A persistent, research-backed memory system that allows OpenClaw agents to retain context, decisions, and preferences across multiple sessions.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install agent-memory-ultimate
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 agent-memory-ultimate 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 Agent Memory Ultimate?
Agent Memory Ultimate is a sophisticated local memory layer designed to solve the common goldfish memory problem in AI agents. Built specifically for Openclaw Skills, it leverages semantic vector search and a two-tier indexing system to ensure your agent remembers architectural decisions, personal preferences, and project details without requiring manual re-explanation every time you start a new thread.
Unlike standard context window management that loses information during compaction, this skill uses biologically-inspired architectures based on the HIPPOCAMPUS and ENGRAM research papers. This ensures that critical facts are preserved through a local SQLite database, providing a seamless experience where the agent evolves alongside your workflow. It functions entirely offline, ensuring that your sensitive project data never leaves your machine while providing a significant reduction in token usage by loading only the most relevant historical context.
Agent Memory Ultimate Use Cases
- Retaining architectural decisions and tech stack preferences across long-term development projects.
- Maintaining awareness of team members, project stakeholders, and personal preferences without repetition.
- Reducing token costs in high-volume environments by implementing intelligent context retrieval instead of full history dumping.
- Ensuring continuity in multi-session workflows where standard context compaction usually destroys thread history.
How Agent Memory Ultimate Works
- The skill captures user inputs and agent responses in real-time during an active session.
- It computes vector embeddings locally and stores them in a structured SQLite database for persistence.
- When a new prompt is received, the system performs a semantic search to identify relevant past memories or decisions.
- The consolidation engine distinguishes between temporary chat logs and permanent facts to determine what should be long-term.
- A natural decay algorithm deprioritizes old, irrelevant data while promoting frequently accessed information to the top of the cache.
- Relevant context is injected into the current session dynamically, allowing the agent to recall previous interactions accurately.
Agent Memory Ultimate Setup
Ensure you have sqlite3 installed on your system. This skill is compatible with Linux and macOS environments.
# Install sqlite3 if not present (example for macOS)
brew install sqlite3
# Clone the repository containing the skill
git clone https://github.com/globalcaos/clawdbot-moltbot-openclaw.git
# Navigate to the skills directory
cd clawdbot-moltbot-openclaw/skills/agent-memory-ultimate
Agent Memory Ultimate Data Schema & Taxonomy
The skill organizes data within a local SQLite database to ensure persistence and user privacy.
| Table | Description | Key Fields |
|---|---|---|
| memories | Stores raw text and memory metadata | id, content, timestamp, type |
| embeddings | Stores local vector representations | memory_id, vector_data |
| index | Two-tier lookup index for fast retrieval | keyword, memory_id, weight |
| decay_log | Tracks access frequency and memory health | memory_id, last_accessed, score |
Agent Memory Ultimate Advanced Features
- Research-backed HIPPOCAMPUS architecture providing O(1) concept lookup capabilities.
- ENGRAM-based context compaction that preserves detail through cache eviction rather than lossy summarization.
- Fully offline local processing ensuring zero data exfiltration for high-security development environments.
- Intelligent token optimization reducing context overhead by 60% to 80% per session.
- Native compatibility and seamless integration with other Openclaw Skills to create a unified agent experience.
SKILL.md
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