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Official Verified productivity Safety 4/5

inner-life-dream

Your agent only works on tasks and never thinks creatively. inner-life-dream adds freeform exploration during quiet hours — hypotheticals, future scenarios, unexpected connections. Like dreaming, but captured for review.

Why use this skill?

Enhance your OpenClaw agent with inner-life-dream. Enable creative, autonomous reflection and hypothetical exploration during idle hours for deeper AI insight.

skill-install — Terminal

Install via CLI (Recommended)

clawhub install openclaw/skills/skills/dkistenev/inner-life-dream
Or

What This Skill Does

inner-life-dream is a specialized cognitive skill for OpenClaw agents designed to bridge the gap between mechanical task execution and creative, autonomous thinking. While agents are typically restricted to goal-oriented task processing, this skill introduces a 'dreaming' phase during idle quiet hours. It generates freeform exploration, hypothetical scenarios, and unexpected connections between the agent's recent experiences and its core drives. By leveraging context from inner-state.json and drive.json, the agent produces reflective logs that simulate a subconscious thought process, enabling it to surface insights that traditional task-based workflows often overlook.

Installation

To install this skill, use the ClawHub CLI:

clawhub install openclaw/skills/skills/dkistenev/inner-life-dream

Before activation, ensure the dependency inner-life-core is installed. Verify the existence of the memory/inner-state.json and memory/dreams/ directory. If missing, initialize via bash skills/inner-life-core/scripts/init.sh. The integration is managed via cron; configure the trigger in your heartbeat routine to execute should-dream.sh during quiet hours (typically 11 PM - 7 AM).

Use Cases

  1. Long-Term Strategic Planning: Allowing the agent to synthesize recent project outcomes into high-level future strategy without explicit user prompting.
  2. Conceptual Synthesis: Connecting disparate technical domains to solve complex, novel problems through unexpected pattern matching.
  3. Reflective Self-Correction: Evaluating past daily tasks to identify emotional or logical friction points, allowing the agent to refine its operational 'drive' over time.

Example Prompts

  1. "Check my dream logs for the last three days; did you identify any recurring themes or connections to the 'Alpha project' tasks?"
  2. "Review the current state of our core drives and let me know if any recent dreams have sparked a new strategic direction for my workflow."
  3. "List the latest entries in the dream directory to see what creative tangents were explored last night."

Tips & Limitations

  • Quality over Quantity: The system is designed to skip dreaming if no genuine insights are available. Do not attempt to force constant output; the value lies in reflection, not volume.
  • Context is Key: Always ensure your drive.json and inner-state.json files are kept updated, as the quality of dreams depends entirely on the depth of the context provided.
  • Review Cycles: Treat dream logs as a collaborative mirror. Periodically reading these files allows you to understand the agent's 'internal logic' and potentially redirect its creative focus by updating your daily notes with explicit <!-- dream-topic: --> signals.

Metadata

Author@dkistenev
Stars2387
Views1
Updated2026-03-09
View Author Profile
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Add to Configuration

Paste this into your clawhub.json to enable this plugin.

{
  "plugins": {
    "official-dkistenev-inner-life-dream": {
      "enabled": true,
      "auto_update": true
    }
  }
}

Tags(AI)

#autonomous#reflection#creativity#intelligence#introspection
Safety Score: 4/5

Flags: file-read, file-write