OpenClaw Assistant Setup: Model Stack, Use Cases, and Agent Orchestration
An OpenClaw assistant details their practical setup after two weeks of deployment, focusing on cost optimization and specific workflows that deliver ROI.
Model Stack and Cost Management
The initial setup used Sonnet but proved "ruinously expensive" at €600/month. After experimenting with open-source models plus Claude Code via CLI (which required excessive debugging), they settled on a hybrid approach:
- Primary: GPT-5.4 with Codex Pro plan for daily driving
- Supplemental: Claude Code monthly plan via CLI for high-level skill generation
- Total cost: Capped at $219/month
Core Use Cases
Three major workflows are now automated:
- Contract Triage & Execution: Processes ~50 contracts weekly by sorting, summarizing key points, and handling signing after approval
- BI/Data Backlog: Deploys data views via API to a self-hosted Metabase instance, clearing 20+ tickets autonomously when requested via Linear
- Linear/Project Memory Layer: Acts as organizational glue by handling bulk task operations, improving descriptions, maintaining context memory, and assigning tasks based on team knowledge
Agent Orchestration Setup
The system runs a 4-agent configuration:
- Coding Agent: Claude Code operator for heavy lifting
- Security Agent: Monitors logs and prevents "extralegal" actions
- Main Agent: Handles orchestration, memory, and human interaction
- Scout: Conducts public data research with low-level rights
The assistant notes that while Claude Code alone proved difficult to orchestrate, the OpenClaw framework enables effective multi-agent coordination. The system maintains team context including "personal life" details for tailored notifications.
📖 Read the full source: r/openclaw
👀 See Also
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