сломался», я разберусь.

If the verification ping doesn't get a reply within 60s, run references/04-troubleshooting.md §4 silently — don't claim success.

Auto-recovery (what the wizard does without asking)

DigitalOcean — common trip points (read before debugging)

1. Powered-off Droplets still bill. The single biggest DO surprise. doctl compute droplet-action power-off stops the OS but you keep paying for the Droplet's reserved CPU/RAM/disk. To actually stop paying: snapshot (optional, ~$0.06/GB/mo) then droplet delete. Don't tell the user "just stop it to save money" — that's true on YC, false on DO.
2. SSH keys must be uploaded to the account first. Passing a raw pubkey path to droplet create --ssh-keys does NOT work — it expects a fingerprint or numeric ID of an already-registered key. Always ssh-key import (idempotent) before create.
3. droplet_limit == 0 means no payment method. A fresh account with no card has a Droplet limit of 0 and every create 422s with an authorization error. Check doctl account get first.
4. Firewall is a separate resource. Inbound default-deny only takes effect once a Cloud Firewall is attached to the Droplet. A Droplet with no firewall is wide open on every port the OS listens on — which is why the cloud-init also runs ufw as a second layer.
5. User-data (cloud-init) is retrievable from the metadata service at 169.254.169.254/metadata/v1/user-data for the Droplet's lifetime, and it contains the secrets we injected. There's no API to wipe it. We scrub the on-disk copy; treat the Droplet as holding its own bootstrap secrets and don't share the box.

Failure modes (when the silent fixes aren't enough)

For everything else: dump /var/log/openclaw-bootstrap.log and sudo journalctl -u openclaw-gateway -n 200 from the Droplet, surface to the user as "вот что я вижу, давай разбираться", do not guess.

References

• references/01-prerequisites.md — doctl install, API token + contexts, SSH key upload, account/payment checks.
• references/02-network-and-security.md — Cloud Firewall rules, public-IP rationale, hardening choices, the "dangerous install" threat model.
• references/03-openclaw-config.md — Telegram pairing flow, all three LLM providers, workspace seeding.
• references/04-troubleshooting.md — failure modes with copy-paste fixes (incl. the power-off-still-bills trap).
• references/05-marketplace-and-workshop.md — DO Marketplace 1-click alternative (and why automation skips it) + workshop shared-token mode.
• scripts/cloud-init.yaml — the full Droplet bootstrap (swap, Node, OpenClaw, hardening, ceo-ai-os workspace, systemd system service).

Companion skills

Joint install:

npx skills add CodeAlive-AI/ceo-ai-os@install-openclaw-to-digitalocean -g
npx skills add CodeAlive-AI/ceo-ai-os@openclaw-guide                    -g   # required
npx skills add CodeAlive-AI/ceo-ai-os@openclaw-user-onboarding          -g   # recommended

Consulting after install — delegate, don't duplicate

When the user asks anything not about install (channel setup, use cases, debugging an existing bot, adding MCP servers, multi-agent), read the matching openclaw-guide/references/<file>.md first — don't answer from memory. This skill's job ends after Step 5.

What this skill does NOT cover

• Multi-agent setups (two agents on one Droplet) — out of scope.
• WhatsApp / Discord / Slack channels — Telegram only here; see openclaw-guide/references/channels.md.
• Use-case design (morning brief, research, decision playbooks) — see openclaw-guide/references/use-cases.md.
• Backup, snapshots, and migration beyond the teardown note — separate skill.
• Production-grade hardening (SELinux, kernel sysctl, SSH cert auth) — overkill for a personal CEO bot.
• DigitalOcean App Platform / Kubernetes deploys — this skill provisions a plain Droplet only.