| name | word-counter |
| description | Deterministic counting for Chinese, English, and mixed-language text such as articles, essays, novels, chapters, outlines, transcripts, and pasted paragraphs. Use when the user asks for word count, character count, manuscript length, bilingual text count, chapter length, or wants a stable count instead of a model estimate. |
Word Counter
Use the bundled script to produce a reproducible count instead of estimating from the model.
If the user asks in Chinese, run the script with --locale zh so the report is returned in Chinese. If the user asks in English, use --locale en. Only use --details when the user explicitly asks for detailed statistics.
Pick A Profile
- Use
zh for Chinese-style content counting.
- Use
en for English-style word counting.
- Use
mixed for one total across Chinese and English text.
If the user is ambiguous, run mixed first and mention the zh and en alternatives.
Run The Script
For pasted content:
python3 "$HOME/.claude/skills/word-counter/scripts/word_counter.py" --profile mixed --locale en --format markdown --text "Hello world from OpenAI"
For a file:
python3 "$HOME/.claude/skills/word-counter/scripts/word_counter.py" --profile zh --locale zh --format markdown ./chapter-01.txt
Return A Clear Summary
Return this compact Markdown structure. Use the English example as the default format reference:
# Word Count Result
- Selected profile: `mixed` (Mixed-language count)
- Selected total: `1234`
- Applied formula: `mixed_count = cjk_chars + english_words + number_tokens + other_words`
| Metric | Value |
| --- | ---: |
| Chinese count | 1300 |
| English words | 45 |
| Mixed total | 1234 |
| Line count | 12 |
| Paragraph count | 4 |
For Chinese replies, use the same compact structure with Chinese labels. Do not show CJK characters, English words, or Number tokens unless the user explicitly asks for detailed statistics, in which case run with --details.
For rules and examples, read references/counting-rules.md.
