text-summarizer

npx skills add majiayu000/claude-skill-registry --skill text-summarizer --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

# Text Summarizer Create concise summaries from long text documents using extractive summarization. Identifies and extracts the most important sentences while preserving meaning. ## Quick Start ```python from scripts.text_summarizer import TextSummarizer # Summarize text summarizer = TextSummarizer() summary = summarizer.summarize(long_text, ratio=0.2) # 20% of original print(summary) # Summarize file summary = summarizer.summarize_file("article.txt", num_sentences=5) ``` ## Features - **Extractive Summarization**: Selects key sentences from original text - **Length Control**: By ratio, sentence count, or word count - **Multiple Algorithms**: TextRank, LSA, frequency-based - **Key Points**: Extract bullet-point summaries - **Batch Processing**: Summarize multiple documents - **Preserve Structure**: Maintains sentence order option ## API Reference ### Initialization ```python summarizer = TextSummarizer( method="textrank", # textrank, lsa, frequency language="english" ) ``` ### Summarization ```python # By ratio (20% of original length) summary = summarizer.summarize(text, ratio=0.2) # By sentence count summary = summarizer.summarize(text, num_sentences=5) # By word count summary =

Summarize text file
python text_summarizer.py --input article.txt --ratio 0.2
Specific sentence count
python text_summarizer.py --input article.txt --sentences 5
Extract key points
python text_summarizer.py --input article.txt --points 5
Batch process
python text_summarizer.py --input-dir ./docs --output-dir ./summaries --ratio 0.3
Output to file
python text_summarizer.py --input article.txt --output summary.txt --ratio 0.2