High-performance server-side querying and filtering for Feishu Bitable records with multiple output formats.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install feishu-bitable-query
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 feishu-bitable-query 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 Feishu Bitable Query?
The Feishu Bitable Query skill is a robust tool designed for developers working within the Openclaw Skills framework to interact with Feishu (Lark) multidimensional tables. It solves the performance bottlenecks of client-side filtering by pushing logic to the server, allowing for efficient retrieval of specific records from large datasets. This skill is particularly valuable for complex data workflows, providing seamless pagination and data transformation capabilities directly from the command line.
By leveraging this skill, users can bypass the limitations of standard listing tools, gaining the ability to select specific fields, apply sophisticated sorting, and generate human-readable or machine-parsable outputs. It integrates tightly with the Openclaw environment, using centralized authentication to simplify the developer experience.
Feishu Bitable Query Use Cases
- Querying Bitable records with complex conditional filters to minimize context window usage.
- Processing large datasets exceeding 100 records that require automatic pagination.
- Exporting multidimensional table data into TSV or JSONL formats for local analysis or piping into other CLI tools.
- Performing granular time-based filtering on record updates or creation dates.
- Retrieving specific data subsets using existing Bitable View configurations.
How Feishu Bitable Query Works
- The skill authenticates using credentials retrieved from the Openclaw Skills configuration file.
- It accepts parameters for app tokens, table IDs, and filter expressions (Formula or JSON structure).
- Depending on the filter type, it calls the Feishu GET List or POST Search API.
- It automatically manages pagination to fetch all matching records without manual intervention.
- The tool processes and formats the fields (e.g., converting timestamps or flattening user objects).
- Final results are streamed to stdout in the requested format (JSON, JSONL, or TSV).
Feishu Bitable Query Setup
Ensure your Feishu credentials are saved in ~/.openclaw/openclaw.json under the channels.feishu key. No additional manual token generation is required as the script handles authentication automatically.
# Basic usage to fetch all records in a table
python3 scripts/feishu_bitable_query.py --app-token YOUR_APP_TOKEN --table-id YOUR_TABLE_ID --all-pages
# Count records matching a specific formula
python3 scripts/feishu_bitable_query.py --app-token APP --table-id TBL --filter 'CurrentValue.[Status]="Done"' --count
Feishu Bitable Query Data Schema & Taxonomy
The skill includes an automatic field formatter that simplifies complex Feishu data types for better readability and easier processing within the Openclaw Skills ecosystem:
| Field Type | Output Transformation |
|---|---|
| User / Person | Flattens to display name string (e.g., "John Doe") |
| Timestamp | Converts Unix milliseconds to YYYY-MM-DD format |
| Multi-Select | Joins multiple options into a comma-separated string |
| Link / DuplexLink | Extracts the display text of the linked record |
| Standard Fields | Returns raw values for strings, numbers, and booleans |
Feishu Bitable Query Advanced Features
- Server-side formula filtering via the
--filterflag for advanced logical operations. - JSON-based search mode (
--filter-json) for efficient server-side date range queries. - Local Time Filter (
--time-filter) providing advanced relative date syntax (e.g.,14d+for future windows). - Compact output mode via
--compact-fieldsto reduce noise and focus on critical data points. - Support for multiple output formats (TSV, JSON, JSONL) allowing seamless integration with unix pipes and standard data tools.
- Automatic suppression of pagination logs when redirecting stderr, ensuring clean data output.
SKILL.md
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