text-summarizer

name	text_summarizer
version	1.0.0
entrypoint	scripts/main.py
description	Summarizes long text into key bullet points
inputs	[{"type":"text","name":"text","description":"Long text to summarize"},{"type":"integer","name":"max_points","description":"Maximum number of bullet points (default 5)","optional":true}]
outputs	[{"type":"text","name":"summary","description":"Summary in bullet points"},{"type":"object","name":"stats","description":"Statistics about the text"}]
tags	["nlp","summarization","text","processing"]
allow_network	false
timeout_seconds	30

Text Summarizer Skill

A more complex example that demonstrates text processing capabilities.

What it does

This skill takes a long piece of text and:

1. Analyzes the text (word count, sentence count, etc.)
2. Extracts key points
3. Creates a bullet-point summary
4. Generates a statistics report

Usage

Input

{
  "text": "Your long text here...",
  "max_points": 5
}

Output

{
  "summary": "• Point 1\n• Point 2\n• Point 3",
  "stats": {
    "word_count": 150,
    "sentence_count": 8,
    "avg_sentence_length": 18.75
  }
}

Artifacts

• summary.md: Markdown file with the formatted summary
• stats.json: JSON file with detailed statistics

Algorithm

This is a simple implementation that:

1. Splits text into sentences
2. Scores sentences by length and position
3. Selects top N sentences as summary points

Note: This is a demonstration. For production use, consider using NLP libraries like spaCy or transformers.