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.
Core Workflow:
- Scan: Analyzes job descriptions (simulated) for a target role (e.g., "Digital Marketing Manager") to identify high-demand skills.
- Sprint: Generates a specific, time-bound challenge (e.g., "48-hour content strategy sprint") based on identified skills.
- Asset: Accepts a user's solution summary and generates a professional PDF case study to be attached to job applications.
The project is structured as a Python CLI application with modularized logic in the src directory.
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 usingreportlab.
- Python 3.12+
- pip
-
Clone the repository:
git clone https://github.com/coad1024-cmd/skillproof-backend.git cd skillproof-backend -
Install dependencies:
pip install -r requirements.txt
To start the interactive CLI application:
python3 main_app.pyFollow the on-screen prompts to simulate the workflow:
- Enter your name and target role.
- "Fetch" job data.
- Receive a generated challenge.
- Input your solution summary.
- Generate the PDF portfolio asset.
- Modular Design: Logic is separated into
data,ai, andutilswithinsrc/to mimic a production-ready structure. - Mock Data: Current implementation relies on hardcoded mock data in
job_fetcher.pyandskill_engine.pyto simulate external API calls (Job Search APIs, OpenAI/Anthropic). - PDF Generation: Uses
reportlabfor programmatic PDF creation.