A specialized tool to automate the extraction of transcripts, AI summaries, and meeting events from public Tencent Meeting recording links.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install tencent-meeting-export
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 tencent-meeting-export using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
Tencent Meeting Export is a robust utility designed to bridge the gap between cloud-based video recordings and actionable text data. This skill enables developers and researchers to programmatically retrieve full transcription data from Tencent Meeting (腾讯会议) public share links without requiring manual login. By leveraging advanced browser automation, it captures not only the spoken word but also the intelligent metadata generated by the platform.
As a part of the Openclaw Skills library, this tool is essential for teams looking to integrate meeting intelligence into their existing documentation workflows. It specifically handles the complexities of lazy-loading and API interception to ensure that every segment of the conversation, including speaker identification and timestamps, is accurately preserved in developer-friendly formats.
To use this skill from Openclaw Skills, ensure you have Python installed and then set up the Playwright environment:
pip install playwright
playwright install chromium
Run the export script by passing a valid public share link:
python scripts/tencent_meeting_export.py <YOUR_SHARE_LINK>
The exported data is organized into a detailed hierarchy to maintain context and attribution. The primary data points include:
| Element | Description |
|---|---|
| AI Full Summary | The comprehensive summary generated by the platform's AI. |
| Smart Chapters | Theme-based segments with associated timestamps and brief descriptions. |
| Critical Nodes | Log of events such as screen sharing starts/stops and participant entry/exit. |
| Transcript Paragraphs | The core dialogue containing speaker details, start/end timestamps (ms), and the raw text string. |
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