SkillBridge — AI-Powered Career Gap Analyzer

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  Skillbridge - Architecture Diagram

Inspiration

Nowadays, AI systems and Applicant Tracking tools shortlist resumes based on specific keywords and skill patterns — often scoring candidates before a human ever reads the profile. SkillBridge helps job seekers beat that system fairly by identifying what their resume lacks. It analyzes your resume using Google Gemini, highlights skill gaps, and suggests what to upskill or add — so your profile is more complete and stands out in AI-driven hiring pipelines.

What it does

SkillBridge is an AI-powered career assistant that analyzes resumes using Google Gemini 2.5 Pro and provides: • A concise Gap Summary of missing or underrepresented skills • A list of Missing Skills (technical and soft) • Recommended Certifications to pursue • Curated Learning Resources — including online courses and books It empowers professionals to discover where they stand, what skills they lack, and how to upskill strategically.

How we built it

• The core UI and analysis logic were vibe-coded in Google AI Studio, which generated the foundational React interface and Gemini integration workflow.
• We used the Google GenAI SDK that connects directly to the Gemini API, passing the extracted resume text and target role in the prompt — along with the desired JSON output format for structured, reliable results.
• The frontend was manually enhanced with UX improvements like Copy to Clipboard, Download as .txt, and Reset for a smooth user experience.
• The app was built using React + Tailwind CSS, containerized with Docker, and deployed on Google Cloud Run as a serverless web app.
• Build and deployment were automated using Google Cloud Build and Artifact Registry.

Prerequisites • Used the Google Cloud Platform credits provided for the hackathon. • Created a project in Google Cloud Console and generated a Gemini API key through Google AI Studio. • Set the API key as an environment variable (GEMINI_API_KEY) in Cloud Build and Cloud Run for secure access.

Challenges we ran into

• Managing environment variables securely between Cloud Build and Cloud Run.
• Maintaining consistent Tailwind CSS styling in production.
• Handling PDF, DOCX, and TXT resume formats gracefully in the browser.
• Ensuring Gemini consistently returned valid JSON responses for reliable parsing.

Accomplishments that we're proud of

• Given a meaningful structure to an idea that can truly help others understand and improve their careers.
• Learned a new framework from scratch and gained hands-on experience integrating Google Cloud Platform (GCP) into the code — being completely new to this cloud ecosystem.

What we learned

This project taught us a lot more than just coding. We explored Google Cloud Run, AI Studio, and Gemini APIs for the first time and learned how everything connects in the GCP ecosystem.

What's next for SkillBridge — AI-Powered Career Gap Analyzer

• Support multiple languages using Gemini’s translation capabilities, helping professionals from all regions.
• Integrate with LinkedIn or Google Jobs APIs to match skills and recommend real job opportunities.
• Introduce conversational analysis — enabling users to chat directly with the AI for deeper, more personalized resume insights.

Built With

• gemini-api
• google-ai-studio
• google-cloud-run
• google-genai-sdk
• react
• tailwind-css
• typescript
• vite