A powerful integration that enables AI agents to losslessly compress and optimize PNG and JPEG images using the TinyPNG API via Openclaw Skills.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install tinypng
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 tinypng 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 TinyPNG Skill for AI Agents?
TinyPNG is a premier service designed to reduce the file size of images without sacrificing visual quality. By leveraging Openclaw Skills, developers can integrate this capability directly into their AI agent workflows, ensuring that web assets and application images are perfectly optimized for performance. This skill facilitates seamless interaction with the TinyPNG API, handling complex tasks like authentication and credential management automatically through the Membrane framework.
This integration allows agents to manage image optimization tasks programmatically, improving page load times and reducing storage costs. By using Openclaw Skills for TinyPNG, users benefit from a standardized interface that simplifies the often cumbersome process of managing API keys and manual image uploads, making it an essential tool for developers and designers alike.
TinyPNG Skill for AI Agents Use Cases
- Automated image optimization during web development cycles using Openclaw Skills.
- Reducing bandwidth consumption for media-heavy applications and mobile apps.
- Improving website SEO and core web vitals by compressing large JPEG and PNG files.
- Integrating image compression steps directly into automated CI/CD pipelines.
- Managing bulk image optimization tasks through conversational AI interfaces.
How TinyPNG Skill for AI Agents Works
- Install the Membrane CLI and authenticate your session to manage Openclaw Skills effectively.
- Establish a secure connection to the TinyPNG service using the connection ensure command.
- Monitor the connection status until it reaches a READY state, following any prompts for browser-based authentication.
- Discover available compression and optimization actions by searching for specific intents through the CLI interface.
- Execute image optimization actions or perform direct API proxy requests to process image data and retrieve compressed assets.
TinyPNG Skill for AI Agents Setup
To get started with TinyPNG for Openclaw Skills, follow these installation steps:
Install the Membrane CLI:
npm install -g @membranehq/cli@latest
Authenticate your agent (replace
membrane login --tenant --clientName=openclaw
Connect to TinyPNG:
membrane connection ensure "https://tinypng.com/" --json
Wait for the connection to be ready:
npx @membranehq/cli connection get <id> --wait --json
TinyPNG Skill for AI Agents Data Schema & Taxonomy
The skill organizes its operations through the following metadata structure:
| Property | Description |
|---|---|
| Connection ID | A unique identifier for the authenticated TinyPNG session. |
| Action Schema | Defines the inputs (e.g., image URL) and outputs (e.g., optimized URL) for specific tasks. |
| Input JSON | Parameters passed to actions, including file paths or source data. |
| Proxy Parameters | Supports standard HTTP methods (GET, POST) for direct API interaction. |
| State | Tracks the readiness of the Openclaw Skills connection (READY, BUILDING, etc.). |
TinyPNG Skill for AI Agents Advanced Features
- Transparent credential refresh ensuring uninterrupted Openclaw Skills workflows without manual re-login.
- Direct API proxy requests allow for custom endpoints beyond the standard pre-built actions.
- Multi-agent support optimized for platforms like openclaw, claude, and windsurf.
- Machine-readable JSON output for all commands to facilitate complex automation and scripting.
- Built-in error handling and status polling for headless environment compatibility.
SKILL.md
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