OpenClaw Cuts Agent Costs With Playbook

This article presents a five-step playbook to dramatically reduce running costs of always-on agents such as OpenClaw by eliminating token and API waste. It details tools and tactics—qmdskill local search, session initialization rules, Exa AI web search, model routing, and local LLM heartbeats—and cites a deployment example dropping monthly costs from roughly $1,200 to about $36, while noting maintenance tradeoffs.