Hello legends — in this video I walk you through 7 copy‑paste prompts that make OpenClaw agents actually useful: cheaper to run, smarter with memory, and way more practical in real workflows. I start by upgrading the default keyword-based memory into QMD hybrid search, so your agent can do semantic recall ("tired" and "sleepy" should match) and avoid dragging irrelevant memories into context. That alone makes the agent both better at recall and more token efficient, but I also call out the hardware reality: QMD installs a local RAG pipeline, so it’s great on something like a Raspberry Pi or Mac Mini, and less ideal on a CPU-only VPS. Then I move into workflows: a daily morning brief (now using Tavily Search since Brave killed the free tier), and my personal favorite — an accountability partner that tracks goals in a SQL database with daily check-ins, weekly reviews, and monthly/quarterly retros. From there, I show how to project that database into a dashboard so you can see progress without spending tokens asking the agent to summarize logs. Finally, I cover a self-improving memory setup (I prefer recreating the value with a prompt vs blindly installing skills), a safe OpenClaw update monitor that waits 24 hours and runs health/security checks, and a context file auditor to cut token bloat from every single message.