Humanizer
Azure-Samples/interview-coach-agent-framework
Remove signs of AI-generated writing from text. An agent skill from Azure-Samples/interview-coach-agent-framework.
Detect and remove AI-generated markers from Hungarian text, making it sound like a native Hungarian speaker wrote it.
$ npx skills add bencium/bencium-marketplace --skill hungarian-humanizer -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install bencium/bencium-marketplace hungarian-humanizer --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/bencium/bencium-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/hungarian-humanizer/skills/hungarian-humanizer .claude/skills/hungarian-humanizer && 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 "hungarian-humanizer" agent skill from https://github.com/bencium/bencium-marketplace/tree/main/hungarian-humanizer/skills/hungarian-humanizer into .claude/skills/hungarian-humanizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hungarian-humanizer", 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/bencium/bencium-marketplace/tree/main/hungarian-humanizer/skills/hungarian-humanizerType 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 bencium/bencium-marketplace --skill hungarian-humanizer -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install bencium/bencium-marketplace hungarian-humanizer --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/bencium/bencium-marketplace.git skills-src && mkdir -p .agents/skills && cp -r skills-src/hungarian-humanizer/skills/hungarian-humanizer .agents/skills/hungarian-humanizer && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "hungarian-humanizer" agent skill from https://github.com/bencium/bencium-marketplace/tree/main/hungarian-humanizer/skills/hungarian-humanizer into .agents/skills/hungarian-humanizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hungarian-humanizer", 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 bencium/bencium-marketplace --skill hungarian-humanizer -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install bencium/bencium-marketplace hungarian-humanizer --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/bencium/bencium-marketplace.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/hungarian-humanizer/skills/hungarian-humanizer .cursor/skills/hungarian-humanizer && 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 "hungarian-humanizer" agent skill from https://github.com/bencium/bencium-marketplace/tree/main/hungarian-humanizer/skills/hungarian-humanizer into .cursor/skills/hungarian-humanizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hungarian-humanizer", 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/bencium/bencium-marketplace.git --path hungarian-humanizer/skills/hungarian-humanizer--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 bencium/bencium-marketplace --skill hungarian-humanizer -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install bencium/bencium-marketplace hungarian-humanizer --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/bencium/bencium-marketplace.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/hungarian-humanizer/skills/hungarian-humanizer .gemini/skills/hungarian-humanizer && 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 "hungarian-humanizer" agent skill from https://github.com/bencium/bencium-marketplace/tree/main/hungarian-humanizer/skills/hungarian-humanizer into .gemini/skills/hungarian-humanizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hungarian-humanizer", 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 bencium/bencium-marketplace hungarian-humanizerInstalls 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 bencium/bencium-marketplace --skill hungarian-humanizer -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/bencium/bencium-marketplace.git skills-src && mkdir -p .github/skills && cp -r skills-src/hungarian-humanizer/skills/hungarian-humanizer .github/skills/hungarian-humanizer && 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 "hungarian-humanizer" agent skill from https://github.com/bencium/bencium-marketplace/tree/main/hungarian-humanizer/skills/hungarian-humanizer into .github/skills/hungarian-humanizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hungarian-humanizer", 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 bencium/bencium-marketplace --skill hungarian-humanizer -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install bencium/bencium-marketplace hungarian-humanizer --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/bencium/bencium-marketplace.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/hungarian-humanizer/skills/hungarian-humanizer .opencode/skills/hungarian-humanizer && 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 "hungarian-humanizer" agent skill from https://github.com/bencium/bencium-marketplace/tree/main/hungarian-humanizer/skills/hungarian-humanizer into .opencode/skills/hungarian-humanizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hungarian-humanizer", 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.
hungarian-humanizerDetect and remove AI-generated markers from Hungarian text, making it sound like a native Hungarian speaker wrote it.
Hungarian Humanizer is an agent skill from bencium/bencium-marketplace. Detect and remove AI-generated markers from Hungarian text, making it sound like a native Hungarian speaker wrote it. Use when asked to "humanize", "naturalize", or "remove AI feel" from Hungarian text, or when editing .md/.txt files containing Hungarian content. Identifies 26 patterns (12 Hungarian-specific + 14 universal) and 4 style markers.
Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/patterns.md`).
It sits in Writing & Content, covering Humanizing AI text. The repository describes itself as: comprehensive skills based on the Anthropic Skills guide and our design and development philosophy. The licence is MIT.
5 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 5de46a3. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From 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.
Links to these hosts (documentation or services it may open):
github.comFrom 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.
Hungarian Humanizer loads about 1.9k tokens when it runs, and up to ~6.9k if it reads all its reference files. Until then it costs about 92 tokens; SKILL.md has 914 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 bencium/bencium-marketplace at commit 5de46a3, republished under its MIT licence (© bencium). 914 words, ~1,878 tokens.
.claude/skills/hungarian-humanizer/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.<role>
Magyar szövegszerkesztő vagy, aki felismeri és eltávolítja a magyar nyelvű AI-szöveg árulkodó jegyeit. Nem vagy nyelvtan-ellenőrző, fordító vagy egyszerűsítő. A feladatod az, hogy a szöveget olyanná tedd, amilyet egy magyar ember írhatott volna.
</role>
<magyar_voice> Mielőtt egyetlen patternt is javítanál, éld bele magad abba, hogyan gondolkodik egy magyar író.
Egyenesség. A magyar kimondja a dolgot, aztán megy tovább. Nincs rávezetés, nincs tompítás, nincsenek felesleges keretek. „Ez nem működik” teljes mondat.
A rövidség erő. A rövid mondat nem lusta — pontos. A hosszú mondatot indokolni kell.
Az ismétlés megengedett. Magyarul ugyanazt a szót kétszer használni természetes. Az angol szinonimakörforgás („megvalósít” → „kivitelez” → „implementál”) magyarul mesterkéltnek hat.
A lelkesedés gyanús. A magyar író nem kiabál és nem hájpol. A száraz megállapítás erősebb, mint a felkiáltójel. A „nem rossz” dicséret.
A hallgatás stíluseszköz. Amit nem mondasz ki, az ugyanolyan fontos lehet, mint amit kimondasz. Ne tömd tele minden rést magyarázattal.
A partikulák életet visznek. hát, hiszen, ugye, bizony, is, csak, pedig, azért, -e — ezek teszik a szöveget elevenné és természetessé. Az AI kihagyja őket, mert „feleslegesek”. Nem azok.
A magyaros szórend. A magyar mondat témával kezd és a fókuszt az ige elé teszi. Az AI ráerőlteti az angol alany–állítmány–tárgy sorrendet, és a szöveg attól lesz idegen ízű.
Lélektelen:
Ez egy rendkívül jelentős fejlesztési lépés, amely széles körben fogja befolyásolni a szakterület jövőjét. Fontos megjegyezni, hogy az adott innováció számos lehetőséget kínál a különböző érdekcsoportok számára.
Élő:
Nagy dolog a szakmának. Sokan járnak vele jól.
Az árulkodó AI-jegyek eltávolítása önmagában nem elég — a szövegnek személyiség is kell.
<process>
## Folyamat
Rövid szöveg (500 szó alatt): Kezeld közvetlenül. Add vissza a természetessé tett szöveget + a változások összefoglalóját.
Hosszú szöveg (500 szó felett):
</process>
<examples>
## Példapatternek
A 26 AI-pattern két csoportra oszlik: magyar nyelvűek (a magyarra jellemző szerkezetek) és univerzálisak (minden nyelvben előfordulnak, itt magyarul ismerjük fel és javítjuk). Alább 7 kanonikus példa. A teljes, 26 kategóriás patternlista: lásd references/patterns.md
#1 Szenvedő/körülíró szerkezetek túlzott használata Az AI a magyarban ritka szenvedő értelmet körülírással pótolja, hogy elkerülje a cselekvő megnevezését: „megvalósításra kerül”, „-ható/-hető”, „kerül + -ásra/-ésre”.
Előtte: Az alkalmazás úgy lett megtervezve, hogy lehetőséget biztosítson a felhasználók számára az adataik hatékony kezelésére. Utána: Az alkalmazással kezeled a saját adataidat.
#4 Hiányzó partikulák Az AI nem használ partikulákat (hát, hiszen, ugye, bizony, is, csak, pedig, -e), mert „informálisnak” tartja őket. Magyarul ezek a normál írott nyelv részei.
Előtte: Ez igaz. A helyzet azonban bonyolult. Utána: Hát igaz. Csak épp bonyolult a helyzet.
#5 Tükörfordításos szerkezetek Az AI olyan magyart gyárt, amely az angol szórendet és szerkezeteket követi. Az eredmény nyelvtanilag helyes, de idegen ízű.
Előtte: Ezen felül fontos figyelembe venni azt a tényt, hogy a piac megváltozott. Utána: A piac is megváltozott.
#6 Birtokos szerkezetek halmozása Egymásra torlódó birtokos szerkezetek, amikor az AI bonyolult viszonyt akar egyetlen szerkezetbe zsúfolni.
Előtte: A termék minősége javításának lehetőségei értékelésének eredményei fejlődési potenciált mutatnak. Utána: Megnéztük, hogyan lehetne javítani a termék minőségén. Van hova fejlődni.
#13 A jelentőség felnagyítása Az AI mindent „jelentőssé”, „kulcsfontosságúvá” vagy „döntővé” fúj fel.
Előtte: A mesterséges intelligencia jelentős és kulcsfontosságú szerepet fog játszani a jövő döntő kihívásainak megoldásában. Utána: A mesterséges intelligencia sok problémára hasznos eszköz lesz.
#15 Hízelgő hangnem Az AI dicséri a kérdezőt vagy a témaválasztást. Magyarul ez különösen kínos.
Előtte: Remek kérdés! Ez az egyik legfontosabb téma jelenleg. Utána: A téma időszerű.
#17 Töltelékszavak és -mondatok Az AI olyan fordulatokkal kezdi vagy tölti a bekezdéseket, amelyek nem visznek tartalmat.
Előtte: Fontos megjegyezni, hogy ebben az összefüggésben lényeges megérteni a platform architektúráját a bevezetés előtt.
Utána: A bevezetés előtt értsd meg a platform architektúráját.
</examples>
<output_format>
Miután természetessé tetted a szöveget, add vissza:
Ha a felhasználó csak a szöveget kéri magyarázat nélkül, hagyd el az összefoglalót. </output_format>
<constraints>
## Megkötések
</constraints>
© bencium, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file (references) in hungarian-humanizer/skills/hungarian-humanizer of bencium/bencium-marketplace.
Open the folder on GitHubat commit 5de46a3
Hungarian Humanizer 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 |
|---|---|---|---|---|---|---|
| Hungarian Humanizer this skillbencium/bencium-marketplace | 446 | — | ~1.9k | Automated safety check: Pass | MIT | |
| HumanizerAzure-Samples/interview-coach-agent-framework | 172 | 37 repos | ~5.8k | Automated safety check: Pass | MIT | |
| Avoid AI Writingconorbronsdon/avoid-ai-writing | 4.9k | 3 repos | ~8.1k | Automated safety check: Pass | MIT | |
| User-Facing Text Cleanupguillaumemeyer/watermarks-remover | 24k | — | ~3.5k | Automated safety check: Pass | MIT | |
| Install Anti Sloptrycompai/crm | 11k | 1 repos | ~881 | Automated safety check: Pass | MIT | |
| Stop SlopXe/site | 732 | 8 repos | ~423 | Automated safety check: Pass | MIT |
Azure-Samples/interview-coach-agent-framework
Remove signs of AI-generated writing from text. An agent skill from Azure-Samples/interview-coach-agent-framework.
conorbronsdon/avoid-ai-writing
Audit and rewrite content to remove AI writing patterns ("AI-isms").
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.
trycompai/crm
Install and configure the anti-slop Oxlint plugin in a local TypeScript or JavaScript repository.
Xe/site
Remove AI writing patterns from prose. An agent skill from Xe/site.
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.
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Categories
Detect and remove AI-generated markers from Hungarian text, making it sound like a native Hungarian speaker wrote it. Hungarian Humanizer is an agent skill from bencium/bencium-marketplace. Detect and remove AI-generated markers from Hungarian text, making it sound like a native Hungarian speaker wrote it.
Hungarian Humanizer fits situations like: asked to humanize; remove AI feel from Hungarian text; editing .md/.txt files containing Hungarian content.
Run `npx skills add bencium/bencium-marketplace --skill hungarian-humanizer -a claude-code`. Or copy the skill folder (hungarian-humanizer/skills/hungarian-humanizer in bencium/bencium-marketplace) into .claude/skills/hungarian-humanizer in your project. Claude Code loads it when a task matches its description.
Run `npx skills add bencium/bencium-marketplace --skill hungarian-humanizer -a codex`. Or copy the skill folder (hungarian-humanizer/skills/hungarian-humanizer in bencium/bencium-marketplace) into .agents/skills/hungarian-humanizer 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 bencium/bencium-marketplace --skill hungarian-humanizer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/hungarian-humanizer, .gemini/skills/hungarian-humanizer, .github/skills/hungarian-humanizer and .opencode/skills/hungarian-humanizer in your project.
SKILL.md names no scripts, command-line tools or credentials: Hungarian Humanizer is instructions for the agent only.
SKILL.md names 1 domain. As links in the text: github.com. 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.
Hungarian Humanizer is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.9k tokens (SKILL.md is roughly 7.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 5k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Hungarian Humanizer: Humanizer (Azure-Samples/interview-coach-agent-framework, 172 stars), Avoid AI Writing (conorbronsdon/avoid-ai-writing, 4.9k stars), User-Facing Text Cleanup (guillaumemeyer/watermarks-remover, 24k stars) and Install Anti Slop (trycompai/crm, 11k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
bencium (a GitHub user) maintains it in bencium/bencium-marketplace, which has 446 GitHub stars. The repository holds 13 skills in this directory. The repository was last updated on October 4, 2026.
Source: bencium/bencium-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.