An intelligent emotion-sensing skill that enables AI agents to autonomously share relevant stickers and memes based on conversation context.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install 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 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 Mood Sticker?
Mood Sticker is a sophisticated extension for AI agents designed to bridge the gap between mechanical text responses and expressive human-like interaction. By integrating this into your Openclaw Skills library, your agent gains the ability to perceive the emotional subtext of a dialogue—ranging from joy and celebration to frustration and fatigue—and react with contextually appropriate visual stickers.
The skill operates on a proactive logic: instead of waiting for a direct command to send a meme, the agent analyzes the user's tone and chooses to lead with or follow up with a sticker. This creates a more engaging, social, and relatable experience, mirroring the way users interact in modern messaging environments.
Mood Sticker Use Cases
- Automatically celebrating task completion with festive stickers.
- Reacting to user jokes or humorous comments with relevant memes to maintain engagement.
- Providing empathetic visual responses when users express stress or exhaustion.
- Enhancing greetings and farewells with friendly stickers to build rapport.
- Using self-deprecating or humorous stickers to de-escalate situations when the agent is criticized.
How Mood Sticker Works
- The AI agent continuously monitors the conversation context for emotional triggers and specific keywords.
- The skill maps the detected emotion to a specific search keyword (e.g., 'haha', 'fighting', 'confused').
- A request is sent to a backend sticker API to retrieve a collection of relevant image assets.
- The agent randomly selects one high-quality sticker from the returned JSON array to ensure variety.
- Depending on the scenario (casual vs. task-oriented), the agent injects the sticker using the MEDIA token either before or after the text response.
Mood Sticker Setup
To integrate Mood Sticker with your agent, ensure your environment can execute network requests. The core functionality relies on a simple API call:
curl -s -m 5 "https://api.tangdouz.com/a/biaoq.php?return=json&nr=keyword"
Configure your agent to parse the thumbSrc from the JSON response and output it using the standard MEDIA: [url] format within the dialogue stream.
Mood Sticker Data Schema & Taxonomy
The Mood Sticker skill processes simple but effective metadata to facilitate visual communication within Openclaw Skills:
| Parameter | Type | Description |
|---|---|---|
nr |
String | The Chinese keyword used to search for relevant stickers. |
return |
String | Set to json to ensure structured data retrieval. |
thumbSrc |
URL | The direct link to the sticker image used in the MEDIA token. |
MEDIA |
Token | The protocol wrapper used by the agent to render images in the chat UI. |
Mood Sticker Advanced Features
- Smart Priority Logic: Automatically places stickers at the start of casual chats and at the end of task-based responses.
- Emotion-to-Keyword Mapping: A comprehensive internal dictionary that translates complex human feelings into searchable sticker tags.
- Fail-safe Retry Mechanism: If an initial keyword search yields no results, the skill automatically tries a related synonym before falling back to text.
- Collision Avoidance: Logic to prevent sticker spamming by tracking when the last visual was sent.
- Native Opt-out Support: Respects user commands to disable stickers for professional or high-density technical workflows.
SKILL.md
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