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Properly Hired

AI-powered career navigation platform built on Base44. Combines dual AI agents, RAG-backed knowledge retrieval, and O*NET occupational data to help job seekers analyze opportunities, optimize resumes, and prepare for interviews.

Features

AI Agents

Simon — Recruiting & HR Expert

  • Ghost job detection with 100-point scoring system
  • Role classification (Executive / Director / Manager / Professional tiers)
  • Job description quality evaluation and linguistic DNA extraction
  • Company research and industry benchmarking
  • Generates structured briefs for Kyle

Kyle — CV & Cover Letter Expert

  • Resume positioning and optimization strategies
  • Cover letter best practices with ARC formula
  • Interview preparation with STAR method templates
  • Bullet point optimization and achievement framing
  • Receives Simon's analysis to tailor application materials

Both agents collaborate via handoff — Simon analyzes the opportunity, Kyle builds the application package.

Core Pages

Category Pages Description
Job Tools Job Analysis, Job Matcher, Job Library, Job Details, Job Summary Analyze postings, match against resume, track opportunities
Resume My Resumes, Resume Builder, Resume Editor, Resume Optimizer, Resume Humanizer, Resume Quality, Resume Review, Resume Templates, Resume Viewer Full resume lifecycle — build, edit, optimize, review, export
Cover Letters Cover Letters, Cover Letter Generate and manage cover letters
Applications Application Tracker, Application Q&A, Autofill Vault Track applications, prepare portal answers, store reusable responses
Networking Networking Hub, Networking Messages, My Network, People Search, Recruiter Connect Professional networking and outreach tools
Intelligence Search Hub, External Resources, O*NET Insights, Activity Insights, Transferable Skills Cross-platform search, skill analysis, labor market data
Admin Agent Workspace, Agent Training, Agent Feedback Insights, Company Research Tool, Collaboration Dashboard, Users, O*NET Import, RAG Monitor Agent management, data import, knowledge base monitoring

RAG System

  • ragIngest — AI-powered knowledge ingestion with smart chunking, heading-aware splitting, and LLM summarization
  • ragRetrieve — Multi-signal retrieval with 8 scoring signals, LLM query expansion, and reranking
  • RAG Monitor — Admin dashboard for ingestion status, test queries, and knowledge base management
  • Knowledge Bases — Simon: 11 recruiting/HR resources (~6 MB), Kyle: 13 career coaching resources (~2.6 MB)

External Integrations

Function Service Purpose
queryONetAPI O*NET Web Services Occupational data and skill taxonomies
queryBLS Bureau of Labor Statistics Salary and employment data
queryDOL Department of Labor Compliance and labor regulations
queryLibraryOfCongress Library of Congress HR and talent management research
extractDocumentText mammoth Parse Word documents for resume import
brightdataCollect Bright Data Web data collection
firecrawlScrape Firecrawl Web scraping
githubQuery GitHub API Repository queries
notionSync Notion API Content synchronization

Project Structure

properly-hired/
├── src/
│   ├── pages/                  # 45 page components
│   ├── components/
│   │   ├── agents/             # AgentChat, handoff, prompts
│   │   ├── builder/            # CV wizard, voice capture, Q&A
│   │   ├── rag/                # RAG monitor panels
│   │   ├── ui/                 # 49 Radix-based UI components
│   │   └── utils/              # Access control, telemetry, device detection
│   ├── context/                # App context provider
│   ├── api/                    # Base44 client, AI integrations, job aggregator
│   ├── lib/                    # O*NET schemas, debug tools, query client
│   └── Layout.jsx              # Sidebar navigation, theming
├── functions/                  # 17 Deno serverless functions
├── agents/
│   ├── simon/                  # Simon base + enhanced Python agents
│   ├── kyle/                   # Kyle base + enhanced Python agents
│   ├── simon.jsonc             # Base44 agent config (Simon)
│   ├── kyle.jsonc              # Base44 agent config (Kyle)
│   ├── local_rag.py            # Local file-based RAG
│   └── rag_client.py           # RAG client with fallback
├── knowledge/
│   ├── simon/                  # 11 recruiting/HR knowledge files
│   └── kyle/                   # 13 CV/cover letter knowledge files
├── vite.config.js              # Vite + Base44 plugin
└── package.json

Getting Started

# Install dependencies
npm install

# Run development server
npm run dev

# Build for production
npm run build

Environment Variables

Variable Required Purpose
ONET_API_KEY For O*NET features O*NET Web Services API key
KYLE_OUTPUT_DIR Optional Override Kyle's CV output directory
KYLE_MASTER_CV_PATH Optional Override master CV file path
RAG_INTEGRATION_PATH Optional Override external RAG integration path

Tech Stack

  • Frontend: React 18, React Router 7, Vite, Tailwind CSS, Radix UI, Framer Motion
  • Backend: Base44 platform, Deno serverless functions
  • AI/RAG: Base44 LLM integration, local keyword RAG, multi-signal retrieval
  • Agents: Python (simon/kyle with enhanced variants), Base44 agent configs (.jsonc)
  • Data: O*NET occupational database, BLS employment data, curated knowledge bases

License

Proprietary

About

Base44 App: Prague Day

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