tiktok-gemini-video-workflow

Automates TikTok product video generation from Feishu Base tasks using Gemini and Flow.

588|92|Updated May 2, 2026
One-click install
npx skills add https://github.com/binggandata/bggg-skills --skill tiktok-gemini-video-workflow
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: tiktok-gemini-video-workflow
Source: https://github.com/binggandata/bggg-skills/tree/main/tiktok-gemini-video-workflow
Command: npx skills add https://github.com/binggandata/bggg-skills --skill tiktok-gemini-video-workflow

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires @larksuite/cli, and includes references (resource) components.

What problem does it solve?

Turning product images and viral reference videos into consistent, trackable TikTok marketing videos requires manual prompt writing, quota juggling across Google accounts, watermark cleanup, and status tracking. This Skill automates that entire pipeline with Feishu Base as the single source of truth.

Core Features & Use Cases

  • Task Queue Management: Reads a Feishu Base for new submissions and human-marked rework tasks, claims records with status locks, and supports resumable multi-segment progress tracking.
  • Storyboard and Prompt Generation: Breaks down viral videos frame by frame, generates one 9:16 3x3 storyboard image per segment, and writes detailed English VIDEO FRAME prompts with timecodes, limb assignments, and continuity rules.
  • Quota Routing and Post-Processing: Routes generation across multiple authorized Google accounts between Gemini and Flow based on live quota checks, removes the Gemini star watermark, restores missing on-screen text hooks, and uploads finished videos back to Feishu for human review.
  • Use Case: An e-commerce team submits a product photo and a viral competitor video through a Feishu form; the Skill claims the task, generates a two-segment 9:16 video with real last-frame continuation, removes the watermark, and returns the finished clips for approval.

Quick Start

Ask the assistant to process the viral video remake tasks in your Feishu Base, confirming the task table, working directory, output directory, and which Chrome profile and Google account to use.

Frequently Asked Questions about tiktok-gemini-video-workflow

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate TikTok video generation from a viral reference video?

Submit a product image and the viral video through a Feishu form linked to the workflow's Base. The Skill breaks down the reference frame by frame, generates a 9:16 storyboard and detailed English video prompts, then submits them to Gemini or Flow and returns the finished clips for review.

How does the workflow handle Gemini and Flow usage limits?

It reads live quota status from the account's settings page rather than assuming fixed limits, rotates across all enabled Gemini accounts first, then falls back to Flow credits. When everything is exhausted it records the recovery text and waits or schedules a resume only with user authorization.

Can I use multiple Google accounts for video generation?

Yes. You register each account with an alias, Chrome profile name, priority, and switching rules in a separate quota table. The workflow polls accounts by priority and last-used time, keeps the same account sticky per task, and logs every switch with reasons.

How are videos longer than one generation segment handled?

Videos up to 15 seconds use one segment and up to 30 seconds use two. The second segment must start from the real extracted final frame of the first segment's downloaded video, combined with the first storyboard and product images to lock continuity.

Does the workflow remove the Gemini watermark from generated videos?

Yes, it uses the open-source gemini-watermark-remover tool, which reconstructs pixels altered by the visible star watermark. It explicitly forbids delogo, blur, mosaic, or cropping as substitutes, and verifies removal by inspecting extracted frames.

What happens when generated videos have missing or garbled on-screen text?

The workflow never relies on the video model to render text hooks. Exact source captions are recorded in a post-production list and added afterward with ffmpeg drawtext or overlay layers, preserving original wording, position, style, and timing before the video can be marked ready for review.