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.

license: MIT

skill-author: AIPOCH

---

# 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.

When to Use

Key Features

Dependencies

Example Usage

cd "20260318/scientific-skills/Evidence Insight/key-takeaways"
python -m py_compile scripts/main.py
python scripts/main.py --help

Example run plan:

1. Confirm the user input, output path, and any required config values.

2. Edit the in-file `CONFIG` block or documented parameters if the script uses fixed settings.

3. Run `python scripts/main.py` with the validated inputs.

4. Review the generated output and return the final artifact with any assumptions called out.

Implementation Details

See `## Workflow` above for related details.

Quick Check

Use this command to verify that the packaged script entry point can be parsed before deeper execution.

python -m py_compile scripts/main.py

Audit-Ready Commands

Use these concrete commands for validation. They are intentionally self-contained and avoid placeholder paths.

python -m py_compile scripts/main.py
python scripts/main.py

Workflow

1. Confirm the user objective, required inputs, and non-negotiable constraints before doing detailed work.

2. Validate that the request matches the documented scope and stop early if the task would require unsupported assumptions.

3. Use the packaged script path or the documented reasoning path with only the inputs that are actually available.

4. Return a structured result that separates assumptions, deliverables, risks, and unresolved items.

5. If execution fails or inputs are incomplete, switch to the fallback path and state exactly what blocked full completion.

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:**

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

- If JSON validation fails, check source file encoding (UTF-8 expected) and re-run; inspect `--verbose` output for parsing errors

References

---

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

Output Requirements

Every final response should make these items explicit when they are relevant:

Error Handling

Input Validation

This skill accepts requests that match the documented purpose of `key-takeaways` and include enough context to complete the workflow safely.

Do not continue the workflow when the request is out of scope, missing a critical input, or would require unsupported assumptions. Instead respond:

> `key-takeaways` only handles its documented workflow. Please provide the missing required inputs or switch to a more suitable skill.

Response Template

Use the following fixed structure for non-trivial requests:

1. Objective

2. Inputs Received

3. Assumptions

4. Workflow

5. Deliverable

6. Risks and Limits

7. Next Checks

If the request is simple, you may compress the structure, but still keep assumptions and limits explicit when they affect correctness.