152 lines
4.0 KiB
Bash
152 lines
4.0 KiB
Bash
#!/bin/bash
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# Create directory structure
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mkdir -p \
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.cursor/rules \
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.cursor/config \
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.cursor/prompts \
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.notes/meeting_notes \
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scripts \
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utils
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# Create core configuration files
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cat > .cursor/rules/cv-platform-rules.mdc <<EOF
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**CV Platform Development Protocol**
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1. Security First:
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- Always sanitize user input using DOMPurify
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- Encrypt resume files with AES-256-GSM during storage
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2. LLM Implementation Rules:
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- Use OpenAI text-embedding-3-small for semantic analysis
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- Maintain 0.7 temperature for balance between creativity/accuracy
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- Verify ATS keyword suggestions against JobCopilot's latest data
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3. Task Management:
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- Reference .notes/task_list.md before making changes
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- Create atomic Git commits per feature using Conventional Commits
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EOF
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cat > .cursor/config/llm-params.json <<EOF
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{
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"defaultModel": "claude-3.5-sonnet-20240620",
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"fallbackModel": "gpt-4-turbo-2024-04-09",
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"temperature": {
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"codeGeneration": 0.3,
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"errorDebugging": 0.7
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},
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"contextWindow": 16000
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}
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EOF
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# Create task tracking system
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cat > .notes/task_list.md <<EOF
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## P-0: Critical Path (Current Sprint)
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- [ ] Implement PDF parser using PyPDF2 and @breezypdf/pdf-extract
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- [ ] Create ATS keyword mapping system (Due: 2025-03-01)
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## P-1: Near-Term Backlog
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- [ ] Design premium subscription flow
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- [ ] Research GDPR-compliant storage solutions
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## P-X: Innovation Pipeline
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- [ ] Experiment with Claude 3 Opus for cover letter generation
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EOF
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# Create prompt engineering files
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cat > .cursor/prompts/cv-analysis.md <<EOF
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# CV Enhancement Workflow
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1. **Structural Analysis**
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- Identify missing sections using industry benchmarks
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- Check chronological consistency of employment history
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2. **ATS Optimization**
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- Cross-reference with 50+ tracking systems
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- Generate keyword gap report
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3. **LLM Enhancement**
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- Rewrite summaries using power verbs
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- Convert responsibilities to measurable achievements
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EOF
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cat > .cursor/prompts/error-handling.md <<EOF
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**Debugging Process**
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1. Reproduce the error in isolation
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2. Analyze stack trace with @backend/logger.js
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3. Propose 3 potential solutions with pros/cons
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4. Implement safest option with rollback plan
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EOF
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# Create development workflow files
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cat > scripts/setup-environment.sh <<EOF
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#!/bin/zsh
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# Install core dependencies
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brew install poppler
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npm install -D eslint @types/node
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# Configure Cline models
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curl -O https://raw.githubusercontent.com/instructa/ai-prompts/main/cline-defaults.json
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# Setup Python virtualenv
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python -m venv .venv
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source .venv/bin/activate
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pip install -r requirements.txt
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EOF
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chmod +x scripts/setup-environment.sh
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# Create sample code files
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cat > utils/resume_analysis.py <<EOF
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from openai import OpenAI
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from pdfminer.high_level import extract_text
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client = OpenAI()
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def analyze_resume(file_path):
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text = extract_text(file_path)
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response = client.chat.completions.create(
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model="gpt-4-turbo",
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messages=[{
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"role": "system",
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"content": "Analyze resume for:\\n1. Missing ATS keywords\\n2. Skill gaps\\n3. Achievement opportunities"
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},
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{"role": "user", "content": text}]
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)
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return response.choices[0].message.content
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EOF
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cat > utils/pdf.worker.js <<EOF
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const { PDFDocument } = require('pdf-lib');
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self.addEventListener('message', async (e) => {
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const pdfDoc = await PDFDocument.load(e.data);
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const pages = pdfDoc.getPages();
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const textContent = pages.map(p => p.getTextContent());
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self.postMessage(textContent);
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});
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EOF
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# Create project documentation
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cat > .notes/project_overview.md <<EOF
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# CV Optimization Platform
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## Key Features
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- AI-powered resume analysis
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- ATS compliance checking
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- Real-time editing suggestions
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- GDPR-compliant storage
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## Tech Stack
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- React.js frontend
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- Node.js/Express.js backend
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- MongoDB database
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- OpenAI/Cline LLM integration
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EOF
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echo "Project structure created successfully!"
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echo "Next steps:"
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echo "1. Run 'chmod +x scripts/*.sh'"
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echo "2. Run 'scripts/setup-environment.sh'"
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echo "3. Install VS Code/Cursor extensions from .vscode/extensions.json"
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