Agent skill

Ru Check

by talkstream in talkstream/ru-text

Full Russian text quality check against the whole corpus. An agent skill from talkstream/ru-text.

MITAuto-check passedWriting & Content

Install Ru Check

skills CLI
$ npx skills add talkstream/ru-text --skill ru-check -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install talkstream/ru-text ru-check --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/talkstream/ru-text.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ru-check .claude/skills/ru-check && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
ru-check
GitHub stars
254
Used in
1 other repo
Token cost
~2.6k tokens
SKILL.md length
1,504 words
Files
1
Skills in repo
3
Repo updated
First seen
Licence
MIT

At a glance

Full Russian text quality check against the whole corpus. An agent skill from talkstream/ru-text.

  • Works in 3 steps: The ru-text SKILL.md — its inline… → The «Neuroslop index» section of… → Section «B. Каталог стоп-слов» of…
  • The user asks to proofread Russian text
  • SKILL.md covers Where the reference files live, Two depths, one command, Check order and Output format
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Ru Check is an agent skill from talkstream/ru-text. Full Russian text quality check against the whole corpus. Triggers: вычитай, вычитай через ru-text, прогони ru-text, проверь текст по ru-text, ru-check, полная вычитка. Use when the user asks to proofread Russian text, or when a project gate names ru-text. Returns findings with the rule behind each and a proposed replacement; never edits a file. Self-initiated runs start with a fast triage and escalate on evidence; an explicit request always runs the full corpus.

Its SKILL.md is about 2.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Writing & Content, covering Copy editing and proofreading and Typography. It works with Notion. The repository describes itself as: Russian text quality for AI agents — neuroslop cleanup, typography, information style, editorial standards, UX writing, business correspondence. Scores text 0–10. 2,000+… The licence is MIT.

When your agent uses it

  • The user asks to proofread Russian text
  • A project gate names ru-text

Example prompts

  • “/ru-check”

Requirements

  • Pre-approved tools (allowed-tools): Read, Grep, Glob

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. The ru-text SKILL.md — its inline typography table and top stop-words. Skip if it is
  2. The «Neuroslop index» section of addenda.md: from the ## Neuroslop index heading to
  3. Section «B. Каталог стоп-слов» of info-style.md: from its ## B. heading to the next

What it can do on your machine

Read from SKILL.md and the folder at commit c5d2ee5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Grep
    • Glob

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Ru Check loads about 2.6k tokens when it runs. Until then it costs about 119 tokens; SKILL.md has 1,504 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~119
When it runs · the whole SKILL.md, loaded when a task matches
~2.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from talkstream/ru-text at commit c5d2ee5, republished under its MIT licence (© talkstream). 1,504 words, ~2,634 tokens.

Download SKILL.mdSave it as .claude/skills/ru-check/SKILL.md (or your agent's skills folder).
name
ru-check
description
Full Russian text quality check against the whole corpus. Triggers: вычитай, вычитай через ru-text, прогони ru-text, проверь текст по ru-text, ru-check, полная вычитка. Use when the user asks to proofread Russian text, or when a project gate names ru-text. Returns findings with the rule behind each and a proposed replacement; never edits a file. Self-initiated runs start with a fast triage and escalate on evidence; an explicit request always runs the full corpus.
allowed-tools
Read, Grep, Glob
disallowed-tools
Write, Edit, NotebookEdit, Bash, PowerShell, Monitor
context
fork
user-invocable
true

Russian Text Quality Check

Review the text provided in $ARGUMENTS (or the most recent Russian text output if no arguments) using the ru-text skill.

Where the reference files live

This skill reads the corpus that ships with the ru-text skill, which is installed alongside it. Locate that folder once, then read the named files from it:

  • Look for a directory named references whose parent directory is named ru-text, and which contains info-style.md. Every file named below sits in that folder.
  • Search with file tools, never with a shell. Glob on a pattern like **/ru-text/references/info-style.md, or whatever file search the host offers, then Read. This command has no use for a command line: Bash is on its disallowed-tools list, and hosts that do not implement that field still refuse it — measured in Claude Cowork on 12.08.2026, where an opening ls returned «Permission to use Bash has been denied» in red before the search found the corpus anyway. The call bought nothing and cost the reader a scare.
  • In Claude Code the plugin root is also available directly, which saves the search.
  • Do not guess a path. If the folder cannot be found, say so and stop — a check run against remembered rules instead of the corpus is not this command, and reporting one as the other is the failure this whole product exists to prevent.

Two depths, one command

This check runs at one of two depths. Nobody chooses a depth; these rules do.

Full — the «Check order» below, whole. Run it whenever a person asked for this check («вычитай», «прогони ru-text», a gate that names ru-text, a golden-set run) or triage escalated. An explicit request is never answered with triage.

Triage — for self-initiated runs only: you produced or encountered Russian text and are checking it out of discipline, with no instruction naming ru-text. Load three things and nothing else:

  1. The ru-text SKILL.md — its inline typography table and top stop-words. Skip if it is already in context, which on an always-on host it usually is.
  2. The «Neuroslop index» section of addenda.md: from the ## Neuroslop index heading to the next ##. Not the rest of the file — the rest is ten times the size.
  3. Section «B. Каталог стоп-слов» of info-style.md: from its ## B. heading to the next ##. Not the rest of the file.

Then check the text: typography mechanically (straight quotes, a hyphen doing a dash's work, ... for an ellipsis, a space between a number and %, an ordinary space after в, к, с, о, у, и, а, я — verify by codepoint, not by eye); catalog stop-words including inflected forms, judging every candidate line yourself («данные» the noun is not «данный» the stop-word); index tells by eye.

Triage may report only what a single line decides: typography and confirmed catalog hits. A neuroslop tell is never a triage finding. Every AD rule carries carve-outs that live only in the full file, and «не X, а Y» with a real antecedent is ordinary prose — flagging it from an index alone is the false positive this command would lose the most trust for. A tell seen in triage is an escalation trigger and nothing else.

Escalate to full when any one of these holds: a neuroslop candidate appeared · five findings are confirmed · the text is bound for a reader (a deliverable, a publication, a client). Escalating is silent — continue into the full procedure as though it had been asked for.

A triage report names itself: «Быстрая проверка: типографика и стоп-слова. Полная вычитка по корпусу не выполнялась.» Reporting triage as the full check is the failure this product exists to prevent. No search tool on this host → no triage: run the full check.

Check order

  1. Typography — read typography.md, then apply:

    • Quotes: «» primary, „“ nested
    • Dashes: — (em) in text, – (en) in ranges, - (hyphen) in compounds only
    • Spaces: NBSP after single-letter words, in digit groups, before units — but % is glued to the number (R37: 100%, not 100 %). Report it with the reason the rule gives: an ordinary space is a line break point and leaves % alone on the next line
    • Ellipsis, abbreviations, special characters
  2. Anti-patterns — read anti-patterns.md, then scan for:

    • Bureaucratic language and nominalization
    • Passive voice overuse
    • Sentence bloat
    • Tautology and pleonasm
  3. Writing quality — read info-style.md, then apply:

    • Stop-words and filler
    • Specificity and facts
    • Structure and clarity
  4. Domain-specific — load if text type is identifiable:

    • UI/interface text → ux-writing.md
    • Email/business → business-writing.md
    • Needs grammar review → editorial-punctuation.md + editorial-grammar.md
  5. Experience-based / neuroslop — read addenda.md, then scan for the AI-generated-prose tells:

    • Manufactured antithesis (AD-6) — «не X, а Y» / «не просто X, а Y» with no antecedent
    • Preemptive virtue qualifier (AD-7) — «без воды», «чётко, по делу»
    • Assistant-register meta-commentary (AD-8) — «Отличный вопрос!», «Надеюсь, это помогло»
    • Hollow openers (AD-9) — «давайте разберёмся», «погрузимся», «важно понимать, что»
    • Declared sincerity (AD-10) — «честный разбор», «давайте будем честны»: honesty predicated of the piece. The same reflex on a single statement — «скажу честно: дедлайн сорван» — is AD-7
    • Mandatory tricolon (AD-11) — «инновационный, трансформирующий, прорывной»
    • Hollowed mechanism (AD-12) — «зависит от различных факторов», «свои особенности»
    • Phantom attribution (AD-13) — «исследования показывают», «эксперты отмечают»
    • Chat transcript as the artifact (AD-14) — the document's skeleton is a dialogue
    • Search-engine addressee (AD-15) — the query phrase repeated where a pronoun would serve
    • Additive pseudo-pair (AD-16) — «не только X, но и Y» where Y adds nothing
    • Comma welded to a dash (AD-17) — a comma and an em dash side by side inside one sentence, both demanded by the same construction: «Отчёт, собранный за ночь, — на столе». Search by codepoint: the gap between the marks is normally the NBSP R16/R44 require before a dash, so a search written with an ordinary space finds nothing in correctly typeset text. Direct speech («Сроки поедут», — предупредила Петрова) is two constructions meeting, and a comma closing homogeneous subordinate clauses before the main clause forms a single mark with the dash — different grounds, same outcome: never this rule
    • Uppercase band (AD-18) — three or more consecutive uppercase Cyrillic words of two letters or more, unbroken by a lowercase word or by a line break. Not a neuroslop tell, and it is absent from the index above on purpose: a person shouts on a keyboard with no italic key, a model does not. It belongs to this full pass and to nothing faster. One or two uppercase words are deliberate emphasis and are never flagged; abbreviations, machine text, status cells and headings do not count toward the run

    The list above is a prompt for the eye, not the rule set. Two of these — AD-14 and AD-15 — are charged to the document, so ask them of the piece as a whole and not of any one sentence. Every rule has carve-outs that decide as many cases as the triggers do; they are in addenda.md, and a finding raised without checking them is the false positive this command costs the most trust for.

Show full SKILL.md (378 more words)Show less

Output format

Read-only — do NOT modify the source files. ru-check is a check: it reports issues and returns the corrected text for the user to apply. It must not write to, edit, or overwrite the analysed file(s).

How this is enforced depends on the host, and it is worth being exact about it.

In Claude Code, disallowed-tools removes the listed tools from the pool while the command is active — verified on 2.1.220 by attempting a write through Write, through Bash redirection, through Monitor, and through a delegated subagent: every path was denied and no file was created. allowed-tools alone would not achieve this; that field pre-approves tools, it does not restrict them.

The list removes the direct file-writers — Write, Edit, NotebookEdit — and the command-executing tools we identified and tested on 2.1.220: Bash, PowerShell and Monitor. Monitor is easy to miss: it runs commands too, and it follows Bash permission rules, so a broad Bash allow-rule silently pre-approves it while a disallowed-tools: Bash entry does not remove it. The list names the paths we closed, not every path that exists.

Four limits, stated plainly. A connected MCP server can expose its own write tools, which a per-tool denial list cannot know about. A named subagent whose own definition grants it tools: Write is governed by that definition, not by a parent command's denial list. A later Claude Code release can add a tool this file does not name, and a hand-written list does not update itself. And on hosts that do not implement disallowed-tools, everything above is an instruction the agent is asked to follow, not a guarantee the platform enforces.

Where the mechanism ends, the contract does not: the rule is that this command returns text and never writes, on every host, whatever the tool roster happens to contain.

Returning the corrected text in the output rather than writing it keeps the command deterministic and free of side effects. Silently inserting NBSP into a source file is doubly harmful: a target that strips NBSP on import (e.g. Notion) shows the reader no change, and the same insertion breaks later exact-string tooling (grep/replace) on that file.

Return:

  1. Corrected text
  2. List of changes grouped by category (typography / style / grammar / domain)
  3. Severity per change: critical / high / medium / low

© talkstream, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/ru-check of talkstream/ru-text.

Open the folder on GitHubat commit c5d2ee5

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in talkstream/ru-text, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Ru Check next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Ru Check compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Ru Check this skilltalkstream/ru-text2541 repos~2.6kAutomated safety check: PassMIT
HumanizerPrism-Shadow/penguin-harness2.5k—~1.8kAutomated safety check: PassApache-2.0
User-Facing Text Cleanupguillaumemeyer/watermarks-remover24k—~3.5kAutomated safety check: PassMIT
Story Multi-Perspective Reviewzenstory-ai/oh-story-claudecode7.4k3 repos~3kAutomated safety check: PassMIT
Chinese Text Humanizerop7418/Humanizer-zh19k—~2kAutomated safety check: PassMIT
Korean AI-Text Humanizerepoko77-ai/im-not-ai5.9k1 repos~4.5kAutomated safety check: PassMIT

Similar skills

  • Humanizer

    Prism-Shadow/penguin-harness

    Rewrite or edit prose in any language so it reads like edited human writing in the register of books, newspapers and encyclopedias rather than default AI output.

    2.5k GitHub stars~1.8k tokensUpdated today
    Writing & ContentAuto-check passed
  • User-Facing Text Cleanup

    guillaumemeyer/watermarks-remover

    Audits prose for invisible Unicode characters and rewrites it while keeping facts, citations, code and required disclosures unchanged and the writer's voice intact.

    24k GitHub stars~3.5k tokensUpdated 2 days ago
    Writing & ContentAuto-check passed
  • Story Multi-Perspective Review

    zenstory-ai/oh-story-claudecode

    Reviews Chinese web-novel text with several reviewer agents in parallel, falling back to a single-agent pass, and reports structure, character, prose and setting problems with fixes.

    7.4k GitHub starsUsed in 3 repos~3k tokens
    Writing & ContentAuto-check passed
  • Chinese Text Humanizer

    op7418/Humanizer-zh

    Edits Chinese articles, comments and documents to remove filler, repetition and template phrasing while keeping the facts, the level of certainty and the author's voice.

    19k GitHub stars~2k tokensUpdated 15 days ago
    Writing & ContentAuto-check passed
  • Korean AI-Text Humanizer

    epoko77-ai/im-not-ai

    Rewrites Korean text written by AI so it reads like a human wrote it, detecting translationese and other AI patterns while leaving the content untouched.

    5.9k GitHub starsUsed in 1 repo~4.5k tokens
    Writing & ContentAuto-check passed
  • Writes and edits Japanese business documents so they read clearly and naturally, removes AI-sounding phrasing and can score how AI-like a text reads.

    1.9k GitHub stars~2.1k tokensUpdated 1 mo ago
    Writing & ContentAuto-check passed

More from talkstream/ru-text

  • Ru Score

    talkstream/ru-text

    Score Russian text 0.0–10.0 across five dimensions: typography, clean language, grammar, structure, precision for the reader.

    254 GitHub starsUsed in 2 repos~1.4k tokens
    Auto-check passed
  • Ru Text

    talkstream/ru-text

    Russian text quality. An agent skill from talkstream/ru-text.

    254 GitHub starsUsed in 1 repo~993 tokens
    Auto-check passed

Works with

Questions about Ru Check

What does Ru Check do?

Full Russian text quality check against the whole corpus. An agent skill from talkstream/ru-text. Ru Check is an agent skill from talkstream/ru-text. Full Russian text quality check against the whole corpus.

When should I use Ru Check?

Ru Check fits situations like: the user asks to proofread Russian text; A project gate names ru-text.

How do I install Ru Check in Claude Code?

Run `npx skills add talkstream/ru-text --skill ru-check -a claude-code`. Or copy the skill folder (skills/ru-check in talkstream/ru-text) into .claude/skills/ru-check in your project. Claude Code loads it when a task matches its description.

How do I install Ru Check in Codex?

Run `npx skills add talkstream/ru-text --skill ru-check -a codex`. Or copy the skill folder (skills/ru-check in talkstream/ru-text) into .agents/skills/ru-check in your project. Codex loads it when a task matches its description.

Can I use Ru Check in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add talkstream/ru-text --skill ru-check -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ru-check, .gemini/skills/ru-check, .github/skills/ru-check and .opencode/skills/ru-check in your project.

What does Ru Check need to run?

SKILL.md names no scripts, command-line tools or credentials: Ru Check is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Grep, Glob.

Does Ru Check access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Ru Check safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Ru Check use?

Ru Check is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Ru Check use?

About 2.6k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Ru Check?

Skills that share tags, products or a category with Ru Check: Humanizer (Prism-Shadow/penguin-harness, 2.5k stars), User-Facing Text Cleanup (guillaumemeyer/watermarks-remover, 24k stars), Story Multi-Perspective Review (zenstory-ai/oh-story-claudecode, 7.4k stars) and Chinese Text Humanizer (op7418/Humanizer-zh, 19k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Ru Check?

talkstream (a GitHub user) maintains it in talkstream/ru-text, which has 254 GitHub stars. The repository holds 3 skills in this directory. The repository was last updated on October 3, 2026.

Source: talkstream/ru-text on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.