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Presets are curated combinations of services and skill packs designed for specific use cases. Instead of manually selecting services, you can start with a preset and customize it.

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Available presets

better-openclaw includes 9 presets that cover common deployment scenarios:

Minimal

Services: Redis, Caddy
Memory: ~1 GB
Use case: Lightweight cache and session management

Creator

Services: FFmpeg, Remotion, MinIO, Redis, Caddy
Memory: ~2 GB
Use case: Media creation and video processing

Researcher

Services: Qdrant, SearXNG, Browserless, Redis, Caddy, PostgreSQL
Memory: ~2.5 GB
Use case: Research agent with vector search and web scraping

DevOps

Services: n8n, PostgreSQL, Redis, Uptime Kuma, Grafana, Prometheus, Caddy
Memory: ~3 GB
Use case: Full monitoring and automation stack

Content Creator

Services: Postiz, FFmpeg, MinIO, Redis, PostgreSQL, Umami, Caddy
Memory: ~2 GB
Use case: Social media scheduling with media processing

AI Playground

Services: Ollama, Open WebUI, LiteLLM, AnythingLLM, Redis, Caddy
Memory: ~4 GB
Use case: Local AI experimentation with multiple models

Coding Team

Services: Claude Code, OpenCode, Gitea, Code Server, Redis, Caddy
Memory: ~2.5 GB
Use case: AI development environment with coding agents

La Suite Meet

Services: PostgreSQL, Redis, LiveKit, La Suite Meet (backend/frontend/agents), Whisper, Ollama, Caddy
Memory: ~2 GB
Use case: Open-source video conferencing with AI agents

Full Stack

Services: All core services + all skill packs
Memory: ~8 GB
Use case: Everything enabled for maximum flexibility

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Preset structure

Each preset is a JSON file that defines: 
{
  "id": "devops",
  "name": "DevOps",
  "description": "Full monitoring and automation stack with n8n, Grafana, and Uptime Kuma",
  "services": [
    "n8n",
    "postgresql",
    "redis",
    "uptime-kuma",
    "grafana",
    "prometheus",
    "caddy"
  ],
  "skillPacks": [
    "dev-ops"
  ],
  "estimatedMemoryMB": 3072
}

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Using presets

You can use presets in multiple ways:
The interactive wizard presents all presets as options:
npx create-better-openclaw
# Select "Use a preset" when prompted
# Choose from the list of 9 presets

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Customizing presets

Presets are starting points, not rigid templates. You can customize them in several ways:

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Add services to a preset

npx create-better-openclaw --preset researcher --services meilisearch,grafana --yes
This starts with the Researcher preset and adds Meilisearch and Grafana.

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Change proxy configuration

npx create-better-openclaw --preset devops --proxy traefik --yes
This uses the DevOps preset but replaces Caddy with Traefik.

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Modify after generation

After generating a stack, you can add or remove services: 
# Generate with preset
npx create-better-openclaw --preset minimal --yes

# Add services later
cd my-stack
npx create-better-openclaw add postgresql
npx create-better-openclaw add grafana

# Remove a service
npx create-better-openclaw remove redis

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Listing presets

npx create-better-openclaw presets list

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Preset vs. custom selection

When should you use a preset vs. manually selecting services?

Use a preset when:

  • You need a quick start for a known use case
  • You want a tested, coherent stack
  • You’re new to better-openclaw
  • You’re deploying for CI/CD automation

Custom selection when:

  • You have specific service requirements
  • You’re building a unique stack
  • You want to minimize resource usage
  • You’re experimenting with new services

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How skill packs relate to presets

Presets include skill packs that bundle related agent skills. For example:
  • Researcher preset → includes research-agent skill pack
  • DevOps preset → includes dev-ops skill pack
  • Creator preset → includes video-creator skill pack
The skill packs ensure that your agents have ready-to-use templates for interacting with the services in your stack.

Learn more

Explore how skill packs work and what they include

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Creating custom presets

You can create your own presets by adding a JSON file to the presets/ directory: 
{
  "id": "my-custom-preset",
  "name": "My Custom Preset",
  "description": "Tailored for my specific use case",
  "services": [
    "postgresql",
    "redis",
    "n8n",
    "grafana"
  ],
  "skillPacks": [
    "dev-ops"
  ],
  "estimatedMemoryMB": 2048
}
Then register it in packages/core/src/presets/registry.ts.
Custom presets are useful for organizations that want to standardize their internal stacks.

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