An automation skill for extracting, summarizing, and analyzing public financial news and hot topics from Caixin.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install caixin
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 caixin using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The Caixin Hot Trend skill is a specialized tool designed for Openclaw Skills to interface with Caixin, one of the most influential financial news platforms. It focuses on the automated retrieval and synthesis of public news, thematic topics, and search results. The skill is engineered to turn unstructured web content into structured data, enabling developers to monitor financial trends without manual browsing.
This skill operates strictly within the boundaries of public access, focusing on lightweight analysis of open pages, channel headers, and search entries. It effectively handles the dynamic rendering requirements of the Caixin website to ensure that all headlines, summaries, and metadata are captured accurately while respecting the platform's rate limits and compliance standards.
To enable this skill within your environment, register it using the following command:
# Register the Caixin Hot Trend skill
clawdbot register caixin-hot-trend
Ensure your Openclaw Skills agent is configured to handle dynamic web rendering for optimal data extraction from the Caixin platform.
The skill organizes extracted news and trend data using the following schema:
| Field | Description |
|---|---|
| Title | The headline of the news article or post. |
| Source | The publishing entity or specific Caixin department. |
| Author | The credited writer (where publically available). |
| Publish Time | Date and time the content was last updated or released. |
| Summary | A brief markdown-formatted excerpt of the main text. |
| Tags | Associated keywords or categorical labels. |
| Link | Direct URL to the public article. |
| Topic/Channel | Metadata identifying the source section (e.g., Finance, Economy). |
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