An advanced associative memory skill that builds and maintains complex relationships between facts and entities across long-form interactions.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install neural-note-taker
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 neural-note-taker 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 Neural Note Taker?
Neural Note Taker is a sophisticated memory enhancement skill designed to help AI agents manage dense information. By implementing a specialized concept-linkage protocol, this skill ensures that context is never lost, even during extended sessions or complex workflows. It acts as a bridge for your agent to connect disparate pieces of information into a cohesive knowledge web, making it a vital component for those looking to expand the capabilities of their Openclaw Skills.
This skill transforms raw data into a structured graph of interconnected entities. It identifies project names, technical tools, and key dates, then maps the relationships between them to provide a more human-like understanding of context. By preserving these links, the agent can recall not just individual facts, but the entire situational framework they belong to.
Neural Note Taker Use Cases
- Managing complex research projects where relationships between entities are critical for success.
- Maintaining deep project context across long-duration development and coding sessions.
- Linking specific technical tools to project requirements and historical timelines.
- Building a persistent personal knowledge base that evolves alongside your interactions with Openclaw Skills.
How Neural Note Taker Works
- The skill monitors the active chat stream to automatically identify and extract entities like names, tools, dates, and projects.
- It applies a relationship mapping protocol using specific notation to define how different concepts relate to one another.
- A context weighting algorithm assigns priority to specific nodes based on how frequently they recur in conversation.
- Users can interact with the memory graph directly through commands to force new connections or query existing associations.
Neural Note Taker Setup
To add this capability to your environment, execute the following command in your terminal:
clawhub install neural-note-taker
After installation, the skill begins monitoring for entity identification and relationship mapping automatically.
Neural Note Taker Data Schema & Taxonomy
The skill organizes data through an associative graph structure. It tracks nodes and their links using the following metadata taxonomy:
| Attribute | Description |
|---|---|
| Entity | The primary identifier, such as a project name, tool, or person. |
| Relation | The directional link between entities using concept-linkage notation. |
| Weight | A priority score calculated based on the recurrence of the entity. |
| Timestamp | The most recent occurrence or reinforcement of the specific connection. |
Neural Note Taker Advanced Features
- Force manual connections in long-term memory using the
memo_linkcommand for precise knowledge mapping. - Surface all associated nodes for a specific topic instantly via the
memo_queryfunctionality. - Automated context weighting ensures that the most relevant information remains at the forefront of the agent's awareness.
- Persistent memory architecture that maintains complex knowledge graphs across multiple Openclaw Skills sessions.
SKILL.md
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