PathFinder AI is an AI-powered career mentor designed for African students and professionals. It creates personalized career roadmaps from education to employment using Gemini, multi-agent systems, and real-time data. It recommends learning paths, bursaries, projects, and job opportunities tailored to local African contexts and opportunities.
# Pathfinder AI
A multi-agent **career guidance** system built with Google's Agent Development
Kit (ADK). Give it your background and a target role, and a team of specialized
agents will assess your skills, build a learning roadmap, find funding, plan a
portfolio, and prepare you for interviews — then synthesize everything into one
plan.
It uses ADK `Agent` definitions, `SequentialAgent`/`ParallelAgent`
orchestration, and a save-output-to-state callback so agents hand work to each
other through shared session state.
## Core Features
- **End-to-End Orchestration**: Seamlessly transitions from profile discovery to interview prep.
- **Evidence-Based Assessment**: Uses optional GitHub integration to validate technical skills.
- **Distributed Tools**: Leverages the Model Context Protocol (MCP) for out-of-process tool execution.
- **Graceful Degradation**: External API dependencies (YouTube, Search) are optional and fail silently with best-effort advice.
- **Privacy First**: Integrated PII filtering and explicit consent management for sensitive data.
## Architecture
```
pathfinder-ai/
├── agents/
│ ├── orchestrator.py # SequentialAgent + ParallelAgent pipeline + synthesizer
│ ├── discovery_agent.py # → user_profile
│ ├── skills_agent.py # → skill_assessment (career_skill, github_skill)
│ ├── roadmap_agent.py # → roadmap
│ ├── scholarship_agent.py # → scholarships
│ ├── portfolio_agent.py # → portfolio_plan (github_skill)
│ └── interview_agent.py # → interview_prep (interview_skill)
├── skills/ # Plain-function tools, passed to agents as ADK FunctionTools
│ ├── career_skill.py # role requirements, skill-gap comparison
│ ├── github_skill.py # GitHub profile analysis, portfolio ideas
│ └── interview_skill.py # question generation + answer rubric
├── mcp/ # Optional MCP servers (distributed tool sources)
│ ├── github_server.py
│ ├── youtube_server.py
│ └─ …