An automated trend discovery and tracking tool that monitors social platforms with built-in de-duplication and usage history.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install hot-topic-finder
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install hot-topic-finder using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The Hot Topic Finder is a specialized tool designed for creators and marketers to identify and track viral trends across multiple platforms like Weibo, Zhihu, and Douyin. As a part of the Openclaw Skills ecosystem, it provides a centralized way to monitor digital heat, ensuring you never miss a trending conversation. Beyond discovery, it acts as a content manager by tracking which topics you have already addressed, preventing content fatigue and ensuring a fresh stream of ideas.
This skill is particularly valuable for users who need to maintain a high-frequency posting schedule while remaining relevant to current events. By utilizing Python-based automation and local data storage, the Hot Topic Finder offers a professional-grade solution for content research and strategic planning.
To get started with this skill, ensure your environment has the necessary binaries installed. Openclaw Skills usually require minimal configuration beyond dependencies.
# Ensure dependencies are available
sudo apt-get install curl python3
# Find hot topics
python3 scripts/find_topics.py --count 10
# Mark a topic as used to update the history
python3 scripts/mark_topic.py "Topic Name" --heat 560000
The skill maintains its state using a local SQLite database, ensuring all usage logs are persistent and private.
| Data Component | Location / Structure |
|---|---|
| Database Path | ~/.openclaw/data/topic_history.db |
| Tracking Rules | 1 use per 24h, max 2 uses per 7 days, max 3 uses per 30 days |
| Metadata Captured | Topic name, Heat index, Usage timestamp, Source platform |
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