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.
Full Russian text quality check against the whole corpus. An agent skill from talkstream/ru-text.
$ npx skills add talkstream/ru-text --skill ru-check -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install talkstream/ru-text ru-check --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ 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-srcUse ~/.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/
Install the "ru-check" agent skill from https://github.com/talkstream/ru-text/tree/main/skills/ru-check into .claude/skills/ru-check/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ru-check", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/talkstream/ru-text/tree/main/skills/ru-checkType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add talkstream/ru-text --skill ru-check -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install talkstream/ru-text ru-check --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/talkstream/ru-text.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/ru-check .agents/skills/ru-check && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "ru-check" agent skill from https://github.com/talkstream/ru-text/tree/main/skills/ru-check into .agents/skills/ru-check/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ru-check", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add talkstream/ru-text --skill ru-check -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install talkstream/ru-text ru-check --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/talkstream/ru-text.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/ru-check .cursor/skills/ru-check && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "ru-check" agent skill from https://github.com/talkstream/ru-text/tree/main/skills/ru-check into .cursor/skills/ru-check/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ru-check", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/talkstream/ru-text.git --path skills/ru-check--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add talkstream/ru-text --skill ru-check -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install talkstream/ru-text ru-check --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/talkstream/ru-text.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/ru-check .gemini/skills/ru-check && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "ru-check" agent skill from https://github.com/talkstream/ru-text/tree/main/skills/ru-check into .gemini/skills/ru-check/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ru-check", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install talkstream/ru-text ru-checkInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add talkstream/ru-text --skill ru-check -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/talkstream/ru-text.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/ru-check .github/skills/ru-check && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "ru-check" agent skill from https://github.com/talkstream/ru-text/tree/main/skills/ru-check into .github/skills/ru-check/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ru-check", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add talkstream/ru-text --skill ru-check -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install talkstream/ru-text ru-check --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/talkstream/ru-text.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/ru-check .opencode/skills/ru-check && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "ru-check" agent skill from https://github.com/talkstream/ru-text/tree/main/skills/ru-check into .opencode/skills/ru-check/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ru-check", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
ru-checkFull 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. 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.
3 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit c5d2ee5. It shows what the files ask for, not the result of running them.
Pre-approves these tools, so the agent can use them without asking each time:
ReadGrepGlobFrom allowed-tools in the SKILL.md frontmatter.
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.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
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.
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.
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.
The full file from talkstream/ru-text at commit c5d2ee5, republished under its MIT licence (© talkstream). 1,504 words, ~2,634 tokens.
.claude/skills/ru-check/SKILL.md (or your agent's skills folder).Review the text provided in $ARGUMENTS (or the most recent Russian text output if no arguments) using the ru-text skill.
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:
references whose parent directory is named ru-text, and
which contains info-style.md. Every file named below sits in that folder.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.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:
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.addenda.md: from the ## Neuroslop index heading to
the next ##. Not the rest of the file — the rest is ten times the size.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.
Typography — read typography.md, then apply:
% 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 lineAnti-patterns — read anti-patterns.md, then scan for:
Writing quality — read info-style.md, then apply:
Domain-specific — load if text type is identifiable:
ux-writing.mdbusiness-writing.mdeditorial-punctuation.md + editorial-grammar.mdExperience-based / neuroslop — read addenda.md, then scan for the AI-generated-prose tells:
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.
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:
© talkstream, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/ru-check of talkstream/ru-text.
Open the folder on GitHubat commit c5d2ee5
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.
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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Ru Check this skilltalkstream/ru-text | 254 | 1 repos | ~2.6k | Automated safety check: Pass | MIT | |
| HumanizerPrism-Shadow/penguin-harness | 2.5k | — | ~1.8k | Automated safety check: Pass | Apache-2.0 | |
| User-Facing Text Cleanupguillaumemeyer/watermarks-remover | 24k | — | ~3.5k | Automated safety check: Pass | MIT | |
| Story Multi-Perspective Reviewzenstory-ai/oh-story-claudecode | 7.4k | 3 repos | ~3k | Automated safety check: Pass | MIT | |
| Chinese Text Humanizerop7418/Humanizer-zh | 19k | — | ~2k | Automated safety check: Pass | MIT | |
| Korean AI-Text Humanizerepoko77-ai/im-not-ai | 5.9k | 1 repos | ~4.5k | Automated safety check: Pass | MIT |
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.
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.
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.
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.
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.
coji/natural-japanese
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.
Works with
Categories
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.
Ru Check fits situations like: the user asks to proofread Russian text; A project gate names ru-text.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.