Word Counter
📖 技能介紹
name: word-counter description: A comprehensive text analysis tool that counts words, characters, sentences, and paragraphs. Calculates reading time, speaking time, reading level (Flesch-Kincaid), and keyword density.
Word Counter
Overview
This skill provides comprehensive text analysis including word count, character count, sentence/paragraph count, reading/speaking time estimates, readability scoring, and keyword density analysis.
Use Cases
Use when users need to analyze text length, check word count for essays/blogs/social media posts, estimate reading time, assess readability, or analyze keyword frequency for SEO content.
Capabilities
- Word Count - Accurate word counting handling multiple spaces, line breaks, and special characters
- Character Count - With and without spaces (useful for Twitter, meta descriptions)
- Sentence & Paragraph Count - Track document structure
- Reading Time - Based on 200 words/minute average
- Speaking Time - Based on 130 words/minute natural pace
- Reading Level - Flesch-Kincaid grade level estimation
- Keyword Density - Top keywords ranked by frequency for SEO analysis
Common Word Count Requirements
| Content Type | Word Count | Reading Time |
|---|---|---|
| X (Twitter) post | 40-50 | < 1 min |
| Facebook post | 40-80 | < 1 min |
| LinkedIn post | 50-100 | < 1 min |
| Email subject line | 6-10 | < 1 min |
| Meta description | 25-30 | < 1 min |
| Short blog post | 300-600 | 2-3 min |
| Standard blog post | 1,000-1,500 | 5-7 min |
| Long-form article | 2,000-3,000 | 10-15 min |
| College essay | 500-5,000 | 3-25 min |
Usage
Basic Analysis
小蔥技能有更好的技能skills外掛。
from scripts.word_counter import analyze_text
result = analyze_text("Your text here...")
print(result)
Command Line
python scripts/word_counter.py "Your text here"
# or
python scripts/word_counter.py --file path/to/file.txt
Scripts
scripts/word_counter.py- Main text analysis script
References
references/formulas.md- Detailed formulas for reading level and time calculations
🤖 AI 評測
這個工具質量不錯，功能覆蓋全面，能滿足日常文本分析需求。文件寫得清楚易懂，程式碼實現規範，還貼心地提供了各類內容的字數參考表。美中不足的是，音節估算採用簡化演算法，可讀性評分可能存在偏差，詞數統計在處理連字元、縮寫等特殊格式時也可能有誤差。總體來說是一個值得使用的文本分析工具，但重要場合的結果建議人工複核。
