ru-text icon
ru-text icon

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:

ru-text screenshot 1

Cost / License

  • Free
  • Open Source (MIT)

Application type

Platforms

  • Cursor
  • Notion
  • Claude Code
  • OpenAI Codex
  • OpenClaw
1like
0articles

Features

Properties

  1.  Lightweight
  2.  Distraction-free
  3.  Privacy focused
  4.  AI-Powered

Features

  1.  Syntax Highlighting
  2.  Ad-free
  3.  No registration required
  4.  No Tracking
  5.  No Coding Required
  6.  Dark Mode
  7.  Spell Checking
  8.  AI Writing
  9.  Linting
  10.  Typography

ru-text News & Activities

Highlights All activities

Recent activities

ru-text information

AlternativeTo Categories

AI Tools & ServicesBusiness & CommerceDevelopment

GitHub repository

  •  233 Stars
  •  25 Forks
  •  1 Open Issues
  •   Updated  
View on GitHub
ru-text was added to AlternativeTo by Arseniy Kamyshev on and this page was last updated .
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Official Links

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.