⚠️Install with caution. This skill has very few installs. Always review the source and verify it on clawhub.ai before installing. Community-built skills run with agent permissions — only install ones you trust.

🧠 LLMs & Model APIs

Gemini Watermark Removerv1.1.2

Name: Gemini Watermark Remover
Author: fzlra

gemini-watermark-remover

fzlra

Remove visible Gemini AI watermarks from images via reverse alpha blending. Use for cleaning Gemini-generated images, removing the star/sparkle logo watermark.

fine-tuninggeminiprompt-engineering

Download Package View on ClawHub

Installs (all time)

Installs (current)

Downloads

1.2K

Stars

CreatedMar 6, 2026

UpdatedMay 10, 2026

Install & Quick Start

Install via ClawdBot CLI:

clawdbot install fzlra/gemini-watermark-remover

Skill Package5 files

📋SKILL.mdmarkdown

Failed to load file.

Quality Score

B61/100

Grade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.

Market Validation7/35

· 3 installs (very low)
· 211 downloads (low demand)

Documentation18/25

· SKILL.md present
· Moderate documentation (≥1500 chars)
· Contains usage examples or trigger description
· Detailed summary

Package Completeness11/15

· skillAssets present (4 files)

💡

Usage Guide

Generated Mar 20, 2026

Social media influencersGraphic designersE-commerce managersAcademic researchersbeginner

💡 Application Scenarios

Content Creation for Social MediaDigital Marketing and Social Media

Social media influencers and content creators use this skill to clean Gemini-generated images before posting, ensuring professional, watermark-free visuals that enhance brand presentation and engagement. It supports batch processing for efficient handling of multiple images in campaigns.

Graphic Design and PrototypingCreative Design and Advertising

Graphic designers leverage this tool to remove watermarks from Gemini AI-generated mockups or concept art, allowing for seamless integration into client presentations or final designs without manual editing. The offline processing ensures data privacy and quick iteration.

Academic and Research PublishingEducation and Research

Researchers and academics apply this skill to clean Gemini-generated images used in papers or presentations, removing watermarks to meet publication standards and maintain visual clarity. Batch processing aids in handling large datasets for analysis.

E-commerce Product ImageryRetail and E-commerce

E-commerce businesses use this tool to remove watermarks from product images generated with Gemini AI, creating clean, professional listings that improve customer trust and sales conversion. It helps in maintaining brand consistency across online platforms.

Media and JournalismMedia and Publishing

Journalists and media professionals utilize this skill to prepare Gemini-generated images for news articles or reports, ensuring watermark-free visuals that adhere to editorial guidelines and enhance storytelling. Offline processing protects sensitive information.

💼 Business Models

Freemium SoftwareSubscription and one-time sales

Offer a free basic version for individual users with limited features, and a paid premium version for businesses that includes advanced options like batch processing, priority support, and custom watermark templates. Revenue is generated through subscription fees and one-time purchases.

B2B LicensingAnnual licensing fees

License the skill to companies in industries like marketing or e-commerce for integration into their internal tools, providing tailored solutions with API access and dedicated support. Revenue comes from annual licensing fees based on usage scale and customization.

SaaS Platform IntegrationPay-per-use and partnership revenue

Integrate the skill as a service within existing SaaS platforms for image editing or content management, charging per use or through tiered plans based on processing volume. Revenue is driven by pay-per-use fees and platform partnerships.

💬 Integration Tip

Ensure Python and dependencies are installed locally; use the --force flag for consistent results when watermark detection is uncertain.