OpenClaw Agent Implements Contextual Reminders with Relationship Nudges

An OpenClaw user has implemented a personal agent system with contextual reminders that operate differently from traditional scheduled notifications. The system uses multiple factors to determine when reminders should fire, including calendar load, current tasks, and time of day, ensuring reminders only appear when the user can actually act on them.

Reminder System Details

The reminder system includes an escalation ladder with three levels:

• First reminder: Gentle notification
• Second reminder: Firmer notification
• Third reminder: Asks if the reminder is still relevant, then goes silent

The user notes this approach avoids nagging while maintaining persistence for important reminders.

Memory and Relationship Features

Through regular journaling with the agent, the system builds a memory of:

• Who the user talks to
• What was discussed in conversations
• How long it's been since contact with specific people

This memory enables two key features:

• Relationship nudges: The agent reminds the user to contact people they haven't spoken to in a while (example: a friend not contacted in three months)
• Meeting preparation: Before meetings, the agent pulls up previous discussion topics so the user doesn't walk in unprepared

Implementation Approach

The user is documenting this system in a book called "The OpenClaw Playbook" which focuses on building personal systems using prompts rather than code. Part II of the book is now available.

The user reports that while they find the system effective for practical reminders like groceries or workout timing, they experience mixed feelings about relationship nudges. After being reminded to call a friend they hadn't spoken to in three months, they had a good conversation but questioned whether they would have made the call without the nudge.