kanji-index — community kanji-index, je-dict-1, community, ide skills, Claude Code, Cursor, Windsurf

v1.0.0
GitHub

About this Skill

Perfect for Language Learning Agents needing advanced Japanese character analysis and dictionary integration capabilities. In-progress Japanese-English learner's dictionary

tkgally tkgally
[0]
[0]
Updated: 3/5/2026

Agent Capability Analysis

The kanji-index skill by tkgally is an open-source community AI agent skill for Claude Code and other IDE workflows, helping agents execute tasks with better context, repeatability, and domain-specific guidance.

Ideal Agent Persona

Perfect for Language Learning Agents needing advanced Japanese character analysis and dictionary integration capabilities.

Core Value

Empowers agents to navigate complex Japanese-English dictionaries using kanji index pages, providing efficient lookup and sorting by reading in hiragana order, leveraging JSON data formats like 'kanji_list.json' and 'kanji_extracted.json'.

Capabilities Granted for kanji-index

Linking headword kanji to comprehensive index pages
Generating sorted entry lists by reading in hiragana order
Maintaining master kanji lists with unique kanji_id mappings

! Prerequisites & Limits

  • Requires directory structure with specific JSON files
  • Limited to Japanese-English language pair
  • Dependent on accurate kanji extraction and mapping
Labs Demo

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

kanji-index

Install kanji-index, an AI agent skill for AI agent workflows and automation. Works with Claude Code, Cursor, and Windsurf with one-command setup.

SKILL.md
Readonly

Kanji Index Maintenance

The kanji index allows users to click on any kanji in a dictionary headword to find all other entries containing that same kanji.

How It Works

  1. Headword kanji are linked to kanji index pages
  2. Kanji index pages list all entries containing that kanji
  3. Entry lists are sorted by reading (hiragana order)

Directory Structure

kanji/
├── kanji_list.json       # Master list: kanji → kanji_id mapping
├── kanji_extracted.json  # Temporary: extracted kanji needing IDs
├── 00001_jin_hito_person.json  # Entry list for 人
├── 00002_nichi_hi_day.json     # Entry list for 日
└── ...

docs/kanji/
├── 00001_jin_hito_person.html  # HTML page for 人
├── 00002_nichi_hi_day.html     # HTML page for 日
└── ...

Kanji ID Format

Format: {5-digit}_{onyomi}_{kunyomi}_{gloss}

  • 5-digit: Sequential number (00001, 00002, ...)
  • onyomi: Most common on'yomi in romaji (or "none")
  • kunyomi: Most common kun'yomi in romaji without okurigana (or "none")
  • gloss: Single English word for primary meaning

Examples

KanjiKanji ID
00001_jin_hito_person
00002_nichi_hi_day
00003_dai_oo_big
00004_none_hatake_field
00005_cha_none_tea

Romaji Rules

  • Long vowels: "ou" not "ō" (e.g., 高 → "kou")
  • Voiced: "ga", "za", "da", "ba" (e.g., 学 → "gaku")
  • No okurigana in kun'yomi (e.g., 高い → "taka", not "takai")

Assigning New Kanji IDs

When new entries introduce kanji not in kanji_list.json:

  1. Detect new kanji:

    bash
    1python3 build/update_kanji_index.py --check-new
  2. Assign readings and gloss using your knowledge:

    • Most common on'yomi
    • Most common kun'yomi (without okurigana)
    • Single-word English gloss
  3. Update kanji_list.json:

    json
    1{ 2 "新": { 3 "kanji_id": "00123_shin_atara_new", 4 "onyomi": "shin", 5 "kunyomi": "atara", 6 "gloss": "new" 7 } 8}
  4. Rebuild:

    bash
    1python3 build/build_flat.py

Common Tasks

Check for New Kanji

bash
1python3 build/update_kanji_index.py --check-new

Rebuild All Kanji JSON Files

bash
1python3 build/update_kanji_index.py --rebuild-all

Rebuild Kanji HTML Pages

bash
1python3 build/build_kanji_html.py

Full Site Build (includes kanji)

bash
1python3 build/build_flat.py

Troubleshooting

"Warning: X kanji need IDs assigned"

New kanji were found in entries. Assign IDs manually:

  1. Run --check-new to see the full list
  2. For each kanji, determine on'yomi, kun'yomi, gloss
  3. Add to kanji/kanji_list.json
  4. Rebuild

Missing kanji index page

Check that:

  1. Kanji is in kanji/kanji_list.json
  2. JSON file exists: kanji/{kanji_id}.json
  3. Run python3 build/build_kanji_html.py

Check that:

  1. Kanji is in kanji/kanji_list.json
  2. Entry HTML was rebuilt after kanji was added

Entry count wrong on kanji page

Rebuild the kanji JSON file:

bash
1python3 build/update_kanji_index.py --rebuild-all 2python3 build/build_kanji_html.py

File Formats

kanji_list.json

json
1{ 2 "metadata": { 3 "description": "Index mapping kanji characters to their kanji index IDs", 4 "generated": "2026-01-22T10:30:00Z", 5 "total_kanji": 1500 6 }, 7 "kanji": { 8 "人": { 9 "kanji_id": "00001_jin_hito_person", 10 "onyomi": "jin", 11 "kunyomi": "hito", 12 "gloss": "person" 13 } 14 } 15}

Individual kanji JSON

json
1{ 2 "metadata": { 3 "kanji": "人", 4 "kanji_id": "00001_jin_hito_person", 5 "onyomi": "jin", 6 "kunyomi": "hito", 7 "gloss": "person", 8 "entry_count": 245, 9 "generated": "2026-01-22T10:30:00Z" 10 }, 11 "entries": [ 12 { 13 "id": "01234_akunin", 14 "headword": "{悪|あく}{人|にん}", 15 "reading": "あくにん", 16 "gloss": "villain, bad person" 17 } 18 ] 19}

Design Decisions

  • Preserves clean headword appearance
  • Users discover feature through tooltip
  • No visual clutter

Why romaji in kanji IDs?

  • ASCII-safe file names
  • Human-readable
  • Easy to search and sort

Why sort by reading?

  • Natural Japanese ordering (gojuon)
  • Consistent with how dictionaries organize entries
  • Helps users find related words

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is kanji-index?

Perfect for Language Learning Agents needing advanced Japanese character analysis and dictionary integration capabilities. In-progress Japanese-English learner's dictionary

How do I install kanji-index?

Run the command: npx killer-skills add tkgally/je-dict-1/kanji-index. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for kanji-index?

Key use cases include: Linking headword kanji to comprehensive index pages, Generating sorted entry lists by reading in hiragana order, Maintaining master kanji lists with unique kanji_id mappings.

Which IDEs are compatible with kanji-index?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for kanji-index?

Requires directory structure with specific JSON files. Limited to Japanese-English language pair. Dependent on accurate kanji extraction and mapping.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add tkgally/je-dict-1/kanji-index. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use kanji-index immediately in the current project.

Related Skills

Looking for an alternative to kanji-index or another community skill for your workflow? Explore these related open-source skills.

View All

widget-generator

Logo of f
f

f.k.a. Awesome ChatGPT Prompts. Share, discover, and collect prompts from the community. Free and open source — self-host for your organization with complete privacy.

149.6k
0
AI

flags

Logo of vercel
vercel

flags is a Next.js feature management skill that enables developers to efficiently add or modify framework feature flags, streamlining React application development.

138.4k
0
Browser

zustand

Logo of lobehub
lobehub

The ultimate space for work and life — to find, build, and collaborate with agent teammates that grow with you. We are taking agent harness to the next level — enabling multi-agent collaboration, effortless agent team design, and introducing agents as the unit of work interaction.

72.8k
0
AI

data-fetching

Logo of lobehub
lobehub

The ultimate space for work and life — to find, build, and collaborate with agent teammates that grow with you. We are taking agent harness to the next level — enabling multi-agent collaboration, effortless agent team design, and introducing agents as the unit of work interaction.

72.8k
0
AI