A specialized tool for sending, caching, and optimizing native Feishu stickers directly via command line or AI agents.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install feishu-sticker
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 feishu-sticker 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 Feishu Sticker Skill?
The Feishu Sticker Skill is a robust extension for the Openclaw Skills ecosystem, designed to streamline how users interact with Feishu (Lark) messaging. It enables the seamless transmission of local images as native stickers, ensuring high performance through intelligent caching and media optimization. By integrating this skill into your workflow, you can automate sticker delivery for notifications, team engagement, or specific bot triggers.
This addition to the Openclaw Skills library handles the technical complexities of media management. It features automatic image uploading to the Feishu CDN, MD5-based file hashing to prevent redundant uploads, and real-time conversion of heavy GIFs into efficient WebP formats using ffmpeg-static. Whether you are building an automated notification bot or looking for a faster way to send visual reactions, this skill provides the necessary infrastructure for modern team communication.
Feishu Sticker Skill Use Cases
- Automating team notifications in Feishu groups using Openclaw Skills to add visual context.
- Sending specific visual alerts or reaction stickers based on CI/CD pipeline results or system triggers.
- Managing a centralized library of stickers that can be searched via CLI by emotion or query.
- Reducing bandwidth and storage costs by automatically converting legacy GIFs to WebP before sending.
How Feishu Sticker Skill Works
- The skill identifies the target image by scanning the local sticker directory or accepting a specific file path provided by the user.
- It calculates an MD5 hash of the image file to check the local cache for an existing image_key, preventing unnecessary uploads.
- If the image is a GIF or exceeds 5MB, the skill utilizes ffmpeg-static to convert or compress the file into an optimized WebP format.
- The optimized media is uploaded to the Feishu CDN using multipart form data, and a unique image_key is retrieved.
- The skill constructs a sticker message payload and dispatches it to the specified Feishu user or group ID via the Lark API.
Feishu Sticker Skill Setup
To get started with this skill in the Openclaw Skills framework, follow these steps:
# 1. Prepare your local sticker repository
mkdir -p ~/.openclaw/media/stickers/
# 2. Navigate to the skill directory
cd skills/feishu-sticker
# 3. Install the necessary technical dependencies
npm install axios commander ffmpeg-static form-data dotenv
Ensure your Feishu bot credentials and STICKER_DIR environment variables are configured in your .env file.
Feishu Sticker Skill Data Schema & Taxonomy
| Component | Description |
|---|---|
| Local Storage | Images are sourced from ~/.openclaw/media/stickers/ or a custom directory. |
| Cache Strategy | MD5 hash-based mapping of local files to remote Feishu image_key identifiers. |
| Media Optimization | Automated GIF to WebP conversion and compression for files over 5MB. |
| Metadata Search | Supports filtering stickers by filename via --query or semantic meaning via --emotion. |
Feishu Sticker Skill Advanced Features
- Intelligent MD5-based caching system to minimize API calls and redundant uploads within the Openclaw Skills environment.
- Native support for ffmpeg-static to handle high-performance media transcoding on the fly.
- Smart search functionality allowing AI agents to find stickers based on natural language queries.
- Robust error handling for Feishu API rate limits and file size constraints.
SKILL.md
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