A sophisticated dual-module memory and knowledge management system designed to give AI agents long-term recall and structured expertise.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install hita-mind-knowledge
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 hita-mind-knowledge 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 Hita Mind and Knowledge?
Hita Mind and Knowledge is a robust system developed by hita to solve the problem of context loss and knowledge fragmentation in AI agents. By utilizing a dual-module architecture, it allows Openclaw Skills to distinguish between behavioral patterns and factual knowledge. The Mind Module focuses on the 'who' and 'how' (preferences, habits, decisions), while the Knowledge Manager focuses on the 'what' and 'where' (skills, rules, documentation).
This framework is essential for developers building persistent agents that need to remember past interactions and apply learned methodologies consistently over time. By integrating this system into your Openclaw Skills workflow, you create a more reliable and intelligent autonomous agent that grows more capable with every interaction.
Hita Mind and Knowledge Use Cases
- Personalizing AI agent behavior based on user-specific preferences and historical habits.
- Storing and retrieving project-specific decisions and causality patterns to maintain consistency across long-term development cycles.
- Managing complex technical documentation and methodologies across three hierarchical layers of data accessibility.
- Building a persistent expertise base for Openclaw Skills to reference during specialized coding, research, or automation tasks.
How Hita Mind and Knowledge Works
- The system ingests new information and automatically routes it to either the Mind Module or the Knowledge Manager based on the nature of the data.
- The Mind Module categorizes behavioral data into one of eight specific domains, such as decision-making patterns, causality, or project feedback.
- The Knowledge Manager evaluates the frequency of use and importance of factual data, moving it into L1 (Hot), L2 (Warm), or L3 (Cold) storage tiers.
- When a user triggers a query (e.g., 'check my memory'), the agent searches the indexed metadata to retrieve relevant context.
- The retrieved memory is injected into the agent's current prompt context, enabling informed and context-aware responses within Openclaw Skills.
Hita Mind and Knowledge Setup
To get started with Hita Mind and Knowledge, you need to initialize both the memory and knowledge modules separately.
# Initialize and list memories in the Mind Module
cd hita-mind-module && node index.js list
# Initialize and list items in the Knowledge Manager
cd hita-knowledge-manager && node index.js list
Hita Mind and Knowledge Data Schema & Taxonomy
The system organizes data into two primary structures to optimize for both retrieval speed and storage capacity.
Mind Module Taxonomy
- Decisions / Preferences: Stores user choices and behavioral leanings.
- Patterns / Causality: Tracks recurring events and cause-and-effect relationships.
- Contacts / Feedback: Manages relationship data and iterative improvements.
- Projects / Daily: Tracks active work contexts and daily logs.
Knowledge Manager Hierarchy
| Layer | Type | Capacity | Content Detail |
|---|---|---|---|
| L1 | Hot Data | 50 Items | Full content storage for immediate access |
| L2 | Warm Data | 200 Items | Summaries and tags for efficient searching |
| L3 | Cold Data | Unlimited | Metadata indexing for archival retrieval |
Hita Mind and Knowledge Advanced Features
- Intelligent three-tier storage optimization (L1/L2/L3) to manage large datasets without slowing down agent performance.
- High-granularity classification using an eight-dimensional memory system for precise context retrieval.
- Native support for Openclaw Skills integration, facilitating cross-agent knowledge sharing.
- Scalable metadata indexing for L3 cold storage, allowing agents to maintain an 'infinite' knowledge base over time.
SKILL.md
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