hierarchical-memory

# Hierarchical Memory (Neural Branching)

This skill provides a structured method for managing long-term memory in a multi-layered, branched format to prevent context bloat and ensure high-fidelity recall.

## 🛡️ Security & Transparency
This skill includes a Python script `scripts/add_branch.py`. This script is used solely to:
1. Create directories in your `memory/` folder.
2. Create boilerplate markdown files for new memory branches.
3. Append links to these new files in your existing memory maps.
**It does not perform any network activity, access sensitive system files, or execute external code.**

## Memory Architecture

The memory system is organized into three primary layers:

1.  **Layer 1: Root Memory (`MEMORY.md`)**
    - The central nervous system.
    - Contains high-level context about the partnership, core missions, and global goals.
    - Acts as a map to all other memory layers.

2.  **Layer 2: Domain Memories (`memory/domains/*.md`)**
    - Specialized knowledge silos.
    - Examples: `coding.md`, `trading.md`, `social.md`, `research.md`.
    - Contains domain-specific philosophies, tech stacks, and project indices.

3.  **Layer 3: Project Memories (`memory/projects/*.md`)**
    - Deep-dive details for specific initiatives.
    - Examples: `hesapgaraj.md`, `clawguard.md`, `baa.md`.
    - Contains project status, to-dos, technical specs, and history.

## How to Use This Skill

### 1. Recalling Information
- Always start by searching `MEMORY.md`.
- Follow the "Map" links to the relevant Domain or Project file.
- Use `read` to load only the specific branch needed for the current task.

### 2. Adding New Information
- **New Fact about the Partnership:** Update `MEMORY.md`.
- **New Domain:** Create a new file in `memory/domains/` and link it from `MEMORY.md`.
- **New Project:** Create a new file in `memory/projects/` and link it from its primary Domain file.

### 3. Cross-Referencing
- If a project belongs to multiple domains (e.g., a trading bot that requ...

# Hierarchical Memory (Neural Branching) 🧠🏗️

A modular, multi-layered memory system designed for long-term AI agents to prevent context bloat and ensure high-fidelity recall.

## 🌟 Key Features
- **Neural Branching:** Organize memory into Root, Domain, and Project layers.
- **Recent Delta:** Quick-load mechanism for the last 3-7 days of context.
- **Zombie Prevention:** Mandatory significance markers for every memory branch.
- **Low Latency:** Only load the specific context needed for the current task.

## 🛠️ Structure
```
workspace/
├── MEMORY.md (Root Map)
└── memory/
    ├── domains/ (Coding, Trading, Social, etc.)
    └── projects/ (Project-specific deep dives)
```

## 🚀 How to Use
1. **Initialize:** The skill sets up your base directories.
2. **Add Branch:** Use `scripts/add_branch.py` to create new domains or projects.
3. **Recall:** Start at `MEMORY.md`, follow the link, and `read` the specific branch.

## 📦 Installation
If published on ClawHub:
```bash
clawhub install hierarchical-memory
```
Or manually add the `SKILL.md` to your skills directory.

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*Built with ❤️ by maymun & Balkan.*