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mindcore

Biomimetic emotional mind engine for AI Agents. Provides human-like emotional responses through a 5-layer neural conduction pipeline (L0 Stochastic Noise → L1 Sensor Perception → L2 Subconscious Impulses → L3 Personality Gate → L4 Decision Output) plus 5 psychodynamic patches. Fully decoupled from any LLM — runs locally on CPU with pure Python. Simulates 150 daily impulses across 9 categories with circadian rhythms, mood modulation, and short-term memory influence.

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Installation

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Skill instructions

MindCore — Biomimetic Subconscious Engine

Give your AI agent autonomous thoughts, emotions, and spontaneous impulses.

What It Does

MindCore is a standalone background daemon that simulates a subconscious mind. It rolls dice every second, modeling the random emergence of thoughts like "I want milk tea", "I'm bored", or "I suddenly want to chat".

When a thought's probability accumulates past the firing threshold, the engine outputs a JSON signal telling your AI Agent: "I have something to say."

Architecture

Layer 0: Noise Generators (3000 nodes)
    ├── Pink Noise (1/f, long-range correlation)
    ├── Ornstein-Uhlenbeck (physiological baseline)
    ├── Hawkes Process (emotional chain reaction)
    └── Markov Chain (attention drift)
         ↓
Layer 1: Sensor Layer (150 sensors)
    ├── Body State (hunger/fatigue/bio-rhythms)
    ├── Environment (time/weather/noise)
    └── Social Context (interaction/neglect)
         ↓
Layer 2: Impulse Emergence (150 impulse nodes)
    ├── Synapse Matrix (sensor → impulse mapping)
    ├── Sigmoid Probability + Mood Modulation
    └── Dice Roll → Random Firing
         ↓
Layer 3: Personality Gate (Softmax Sampling)
    ├── Learnable Personality Weights
    └── Short-Term Memory Topic Boost
         ↓
Layer 4: Output Template → JSON signal

Quick Start

# Install dependencies
pip install -r requirements.txt

# Start the engine
python main.py

Requires Python 3.8+. On first run, automatically downloads all-MiniLM-L6-v2 local NLP model (~80MB) for synapse matrix generation.

Key Features

  • 150 Daily Impulses across 9 categories (food, social, entertainment, etc.)
  • Stochastic, Not Scheduled — Pink Noise + Hawkes Process + Sigmoid probability
  • Circadian Rhythms — real clock-driven hunger/thirst/sleep cycles
  • Short-Term Memory — 5-slot FIFO buffer with 2-hour exponential decay
  • Mood Baseline — continuous valence modulation of impulse probability
  • **Tunable F...

Source information

Source
github
Repository
openclaw/skills
Path
skills/fatcatmaofei/mindcore
Version
—
Commit
8d175737eb5940f7238b4b1b1dc0270a92d270f5
Classification source
rules
Status
active
Visibility
public

These signals come from indexed source analysis and may lag behind changes. Check the current source files.

Extracted content

SKILL.md
# MindCore — Biomimetic Subconscious Engine

> Give your AI agent autonomous thoughts, emotions, and spontaneous impulses.

## What It Does

MindCore is a standalone background daemon that simulates a **subconscious
mind**. It rolls dice every second, modeling the random emergence of thoughts
like *"I want milk tea"*, *"I'm bored"*, or *"I suddenly want to chat"*.

When a thought's probability accumulates past the firing threshold, the engine
outputs a JSON signal telling your AI Agent: **"I have something to say."**

## Architecture

```
Layer 0: Noise Generators (3000 nodes)
    ├── Pink Noise (1/f, long-range correlation)
    ├── Ornstein-Uhlenbeck (physiological baseline)
    ├── Hawkes Process (emotional chain reaction)
    └── Markov Chain (attention drift)
         ↓
Layer 1: Sensor Layer (150 sensors)
    ├── Body State (hunger/fatigue/bio-rhythms)
    ├── Environment (time/weather/noise)
    └── Social Context (interaction/neglect)
         ↓
Layer 2: Impulse Emergence (150 impulse nodes)
    ├── Synapse Matrix (sensor → impulse mapping)
    ├── Sigmoid Probability + Mood Modulation
    └── Dice Roll → Random Firing
         ↓
Layer 3: Personality Gate (Softmax Sampling)
    ├── Learnable Personality Weights
    └── Short-Term Memory Topic Boost
         ↓
Layer 4: Output Template → JSON signal
```

## Quick Start

```bash
# Install dependencies
pip install -r requirements.txt

# Start the engine
python main.py
```

Requires Python 3.8+. On first run, automatically downloads `all-MiniLM-L6-v2`
local NLP model (~80MB) for synapse matrix generation.

## Key Features

- **150 Daily Impulses** across 9 categories (food, social, entertainment, etc.)
- **Stochastic, Not Scheduled** — Pink Noise + Hawkes Process + Sigmoid probability
- **Circadian Rhythms** — real clock-driven hunger/thirst/sleep cycles
- **Short-Term Memory** — 5-slot FIFO buffer with 2-hour exponential decay
- **Mood Baseline** — continuous valence modulation of impulse probability
- **Tunable F...

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