Agent skill
key-takeaways
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.
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/key-takeaways
Metadata
Additional technical details for this skill
- version
- 1.0
- skill author
- AIPOCH
SKILL.md
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.logafter 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_pointssetting - 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
--verboseoutput for parsing errors
- If JSON validation fails, check source file encoding (UTF-8 expected) and re-run; inspect
- Results reviewed against original source for accuracy
References
references/guide.md- Detailed documentationreferences/examples/- Sample inputs and outputs
Skill ID: 308 | Version: 1.0 | License: MIT
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