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:

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

Usage

Input

json

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

Output

json

{
  "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:

•Splits text into sentences
•Scores sentences by length and position
•Selects top N sentences as summary points

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