Deploy files, static sites, and containerized server-side apps to live URLs straight from your AI coding agent, powered by secure Drives for persistent memory.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install dataecho
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 dataecho 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 DataEcho?
The DataEcho skill is an invaluable asset for AI developers using Openclaw Skills to bridge the gap between building software and running it live in production. This tool empowers AI agents to instantly publish anything they generate—be it a single PDF document, a static HTML/CSS/JS frontend, or a complex containerized server-side application. By enabling agents to handle deployment, it streamlines developer workflows, providing live shareable links on demand.
At its core, the skill offers three distinct deployment modes and integration with private cloud Drives for secure session-to-session memory handoffs. It simplifies agent operations by packaging deployments into simple shell scripts or direct REST API calls. Whether it's spinning up an ephemeral static site or deploying a SQLite-backed CRM inside a gVisor sandbox, DataEcho extends the capabilities of Openclaw Skills into robust, production-ready execution environments.
DataEcho Use Cases
- Instant Demo Sharing: A developer asks an AI agent to build a landing page, and the agent automatically hosts it as a live URL to share with stakeholders.
- Full-Stack App Hosting: Hosting database-driven projects like a Python or Node.js CRM by generating a Dockerfile and deploying it as a live container.
- File Sharing & PDF Previews: Uploading generated assets like PDF reports, generated images, or video files with auto-generated rich viewers.
- Agent Memory Handover: Passing data files or progress notes between different agent sessions or multiple collaborative agents using private, versioned cloud Drives.
How DataEcho Works
- Analysis and Mode Selection: The agent determines whether the output is a single file, a static folder, or a full-stack application. If a backend is needed, the agent generates a custom Dockerfile.
- Handshake and Deployment Trigger: The agent executes the bundle scripts (
publish.shorpublish.ps1) or directly invokes the REST API targeting the DataEcho platform. - Content Bundling & Upload: For static sites, a complete snapshot is uploaded; for apps, the workspace is packaged, and the system triggers a secure container build in a gVisor sandbox.
- Routing & CDN Propagation: The platform assigns a unique subdomain (or custom slug) making the site live immediately over HTTPS.
- Claim Handshake: For anonymous deployments, a claim token is stored locally so users can permanently bind the deployment to their account using Openclaw Skills integrations.
DataEcho Setup
To get started with DataEcho, you can install the helper scripts directly into your project directory using the bootstrap commands:
# macOS / Linux (requires bash + python3)
curl -fsSL https://dataecho.ai/install.sh | bash
# Windows (PowerShell equivalent)
irm https://dataecho.ai/install.ps1 | iex
To persist deployments permanently and access cloud drives, configure your API credentials:
# Request authorization code
curl -sS -X POST https://dataecho.ai/api/auth/agent/request-code -H 'content-type: application/json' -d '{"email":"[email protected]"}'
# Exchange verification code for API Key (save key to ~/.artifact/credentials)
echo 'YOUR_API_KEY' > ~/.artifact/credentials && chmod 600 ~/.artifact/credentials
DataEcho Data Schema & Taxonomy
DataEcho relies on specific local artifact structures and environment patterns to govern state:
Local Credential & Claim Files
| Path | Type | Description |
|---|---|---|
~/.artifact/credentials |
Secure Text | Contains the raw API key used for authorized commands and Drives. |
~/.artifact/claims/<slug>.json |
JSON Metadata | Stores the claim token and metadata generated for anonymous site uploads. |
Application Container Environment
- Port Binding: The web application must dynamically listen on
process.env.PORTinstead of hardcoding port values. - Data Persistence: SQLite databases and persistent server state must be saved under the
/datadirectory inside the container to survive redeployments. - Environment Secrets: Variables configured via the API endpoint
/api/v1/me/variablesare automatically injected into your live containers at runtime.
DataEcho Advanced Features
- Containerized Sandbox Environments: Deploys full-stack projects inside secure gVisor sandboxes with isolated CPU and memory allocations.
- Versioned Cloud Drives: Seamless read/write operations with shared tokens using Openclaw Skills, enabling secure, isolated memory handoffs between active agents.
- Automatic Viewer Generators: Serves media, PDFs, and directories via auto-generated viewer pages without requiring manual index.html boilerplates.
- Zero-Dependency Direct REST API: Fully functional fallback utilizing raw HTTP requests (with detailed errors and OpenAPI schemas) for environments lacking Python or Bash runtimes.
SKILL.md
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