A professional integration skill designed to bridge AI agents with Feishu and Lark workspaces for automated document management, knowledge retrieval, and data tracking.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install openclaw-feishu-workspace
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 openclaw-feishu-workspace using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The Feishu Workspace skill empowers users to interact programmatically with the Feishu and Lark productivity suites. It provides a robust interface for managing team documentation, internal wikis, and structured databases within Bitable. By leveraging Openclaw Skills, teams can automate the creation of meeting notes, maintain knowledge bases, and synchronize project tasks without manual data entry.
This skill is particularly valuable for organizations that rely on Feishu as their primary collaboration hub. It ensures that conversations and insights are immediately translated into structured, readable team artifacts, enhancing overall organizational transparency and operational efficiency.
To begin using this skill within the Openclaw Skills framework, ensure your Feishu/Lark app has the necessary permissions for Docs, Wiki, and Bitable. Use the following configuration steps:
# Configure your Feishu application credentials
export FEISHU_APP_ID="your_app_id"
export FEISHU_APP_SECRET="your_app_secret"
Ensure that the agent has been granted access to the specific document tokens or wiki spaces you intend to manage.
The skill handles data across three primary schemas to ensure compatibility with Feishu API requirements:
| Surface | Data Type | Key Metadata |
|---|---|---|
| Docs | Markdown/Blocks | Document Token, Section ID |
| Wiki | Search Index/Pages | Space ID, Page Token, Parent ID |
| Bitable | Records/Fields | Table ID, View ID, Field Mapping Schema |
All data is processed to be concise and structured, avoiding unstructured walls of text while maintaining metadata integrity.
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