korean-character-count

Count Korean text characters, lines, and bytes with Intl.Segmenter.

Updated May 1, 2026
One-click install
npx skills add https://github.com/seolcoding/k-parent-skill --skill korean-character-count-seolcoding
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: korean-character-count
Source: https://github.com/seolcoding/k-parent-skill/tree/main/korean-character-count
Command: npx skills add https://github.com/seolcoding/k-parent-skill --skill korean-character-count-seolcoding

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

Korean text character count limits for self-introductions, application forms, and free-response fields are extremely strict, with even a 1-character discrepancy causing submission failures, but LLM-based estimates are unreliable and lack reproducibility.

Core Features & Use Cases

  • Deterministic Grapheme Counting: Uses Intl.Segmenter to count Unicode extended grapheme clusters, accurately handling mixed Korean, English, emoji, and special characters without estimation.
  • Dual Byte Calculation Profiles: Supports default UTF-8 byte counting and NEIS (school record system) compatible byte rules for school submission requirements.
  • Consistent Line Counting: Handles all standard line break sequences (CRLF, LF, CR, U+2028, U+2029) uniformly, with clear rules for empty strings.
  • Use Case: Students submitting college or job application self-introductions, parents filling out school forms with strict character limits, or administrators validating document length requirements can use this skill to get exact, reproducible counts.

Quick Start

Ask the korean-character-count skill to calculate the exact character, line, and byte count for your Korean application text, and specify the NEIS profile if you are submitting to a school record system.

Frequently Asked Questions about korean-character-count

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I count Korean text characters accurately for strict application form limits?

To count Korean text characters accurately for strict application form limits, use a tool that implements Unicode extended grapheme cluster counting via Intl.Segmenter. This ensures exact grapheme counting for mixed Korean, English, and emoji text without unreliable LLM estimations.

Why does my Korean text byte count not match the NEIS school record system requirements?

Your Korean text byte count might not match NEIS requirements because standard UTF-8 byte calculation differs from NEIS-specific byte rules. You need a byte calculation tool that explicitly supports a NEIS-compatible profile to ensure school record submissions meet the exact system constraints.

How are emojis and mixed English characters handled when counting Korean text length?

When counting Korean text length, emojis and mixed English characters are handled by segmenting text into Unicode extended grapheme clusters. This approach accurately counts each user-perceived character, including complex emoji sequences, ensuring deterministic and reproducible length validation.

What is the best way to count lines and bytes for a Korean self-introduction essay?

The best way to count lines and bytes for a Korean self-introduction essay is to use a deterministic text counting tool that uniformly handles standard line break sequences like CRLF, LF, and CR. This provides consistent character, line, and byte counts without altering the input text.

Can I use a standard character counter for university application text validation?

Standard character counters often fail university application text validation because they do not support NEIS-specific byte calculation profiles or grapheme cluster segmentation. You need a specialized text validation tool that provides deterministic CLI output to guarantee reproducible counts.

Does Korean character counting normalize or change my original text input?

Accurate Korean character counting should not normalize or change your original text input. The tool processes the exact string provided, applying deterministic rules for grapheme clusters and line breaks to yield reproducible counts without altering the submitted text.