A time-windowed autonomous task queue that separates active daytime work from overnight maintenance cycles for predictable agent behavior.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install autonomy-windowed
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install autonomy-windowed using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
Windowed Autonomy is a specialized framework within the ecosystem of Openclaw Skills designed to transition agents from reactive responders to proactive workers within defined time constraints. By establishing specific operational windows—typically aligned with daytime hours—developers can ensure their agents focus on high-value task queues while reserving nighttime hours for system maintenance, backups, and resource-heavy cron jobs.
This skill is essential for users who require a predictable work schedule and controlled token expenditure. By utilizing Openclaw Skills to manage temporal separation, the agent maintains a clear distinction between autonomous progress and background housekeeping, preventing resource contention and ensuring that autonomous work only occurs when the environment is optimized for it.
To integrate this functionality into your Openclaw Skills environment, configure your queue file and history logs:
tasks/QUEUE.md:## Autonomy Windows
- Daytime: 08:00 - 20:00 UTC -> Autonomy ON
- Overnight: 20:00 - 08:00 UTC -> Autonomy OFF
tasks/MODE_HISTORY.md to monitor window transitions.The skill organizes data across three primary files to maintain state and history:
| File | Purpose | Content Type |
|---|---|---|
tasks/QUEUE.md |
Central task management | Window definitions, Priority list (Urgent to Low), and task state. |
tasks/MODE_HISTORY.md |
Temporal logs | Audit trail of window openings, closings, and tasks completed per session. |
.learnings/ |
Knowledge persistence | Metadata and findings from completed autonomous tasks. |
@priority:urgent to bypass time windows and trigger immediate execution.Loading
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