Feishu Bitable Smart Import

Problem

Teams often need to move data exported from data warehouses, BI tools, CRM systems, or ERP systems into Feishu Bitable. Manual copy-paste can miss rows or shift columns, recurring reports require repeated imports, and hand-built field types may not match later analysis. feishu-bitable-import targets this local-file-to-Feishu sync problem: turning CSV, Excel, and JSON files into structured, collaborative table data.

How It Works

The skill analyzes fields first, then applies a sync strategy based on the business case. Key capabilities include:
- Type inference: infers Feishu field types from numeric, date, single-select, multi-select, link, and phone-number patterns.
- Sync modes: incremental update for records keyed by primary values; full overwrite for scheduled reports; append-only for log-style growth.
- Table creation: creates a table and fields from the source structure instead of manual setup.
- Resilience handling: retries on API throttling or network timeouts, skips malformed rows when possible, and surfaces permission or format errors.

A typical flow is: configure Feishu app permissions and .env, load the source file, analyze the data structure, choose a sync mode, run the import, and review the result report.

Boundaries and Notes

It fits teams that have stable structured data and need regular synchronization into Feishu Bitable. If the source schema changes often, field semantics are unclear, or app permissions are missing, clean the data and fix the Feishu app setup first. Full overwrite replaces existing data, incremental sync depends on usable matching rules, and production runs should be validated on a small sample.