ru-text
ru-text is an open-source plugin that brings Russian text quality rules directly into AI coding agents. It provides ~1,040 independently formulated rules across 7 domains:
Cost / License
- Free
- Open Source (MIT)
Application type
Platforms
- Cursor
- Notion
- Claude Code
- OpenAI Codex
- OpenClaw
Features
Properties
- Lightweight
- Distraction-free
- Privacy focused
Features
- Syntax Highlighting
- Ad-free
- No registration required
- No Tracking
- No Coding Required
- Dark Mode
- Spell Checking
- AI-Powered
- AI Writing
- Linting
- Typography
ru-text News & Activities
Recent activities
- talkstream liked ru-text
- talkstream added ru-text
- POX updated ru-text
talkstream added ru-text as alternative to Grammarly, LanguageTool, Typopo and Hemingway Editor
ru-text information
Developed by
Arseniy Kamyshev Licensing
Open Source (MIT) and Free product.Alternatives
5 alternatives listedSupported Languages
- English
- Russian
AlternativeTo Categories
AI Tools & Services, Business & Commerce, DevelopmentGitHub repository
- 38 Stars
- 7 Forks
- 0 Open Issues
- Updated
What is ru-text?
ru-text is an open-source plugin that brings Russian text quality rules directly into AI coding agents. It provides ~1,040 independently formulated rules across 7 domains:
— Typography: guillemets, em dashes, non-breaking spaces, digit grouping — Information style: 97 stop-words, reader-first structure, facts over adjectives — Editorial standards: 57 comma traps, pleonasms, capitalization — UX writing: 51 button labels, error messages, empty states, forms — Business correspondence: email structure, messenger etiquette, tone
The plugin auto-activates when the agent writes or edits Russian text — no manual triggering needed. Rules are organized into 9 reference files that load on demand, keeping the context window lean.
Works with Claude Code, Codex CLI, Gemini CLI, Cursor, OpenClaw, and Notion. One codebase, seven platforms.
All rules are independently formulated based on 16 canonical Russian-language sources (Ilyakhov, Gorbunov, Milchin, Nora Gal, and others). No verbatim quotes, full attribution.
Includes /ru-check for manual text audits and /ru-score for a 0.0–10.0 quality score across 5 dimensions.
Free, MIT licensed. No telemetry, no data collection.