From k-skill
Counts Korean text deterministically using Unicode grapheme clusters, UTF-8 bytes, and line breaks. Useful for self-introductions and form limits where exact character counts matter.
How this skill is triggered — by the user, by Claude, or both
Slash command
/k-skill:korean-character-countThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
자기소개서, 지원서, 자유서술형 폼처럼 **글자 수 제한이 중요한 한국어 텍스트**를 대상으로 LLM 추정 없이 결정론적으로 카운트한다.
자기소개서, 지원서, 자유서술형 폼처럼 글자 수 제한이 중요한 한국어 텍스트를 대상으로 LLM 추정 없이 결정론적으로 카운트한다.
Intl.Segmenter 기반 Unicode extended grapheme clusterCRLF, LF, CR, U+2028, U+2029 를 줄바꿈 1회로 계산neis byte 규칙default profileIntl.Segmenter("ko", { granularity: "grapheme" })Buffer.byteLength(text, "utf8")01CRLF 는 2줄바꿈이 아니라 1줄바꿈으로 센다.neis profiledefault 와 동일default 와 동일3B1B2Bnode 18+scripts/korean_character_count.js helper 포함node scripts/korean_character_count.js 로 결정론적 카운트를 실행한다.default/neis)과 출력 형식(json/text)을 고른다.node scripts/korean_character_count.js --text "가나다"
node scripts/korean_character_count.js --text $'첫 줄\r\n둘째 줄🙂'
node scripts/korean_character_count.js --text $'첫 줄\n둘째 줄🙂' --profile neis --format text
node scripts/korean_character_count.js --file ./essay.txt --profile default
cat essay.txt | node scripts/korean_character_count.js --stdin --profile neis
default profile을 사용한다.neis 를 쓴다.default 와 neis 계약 차이가 문서에 명시된다.node scripts/korean_character_count.js --help 가 동작한다.Buffer.byteLength: https://nodejs.org/api/buffer.htmlnpx claudepluginhub nomadamas/k-skill --plugin k-skillUses the Nara/PNU Korean spell-check web surface to proofread Korean text, chunking long input and returning change-focused correction suggestions with original text, correction, and reason.
Detects and corrects Korean grammar, spelling, spacing, and punctuation errors per standard rules. Handles issues like 되/돼, dependent spacing, particles, tense. Use for docs review, code comments, real-time edits, learning, official quality.
Use this skill for any task involving Thai text in code — word segmentation, Unicode normalization, sorting/collation, search indexing, romanization, truncation, or database/Elasticsearch configuration for Thai. Trigger whenever the user asks to: tokenize / segment Thai (no spaces between words), normalize Thai text (NFC vs decomposed), sort Thai strings correctly, transliterate to roman / Latin, build a Thai search index, fix Thai text that breaks length limits or renders broken glyphs, or pick a Thai NLP library. Also trigger for requests like "ตัดคำภาษาไทย", "Thai word segmentation", "Thai NLP", "ค้นหาภาษาไทย", "Thai romanization", "PyThaiNLP", "Thai sort", "ICU Thai", "Thai collation", "Thai search index", "Thai full text search", or any variation. If the task involves processing Thai text in software, use this skill.