Skill: fatcatmaofei/mindcore (version 1.0.0)

--- name: mindcore description: > 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. --- # 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 Frequency** — single `BURST_BASE_OFFSET` parameter controls activity ## Integration MindCore outputs standard JSON and is designed for [OpenClaw](https://openclaw.ai) but compatible with any AI Agent framework that supports external signal injection. See `references/INTEGRATION.md` for detailed integration guide. ## File Structure - `main.py` — Entry point and engine loop - `engine/` — Core 5-layer pipeline implementation - `engine_supervisor.py` — Process supervisor for daemon mode - `data/` — Runtime data (sensor state, synapse matrix, memory) - `js_bridge/` — JavaScript bridge for OpenClaw integration ## License AGPL-3.0 (commercial licensing available — contact [REDACTED_SECRET])

path: scripts/data/LongTermMemory.json

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