auto-drive for Openclaw

A decentralized storage and memory chain skill for AI agents that ensures permanent history through linked-list CIDs on the Autonomys Network.

emilfattakhov
v1.0.4
Feb 28, 2026
1
1.7k
0

Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install auto-drive

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

Copy this prompt to OpenClaw to install it automatically.

Help me install auto-drive 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 auto-drive?

The auto-drive skill is a specialized extension for Openclaw Skills designed to provide AI agents with permanent, immutable memory. By leveraging the Autonomys Network, it allows agents to store their identity, decisions, and context as a memory chain. This decentralized approach ensures that even in the event of total state loss, an agent can be resurrected by walking back through its linked-list history from a single Content Identifier (CID).

This skill is essential for developers building long-lived agents that require a verifiable and indestructible record of their experiences. It supports all major LLMs including Claude, GPT, and Gemini by providing a standardized way to interface with decentralized storage. By integrating this into Openclaw Skills, agents gain a persistent 'soul' that exists independently of the local file system.

auto-drive Use Cases

  • Creating permanent checkpoints for agent state and configuration.
  • Storing and retrieving large files or documents via immutable CIDs on a decentralized network.
  • Reconstructing an agent's full interaction history from a single head CID (Resurrection).
  • Documenting decision-making processes in a verifiable, linked-list JSON format.
  • Anchoring agent identity across multiple sessions or different hardware environments using Openclaw Skills.

How auto-drive Works

  1. The agent identifies data or files that need to be persisted permanently.
  2. The skill uploads the content to the Autonomys Network using a 3-step upload protocol, returning a unique CID.
  3. Each new memory entry is wrapped in a structured JSON header containing a pointer to the previous CID.
  4. This link forms a continuous chain of experiences stored on the decentralized network.
  5. To restore memory, the agent provides the latest CID, and the skill walks the chain backwards to rebuild the complete context.

auto-drive Setup

To get started with this skill within the Openclaw Skills ecosystem, follow these steps:

# Navigate to the skill directory and make scripts executable
chmod +x skills/auto-drive/scripts/*.sh

# Run the guided setup script to configure your environment
scripts/setup-auto-drive.sh

You will need to obtain an AUTO_DRIVE_API_KEY from the Autonomys explorer. The setup script will assist in saving this to your environment configuration.

auto-drive Data Schema & Taxonomy

The skill organizes memory using the Autonomys Agents header/data structure to ensure compatibility and easy traversal:

Key Description
header.agentName The identifier for the agent (default: openclaw-agent).
header.previousCid The CID of the previous experience in the chain.
header.timestamp ISO-8601 formatted string of the storage time.
data.type The classification of the stored data (e.g., 'memory').
data.content The actual payload, which can be a string or structured JSON.

auto-drive Advanced Features

  • Auto-Pinning: Automatically updates a MEMORY.md file in the workspace with the latest head CID for easy tracking.
  • Chain Resurrection: Support for walking the linked list backwards up to a specified limit to restore agent context.
  • Compression Support: Optional ZLIB compression for uploads to optimize storage efficiency and manage API limits.
  • Multi-Agent Headers: Support for unique agent names and versions within the memory chain metadata.
  • On-Chain Anchoring: Designed to work with the Autonomys EVM for permanent head CID storage, enabling recovery without local state.

SKILL.md


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