gemini-editor

Orchestrate two-pass Google Gemini translation reviews with Git audit trails.

2|Updated Jun 7, 2025

Search Tags:#quality assurance #editing #localization #translation #gemini #ai review

Ready to run

npx skills add https://github.com/archetypal-cz/bashkirtseff --skill gemini-editor

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: gemini-editor
Source: https://github.com/archetypal-cz/bashkirtseff/tree/main/.claude/skills/gemini-editor
Command: npx skills add https://github.com/archetypal-cz/bashkirtseff --skill gemini-editor

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill automates the crucial step of AI-driven review for translated texts, ensuring higher quality and consistency across different languages by leveraging a secondary AI model.

Core Features & Use Cases

Dual-Pass AI Review: Performs a text-only review for naturalness and a second review with context for semantic accuracy.
Cross-Model Validation: Catches errors that human editors or the primary translation AI might miss.
Use Case: After a translation is completed and initially edited, this Skill can be dispatched to perform a final AI quality check, flagging any remaining subtle errors before publication.

Quick Start

Run the gemini-editor skill to perform a two-pass AI review on the Czech translations in the 'carnet-001' directory.

Frequently Asked Questions about gemini-editor

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

FAQPage Schema

How does AI translation review work for multilingual quality assurance?▼

AI translation review uses a secondary AI model like Google Gemini to perform a dual-pass check on translated texts. It first evaluates text-only for naturalness, then reviews comments for semantic accuracy to catch subtle errors.

Can I use Google Gemini for automated localization editing and cross-model validation?▼

Yes, you can dispatch this skill to orchestrate an external AI review using Google Gemini. It performs cross-model validation to catch localization errors that the primary translation AI or human editors might have missed.

What is the best way to perform a two-pass AI review on translated texts?▼

The best way to perform a two-pass AI review is running an automated workflow that first checks text for naturalness, then assesses semantic accuracy with context. This skill handles rate limits automatically and logs audit trails via Git commits.

How do I handle rate limits when running automated AI reviews across multiple languages?▼

To handle rate limits during automated AI reviews across multiple languages, this skill manages the retry logic internally. It ensures the dual-pass translation review completes successfully while providing detailed audit trails via Git commits.

Why use cross-model validation for translation quality assurance?▼

Cross-model validation is used for translation quality assurance to catch subtle semantic errors that a primary translation AI might miss. By leveraging a secondary AI model like Gemini, it flags remaining discrepancies before publication.

Do I need Git to track audit trails for AI-powered translation reviews?▼

Yes, Git is used to provide detailed audit trails for AI-powered translation reviews. This ensures that every automated correction and cross-model validation check is tracked and committed for future reference.