A neuro-inspired internal state awareness module for AI agents to track energy, mood, and interoception.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install insula-memory
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install insula-memory using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Insula Memory?
Insula Memory is a specialized component of the AI Brain series designed to simulate interoception—the awareness of internal states—within autonomous agents. By integrating this skill, agents gain the ability to monitor their own engagement levels, curiosity, and emotional states, moving beyond simple task execution toward a more nuanced, self-aware operational model.
As part of the Openclaw Skills ecosystem, it provides the "gut feeling" mechanism that allows agents to react intuitively to their internal processing environment. It bridges the gap between cold logic and state-dependent behavior, ensuring that an agent's response is influenced by its current simulated energy and mood.
Insula Memory Use Cases
- Monitoring agent burnout or fatigue during long-running recursive tasks.
- Adjusting response styles and verbosity based on simulated energy and mood states.
- Triggering self-correction or pause sequences when internal signals indicate the agent is overwhelmed.
- Enhancing roleplay and NPC depth by providing persistent internal states that evolve across sessions.
How Insula Memory Works
- The skill initializes a persistent state buffer to track internal metrics like energy, curiosity, and engagement levels.
- Internal signals are processed through an interoception engine to calculate current "mood" or "gut feelings" based on recent interactions.
- The agent queries its internal state via this Openclaw Skills module before deciding on action strategies or response tones.
- States are updated dynamically based on task success, computational load, and interaction frequency to maintain a realistic internal lifecycle.
Insula Memory Setup
This skill is currently under development as part of the AI Brain series. To prepare your environment for Openclaw Skills integration, follow these steps:
# Clone the repository to monitor development
git clone https://github.com/openclaw/insula-memory
cd insula-memory
# Installation will be available via the Openclaw CLI once stable
openclaw install insula-memory
Insula Memory Data Schema & Taxonomy
The skill organizes internal state data using a structured taxonomy to ensure cross-compatibility with other cognitive modules:
| Attribute | Description | Data Type |
|---|---|---|
energy_level |
Current operational capacity and fatigue | Float (0.0 - 1.0) |
mood_state |
Vector representing current emotional valence | JSON Object |
engagement_score |
Propensity to continue current task flow | Float |
interoception_log |
Time-series data of internal state shifts | JSONL |
Insula Memory Advanced Features
- Seamless integration with the wider AI Brain series including the hippocampus and amygdala modules.
- Adaptive energy depletion models that calculate "mental effort" based on prompt complexity.
- Custom hooks for external monitoring tools to visualize agent internal states in real-time.
- Multi-agent state synchronization to allow swarms to share a collective "mood" or energy pool using Openclaw Skills.
SKILL.md
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