OpenClaw Full Course: Setup, Skills, Voice, Memory & More

Purpose

Step-by-step, in-depth tutorial to install, configure and make an OpenClaw (Clawbot / Claudebot) instance productive and secure. Emphasis on practical best practices learned from many hours of personal configuration.

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Security & deployment

• Treat OpenClaw as an untrusted virtual assistant. Isolate it from sensitive accounts (main computer, crypto keys, primary email).
• Use separate service accounts and limited-permission tokens for integrations.
• Prefer running OpenClaw on a VPS rather than local hardware. VPS advantages:
  • automatic backups, data-center physical security,
  • easy on/off and low cost.
• Referenced a longer (~50-minute) security/hardening video for advanced hardening steps.

Best practice: assume the agent can be compromised and minimize its access to sensitive resources.

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Quick install (Hostinger one‑click)

Recommended fastest route: Hostinger KVM2 one‑click deploy. (Presenter referenced a discount code.)

Typical flow:

1. Choose plan and location.
2. Paste one LLM API key (Anthropic Opus in the transcript).
3. Deploy — Hostinger runs OpenClaw in a Docker container.
4. After deploy: copy the gateway token from the environment, open the OpenClaw gateway web UI and log in with the token.

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Server access and Docker

Options to interact with the VPS/container:

• Use the host web terminal.
• SSH to the VPS directly.
• SSH from VS Code or Cursor (remote).

Docker notes:

• OpenClaw runs inside a container.
• To run CLI inside the container: list containers (docker ps) then exec into the container (docker exec -it /bin/bash) and run openclaw commands.
• Use gateway logs (filter by error/fatal) to debug common problems (missing API keys, insufficient billing credits, etc.).

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LLM model strategy & cost control

• Use a high-quality model (Anthropic Opus, e.g., Opus 4.6) for planning and high-leverage tasks.
• Use a cheaper fallback model (OpenAI Codex / ChatGPT subscription / “codeex”) for routine tasks and code execution to save cost.
• Configure automatic model routing:
  • Set Opus as default for planning.
  • Delegate coding and routine tasks to the cheaper model.
  • Example approach: create a /model command to switch models and save routing rules; have tasks report which model handled them.
• Billing tips: add API credits, set monthly spend limits, enable spend notifications.

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Integrations — Telegram

• Create a Telegram bot via BotFather and copy the bot token.
• Pair the bot with OpenClaw using the gateway pairing command.
• Promote the bot to admin in group chats and configure permissions.
• Create separate Telegram groups for scoped topics (e.g., “startup ideas”, “accounting”) so the bot’s memory/history and behavior can be channel-scoped.
• Configure rules so the bot restricts responses by channel topic and replies only when required.

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Voice / speech-to-text

• Enable the audio transcription skill. Supported providers include Deepgram, OpenAI Whisper, etc.
• If a provider key is not required, OpenClaw may fall back to a default provider.
• If transcription fails, install Whisper locally or choose another provider.
• Once enabled, sending audio messages to Telegram will allow OpenClaw to transcribe them (voice mode).

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Skills system (what a skill is, ClawHub, creating skills)

• Definition: a skill is a folder containing a skill.md (markdown) plus optional scripts (for example, Python files) that the agent can run.
• ClawHub provides pre-built skills. Caution: review and vet skills before enabling them.
• OpenClaw can write its own skills on demand. Example workflow:
  • Create a “hello world in 5 languages” skill → folder + skill.md generated → registers a command (e.g., /skill hello-world-languages).
• Skill installation: enable from the Gateway and install dependencies (some skills require extra setup).

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Coding agent & GitHub integration

• Enable the coding agent skill so the bot can generate code and scripts.
• Create a separate GitHub account for the bot and connect via GitHub CLI / OAuth.
• Configure git identity inside the container and allow OpenClaw to auto-commit code for auditing and backups.
• Use the coding agent + GitHub to let the bot create, commit, and manage its own repositories.

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Editing workspace and files

• Use VS Code or Cursor remote SSH to browse the container’s OpenClaw data/workspace.
• Important locations to review:
  • workspace/skills
  • memory files
  • config files
  • scripts
• Reading skill.md and related scripts helps you understand and audit the bot’s capabilities.

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Memory architecture & enhancements

Types of memory:

• memory.md: persistent long-term memory.
• Daily/session memory files: short-term per-day logs.

Recommended settings and features:

• Enable compaction and memory flush so important context is written to memory before history gets compacted.
• Enable session memory search so recent session transcripts are searchable.
• Vectorized memory search: enable a vector memory backend (transcript mentioned a “QMD” backend). Vector search greatly improves recall and retrieval quality.
• Follow OpenClaw documentation for prerequisites and setup of vector memory backends.

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Identity, user, soul, tools, heartbeat

• user.md and identity.md: store human-specific and bot-specific long-term data. Best practice: have the bot interview you to populate these files rather than editing them manually.
• soul.md: bot persona, core beliefs, behavior boundaries and “vibe” — edit to adjust tone or constraints.
• tools.md: device and tool preferences used by skills.
• heartbeat.md:
  • Defines periodic wake-up tasks (default/recommended interval often ~30 minutes, configurable).
  • On each heartbeat the bot can run review jobs, spawn subagents, check email, or perform maintenance.
• Crons: scheduled one-off or recurring jobs for reminders and automation.

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Subagents (background agents)

• Subagents are lightweight background agents spun up to do parallel work.
• Many subagents can be created to split tasks into parallel subtasks.
• They are visible in the Gateway sessions area and useful for parallelization.

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Practical recommendations & tips

• Always check logs and billing when something stops working (common causes: missing API key or low credits).
• Start with a secure baseline; using the one-click VPS route speeds setup — harden later as needed.
• Keep sensitive data out of the agent: separate accounts and limited-permission tokens.
• Don’t enable random ClawHub skills without reviewing their contents.
• Balance quality vs. cost with a mix of high-quality and cheaper models.
• Use GitHub integration to automatically store code written by the agent for review and version control.

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Tools / integrations mentioned

• Hostinger (VPS one‑click deployment)
• Docker (container runtime)
• Anthropic (Opus models)
• OpenAI (Codex / GPT)
• Telegram (BotFather, groups, tokens)
• Whisper / Deepgram (STT providers)
• ClawHub (pre-built skill marketplace)
• GitHub (CLI, OAuth, separate bot account)
• VS Code or Cursor (remote SSH editor)
• QMD / vector memory backend (for vectorized memory search)
• OpenClaw gateway (web UI), logs, sessions, skills dashboard

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Referenced resources / further guides

• Longer (~50-minute) hardening/security video (shown in the original presentation).
• OpenClaw documentation and examples (memory & vector backend instructions).
• ClawHub for skill repositories.

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Main speaker / sources

• Presenter: Tech With Tim (Tim). Coupon code referenced: “techwithtim”.
• Technologies and providers discussed: OpenClaw, Hostinger, Anthropic (Opus), OpenAI (Codex/ChatGPT), Telegram, Docker, Whisper/Deepgram, GitHub, ClawHub, VS Code/Cursor.

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