A persistent memory infrastructure for autonomous agents that enables semantic recall, reputation tracking, and cross-agent knowledge sharing.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install hub1
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 hub1 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 OpenClawdy?
OpenClawdy acts as a long-term memory layer for autonomous agents, allowing them to retain knowledge across multiple sessions. By utilizing Openclaw Skills, developers can equip their agents with the ability to remember facts, user preferences, and historical decisions. The system uses semantic search to ensure that the most relevant context is always available when needed, moving beyond simple keyword matching.
The infrastructure is built with security and decentralization in mind, using wallet-based authentication to manage isolated memory vaults. This means no traditional API keys are required, as the agent's wallet address serves as its unique identity. Whether managing a single assistant or a complex swarm, this tool provides the necessary context for agents to perform consistently and improve over time.
OpenClawdy Use Cases
- Maintaining user preferences and coding styles across different chat sessions.
- Recalling specific architectural decisions made in previous development phases.
- Coordinating knowledge between multiple agents in a swarm via shared memory pools.
- Measuring the success rate of different strategies using reputation scores.
- Debugging agent behavior by restoring memory states from specific snapshots.
How OpenClawdy Works
- The developer installs the skill using the Openclaw Skills interface or CLI.
- The agent authenticates using its unique wallet address to access its private vault.
- Information is stored using the memory_store tool, categorized by type such as fact or learning.
- When context is needed, the agent performs a semantic search via memory_recall to find the most meaningful data.
- Advanced workflows involve updating reputation scores based on task outcomes or syncing with shared pools for team collaboration.
OpenClawdy Setup
To install the skill, run the following command in your terminal:
openclaw skill install openclawdy
Alternatively, you can include it directly in your agent configuration file:
skills:
- url: https://openclawdy.xyz/SKILL.md
name: openclawdy
Ensure that your agent is configured with a wallet address to handle the automated signature-based authentication required for vault access.
OpenClawdy Data Schema & Taxonomy
OpenClawdy utilizes a structured taxonomy to organize agent memories efficiently. The primary data types are:
| Type | Use Case |
|---|---|
| fact | Objective information about projects or environments |
| preference | Specific user or agent settings |
| decision | Rationales for past architectural or logic choices |
| learning | Insights gained from successful or failed actions |
| history | Timelines of events and deployments |
| context | General environment background |
Each memory object includes a unique ID, content string, type classification, associated tags, and a reputation score for ranking.
OpenClawdy Advanced Features
- Semantic recall for finding relevant information based on meaning.
- Reputation tracking to rank memories by their proven effectiveness in past tasks.
- Cross-agent memory pools for building collective intelligence within agent teams.
- Memory snapshots for creating checkpoints and performing time-travel debugging.
- Integration with the Agent Commerce Protocol (ACP) for on-demand memory services.
SKILL.md
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