OpenClawdy is a memory infrastructure for autonomous agents providing persistent storage, semantic recall, 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 openclawdy
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 openclawdy 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 provides a robust memory layer designed specifically for autonomous agents, ensuring that facts, preferences, and decisions survive across sessions. By leveraging vector databases and semantic search, it allows agents to recall relevant information based on meaning rather than just keyword matches. This is a critical addition to the ecosystem of Openclaw Skills, enabling more consistent and personalized agent behaviors.
The service utilizes wallet-based authentication to ensure that each agent has its own isolated memory vault. This privacy-first approach, combined with the ability to store structured data like reputation and decision history, makes it an essential tool for developers building sophisticated, long-running agentic workflows.
OpenClawdy Use Cases
- Maintaining long-term user preferences and coding styles across disparate sessions.
- Implementing shared knowledge bases for agent swarms using cross-agent memory pools.
- Auditing and debugging agent decision-making processes through time-travel snapshots.
- Optimizing agent performance by retrieving memories based on proven reputation and success rates.
How OpenClawdy Works
- The agent authenticates by signing a timestamp message with its wallet to verify ownership without exposing private keys.
- Stored information is processed and indexed in a managed vector database for high-speed semantic retrieval.
- The agent uses semantic queries to recall the most relevant context, facts, or past decisions for a given task.
- Advanced operations allow agents to snapshot their state or update the reputation of specific memories based on task outcomes.
OpenClawdy Setup
To install this skill using the CLI, run the following command:
openclaw skill install openclawdy
Alternatively, you can add it to your agent configuration file manually:
skills:
- url: https://openclawdy.xyz/SKILL.md
name: openclawdy
OpenClawdy Data Schema & Taxonomy
OpenClawdy organizes information into specific taxonomies to optimize how agents process and retrieve knowledge. This structure is supported within the Openclaw Skills framework for maximum interoperability:
| Type | Use Case | Example |
|---|---|---|
| fact | Objective data points | "The production server uses Node.js v20" |
| preference | User or agent settings | "User prefers documentation in Markdown" |
| decision | Records of past choices | "Chose Vite over Webpack for build speed" |
| learning | Insights gained over time | "The legacy API requires a specific Auth header" |
| history | Timeline of events | "Version 1.2.0 was deployed on Friday" |
| context | Active project details | "Currently refactoring the auth module" |
OpenClawdy Advanced Features
- Memory Reputation Tracking: Store and recall memories based on their effectiveness and success rates in previous tasks.
- Cross-Agent Memory Pools: Create shared intelligence layers where multiple agents can contribute to and learn from a collective pool.
- Time-Travel Snapshots: Version agent memory states to allow for debugging, comparison, and restoration of previous knowledge bases.
- Semantic Search: High-precision retrieval using vector embeddings to find memories by intent and meaning rather than keywords.
SKILL.md
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