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SkillProof Backend

SkillProof is an "AI Portfolio Factory" CLI prototype designed to help candidates create verifiable portfolio assets (PDF case studies) based on real-time job market data.

🚀 Project Overview

Core Workflow:

  1. Scan: Analyzes job descriptions (simulated) for a target role (e.g., "Digital Marketing Manager") to identify high-demand skills.
  2. Sprint: Generates a specific, time-bound challenge (e.g., "48-hour content strategy sprint") based on identified skills.
  3. Asset: Accepts a user's solution summary and generates a professional PDF case study to be attached to job applications.

🏗 Architecture

The project is structured as a Python CLI application with modularized logic in the src directory.

Directory Structure

  • main_app.py: The CLI entry point orchestrating the user flow.
  • landing.html: A static HTML landing page for the product concept.
  • requirements.txt: Python dependencies.
  • src/:
    • ai/skill_engine.py: Logic for extracting skills from job data and generating challenge prompts.
    • data/job_fetcher.py: Handles fetching of job listings.
    • utils/pdf_generator.py: Generates the final PDF case study using reportlab.

🛠 Getting Started

Prerequisites

  • Python 3.12+
  • pip

Installation

  1. Clone the repository:

    git clone https://github.com/coad1024-cmd/skillproof-backend.git
    cd skillproof-backend
  2. Install dependencies:

    pip install -r requirements.txt

Usage

To start the interactive CLI application:

python3 main_app.py

Follow the on-screen prompts to simulate the workflow:

  1. Enter your name and target role.
  2. "Fetch" job data.
  3. Receive a generated challenge.
  4. Input your solution summary.
  5. Generate the PDF portfolio asset.

📝 Development Notes

  • Modular Design: Logic is separated into data, ai, and utils within src/ to mimic a production-ready structure.
  • Mock Data: Current implementation relies on hardcoded mock data in job_fetcher.py and skill_engine.py to simulate external API calls (Job Search APIs, OpenAI/Anthropic).
  • PDF Generation: Uses reportlab for programmatic PDF creation.

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