| name | text_summarizer |
| version | 1.0.0 |
| entrypoint | scripts/main.py |
| description | Summarizes long text into key bullet points |
| inputs | [object Object], [object Object] |
| outputs | [object Object], [object Object] |
| 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
{
"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 summarystats.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.