by talkstream · Codex Skill · ★ 176
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ru-text Languages: English | Русский Russian text quality plugin for Claude Code, Codex CLI, Gemini CLI, Cursor, OpenClaw, and Notion — typography, information style, editorial standards, UX writing, and business correspondence. 1,040 independently formulated rules informed by 16 canonical Russian-language sources. All formulations are original — no verbatim quotes, full attribution. Acknowledgments This plugin exists because a handful of people decided that Russian text on the internet deserves better. They wrote the books, built the tools, maintained the guides, and set the standards that thousands of editors, writers, and designers now rely on every day. Their work fundamentally changed how Russian text is written, formatted, and read on screens. I am deeply grateful to every one of them. If this plugin saves you time, please buy their books and use their tools — they earned it. What it does ru-text gives your AI coding assistant
| Stars | 176 |
| Forks | 20 |
| Language | Shell |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 74.3113381747823/100 |
| Last Updated | 2026-08-01 |
| Created | 2026-03-28 |
| Platforms | claude-code, cli, codex, gemini |
| Est. Tokens | ~13k |
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ru-text is Russian text quality for AI agents — neuroslop cleanup, typography, information style, editorial standards, UX writing, business correspondence. 2,000+ linguistic atoms, loaded on demand.. It is categorized as a Codex Skill with 176 GitHub stars.
ru-text is primarily written in Shell. It covers topics such as agent-skills, ai-agents, ai-text-detection.
You can find installation instructions and usage details in the ru-text GitHub repository at github.com/talkstream/ru-text. The project has 176 stars and 20 forks, indicating an active community.
ru-text is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to ru-text on Agent Skills Hub include humanizer-ru, humanizer-ru, agent-skills. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.