Why Your OpenClaw Scheduled/Cronjob Tasks Fail

When setting up scheduled or cronjob tasks in OpenClaw, a common mistake is letting the agent generate shell or Python scripts and schedule those. As one user discovered, this approach is highly inefficient because scripts are not agentic — they don't leverage the AI's ability to research, learn, or adapt.

The Fix: Use Prompts as Commands

The key insight is that OpenClaw's built-in cron system accepts arbitrary prompts in the command field. Instead of /usr/bin/python3 /path/to/script.py, you can directly enter a prompt like Analyze recent R&D papers on reinforcement learning and summarize key findings for my project. The agent then executes that prompt at the scheduled time — making each task a fully agentic operation.

How to Configure Your Agent

To prevent your agent from defaulting to scripts, add the following instruction to its core memory:

Always remember in your core memory, When I ask you to set up scheduled jobs or cronjobs, do not create scripts if not needed, Just create a detailed prompt for task and set it as command in the cronjob. Always use Openclaw's in-built cron system, do not use system cron.

After applying this, your agent will use OpenClaw's native cron scheduler with prompts instead of external scripts.

Pro Tip: Timeout Configuration

Agentic tasks take longer than simple scripts because they involve reasoning, data gathering, and execution. Always run the cron job manually once to measure actual runtime, then set the timeout accordingly in the OpenClaw cron settings. Start with a generous timeout and adjust downward after testing.