Execsum Deal Brief

Abstract

1. Introduction

Deal size alone does not determine the ranking. Anonymous sources are never presented as experts, and missing deal terms are labeled as undisclosed.

The OpenAI integration follows the official Responses API pattern with the web_search tool and Structured Outputs. Web citations are rendered as visible, clickable links in the email.

2. Objective

Automated daily Exec Sum deal-flow brief with Top 3 deal ranking, sourced expert insights, IB analysis, and Gmail delivery.

This project demonstrates how Python can be applied to a real-world Digital Marketing & SEO problem.

4. Technology Stack

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

• Python 3.8 or later
• pip / virtualenv for dependencies
• VS Code, PyCharm or Jupyter Notebook
• Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/kklounge/execsum-deal-brief.git
cd execsum-deal-brief

python -m venv .venv
source .venv/bin/activate
python -m pip install .

export OPENAI_API_KEY="..."
export GMAIL_ADDRESS="you@gmail.com"
export GMAIL_APP_PASSWORD="your-16-character-app-password"
export RECIPIENT_EMAIL="you@gmail.com"

python -m execsum_deal_brief.main --dry-run
python -m execsum_deal_brief.main

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

• Export reports to Google Sheets or PDF
• Schedule weekly automated reports
• Add competitor comparison

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

1. Which marketing or SEO problem does this tool solve?
2. Which data sources or APIs does it use (Search Console, Analytics, social platforms)?
3. Which metrics or KPIs does it report and how are they calculated?
4. How could the output help a business make decisions?
5. How would you schedule it to run automatically?

9. Source Code & License

This project is developed by kklounge and published on GitHub under the MIT License. Please follow the license terms and credit the original author when you use or modify this code.