key-takeaways

name	key-takeaways
description	Extracts and summarizes key takeaways from documents, meeting notes, articles, and other text content. Use when the user asks for summaries, bullet points, main points, highlights, or a TL;DR of any document or body of text. Produces structured outputs such as numbered lists, executive summaries, and action items. Supports configurable output formats including JSON export for downstream use.
allowed-tools	Read Write Bash Edit
license	MIT
metadata	{"skill-author":"AIPOCH","version":"1.0"}

Key Takeaways

Extracts and presents the most important points from any body of text — meeting notes, articles, reports, or documents — as concise, structured takeaways. Supports multiple output formats and is configurable for audience or depth.

Quick Start

from scripts.main import Key_Takeaways

# Initialize
tool = Key_Takeaways()

# Extract key takeaways from a document
result = tool.process("meeting_notes.txt")

# Export as structured JSON
tool.export(result, format="json")

Core Capabilities

1. Extract key points from text

# Read source document and extract top takeaways
result = tool.process("quarterly_report.txt")
# Returns: [{"point": "Revenue grew 12% YoY", "source_line": 4}, ...]

2. Generate structured summaries

# Generate a bullet-point executive summary
result = tool.process("meeting_notes.txt", style="executive")
# Returns: {"summary": "...", "action_items": [...], "decisions": [...]}

3. Configure output depth and audience

# Adjust number of takeaways and target audience
result = tool.process("article.txt", max_points=5, audience="non-technical")

4. Export results

# Export takeaways to JSON or plain text
tool.export(result, format="json", output_path="takeaways.json")
tool.export(result, format="txt",  output_path="takeaways.txt")

CLI Usage

# Extract key takeaways from a file
python scripts/main.py --input document.txt --output takeaways.txt

# Use a config file to set depth, audience, and format
python scripts/main.py --input document.txt --config config.json --verbose

# Batch process a directory of documents
python scripts/main.py --batch input_dir/ --output output_dir/

Batch processing notes:

• Verify the output directory exists before running: mkdir -p output_dir/
• If processing fails on an individual file, the tool logs the error and continues with remaining files; review output_dir/errors.log after the run
• After batch completion, validate all JSON outputs: for f in output_dir/*.json; do python -m json.tool "$f" > /dev/null && echo "OK: $f" || echo "FAIL: $f"; done

Example Input / Output

Input (meeting_notes.txt):

Q3 review: Sales up 15%. New product launch delayed to Q4.
Action: Alice to update roadmap by Friday. Budget approved for hiring.

Output (takeaways.json):

{
  "key_points": [
    "Sales increased 15% in Q3",
    "Product launch rescheduled to Q4"
  ],
  "action_items": [
    "Alice to update roadmap by Friday"
  ],
  "decisions": [
    "Budget approved for hiring"
  ]
}

Quality Checklist

• Source text is readable and complete before processing
• Output point count matches configured max_points setting
• Action items and decisions are separated from general observations
• Exported file opens and validates correctly (e.g., python -m json.tool takeaways.json)
  • If JSON validation fails, check source file encoding (UTF-8 expected) and re-run; inspect --verbose output for parsing errors
• Results reviewed against original source for accuracy

References

• references/guide.md - Detailed documentation
• references/examples/ - Sample inputs and outputs

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Skill ID: 308 | Version: 1.0 | License: MIT