What is the difference between the 'lark' and 'feishu' MCPs in this skill?

The 'lark' MCP uses tenant access tokens for Bitable and IM notifications, while the 'feishu' MCP uses OAuth user tokens specifically for document and folder management.

Does it support Markdown tables?

Yes, unlike basic converters that use code blocks, this skill converts Markdown tables into native Feishu table blocks, making them fully editable within the cloud space.

How does the skill handle large research diaries?

It implements a partitioning rule that splits diaries by iteration headers and limits volume size to approximately 20KB per part to ensure stability within Feishu's API limits.

How is data consistency maintained during sync?

The skill uses a file-based locking system (sync.lock) to prevent concurrent operations and maintains a registry.json to track the last synced lines and document tokens for incremental updates.

Sibyl Feishu & Lark Sync

Name: Sibyl Feishu & Lark Sync
Author: qcai0427

byqcai0427

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コラボレーションツール

Syncs research project data, documents, and experiment logs from local workspaces to Feishu and Lark cloud environments.

This skill automates the synchronization of research outputs between Sibyl-based development environments and Feishu/Lark cloud spaces. It utilizes a sophisticated dual-MCP architecture to manage folder structures, multi-part research diaries, and complex document formatting, including native tables and Bitable records. By bridging local research logs with enterprise collaboration tools, it ensures team transparency and data persistence for experiment results, reflection reports, and evolving system insights without interrupting the research workflow.

主な機能

01Automated Bitable record management for experiment logs and iteration data

02Incremental synchronization of research diaries with intelligent multi-part partitioning

03Dual MCP integration for Lark (Bitable/IM) and Feishu (Docs/Folders) operations

040 GitHub stars

05Robust concurrency control using a locking mechanism and detailed progress tracking

06Markdown-to-Native Feishu block conversion with dedicated support for native tables

ユースケース

01Maintaining live-updating Bitables of experiment metrics and system evolution logs

02Automating the generation of structured research documentation from local Markdown files

03Publishing ongoing AI research iterations to team-shared Feishu folders for collaborative review

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add qcai0427/sibyl-codex sibyl-lark-sync

For use in Claude.ai and ChatGPT

主な機能

01Automated Bitable record management for experiment logs and iteration data

02Incremental synchronization of research diaries with intelligent multi-part partitioning

03Dual MCP integration for Lark (Bitable/IM) and Feishu (Docs/Folders) operations

040 GitHub stars

05Robust concurrency control using a locking mechanism and detailed progress tracking

06Markdown-to-Native Feishu block conversion with dedicated support for native tables

ユースケース

01Maintaining live-updating Bitables of experiment metrics and system evolution logs

02Automating the generation of structured research documentation from local Markdown files

03Publishing ongoing AI research iterations to team-shared Feishu folders for collaborative review