Humanizer-ru: Make Russian AI Text Sound Human

Where this fits

You're a developer who ships Russian-language content through an AI agent — product descriptions, support replies, or marketing copy. The output reads fine but feels sterile: perfect grammar, flat rhythm, and telltale phrases like "в современном мире" or "следует отметить". Your user asks, "убери гпт-шность." This is exactly the gap humanizer-ru fills: it detects machine-generated patterns in Russian text and, on explicit request, rewrites it to sound like a native speaker wrote it.

Why agents benefit

• Targeted detection — Scans for known GPT-isms, clichés, and канцелярит (bureaucratic filler) specific to Russian, not just generic repetition or over-polish. It flags phrases that native editors would cut.
• Context-aware rewriting — Rewrites preserve meaning, tone, and intent while restructuring sentences to vary rhythm, add natural connectors, and remove formulaic openings/closings.
• Explicit trigger only — The skill never rewrites unless the user asks. It first reports the problematic spots, then acts on phrases like "очеловечь" or "сделай живым". This keeps control in the user's hands.
• No code execution, no network — Works purely on text with Read/Grep/Glob tools. Safe for agent runtimes that restrict external calls, and it reads only its own markup files.
• Language-bound scope — It correctly refuses to process non-Russian text, source code, legal documents, or fiction. That boundary prevents misuse and keeps output quality high.

Practical scenarios

Content team asks for "less robotic" product pages

Your agent drafts a Russian e-commerce product description. The editor says it sounds like a neural network. The agent runs humanizer-ru, gets a diagnostic list of clichés and over-formal constructions, then rewrites the copy to be more direct and conversational — without losing the SEO keywords.

Support ticket replies need a human touch

A customer complains that the automated response feels canned. The agent applies humanizer-ru to the draft, softening the impersonal passive voice and adding natural empathy markers — while keeping the factual content intact. The reply now reads like a thoughtful human wrote it.

Localization QA catches AI-flavored translations

Your pipeline translates UI strings from English to Russian via an LLM. humanizer-ru acts as a final filter: it flags strings that carry translationese patterns, and your agent rewrites them to match native UI tone. This runs automatically before release.

Add it to your agent workflow

Install via the agent skills CLI:

npx skills add Vladimir-Human/humanizer-ru --skill humanizer-ru

Then in your agent prompt, trigger it naturally:

User: Проверь этот текст на ИИ и убери штампы: "Данный продукт позволяет оптимизировать процессы и повысить эффективность."
Agent: [runs humanizer-ru detection] → "В этом тексте есть два канцеляритных оборота. Переписать?" → User: Да → Agent: "С этим продуктом вы быстрее справитесь с рутиной и сэкономите время."

The skill works with DeepSeek Harness, Claude.ai, Claude Code, opencode, and other agents that follow the agentskills.io spec. See the full humanizer-ru skill page for documentation and examples.

Compare before adopting

Before committing, weigh three things. Quality signals — Does it actually catch Russian-specific patterns beyond generic AI-detection? Test it on your corpus. Maintenance freshness — The README shows a version 3.15.0 with a review date in late 2026; check the GitHub issues for active responses. Alternatives — Compare with general-purpose humanizer prompts or other Russian-focused tools. Also confirm it fits your workflow: it's text-only, no network, so it won't slow down or risk data leaks.

Why it is worth tracking

With 117 stars and a clear scope, humanizer-ru is a niche but active tool for Russian-language AI cleanup. Its versioning and security policy suggest a maintainer who cares about stability. If you regularly generate Russian content, this skill can save hours of manual editing — and it's worth evaluating now, especially since the detection step alone gives you a useful audit of your agent's writing habits.