alijilani-dev/ai-driven_development/cover-letter-generator

Cover Letter Generator

Generate PSI-formatted cover letters tailored to LinkedIn AI job postings.

Workflow

Step 1: Analyze Resume

Extract and analyze the applicant's resume:

python3 scripts/extract_resume.py "<path_to_resume.docx>"

Identify from the resume:

• Core technical stack: Languages, frameworks, platforms
• Quantified achievements: Metrics, percentages, business outcomes
• Domain experience: Industries, project types, team sizes
• AI/ML specific skills: Models, pipelines, tools

Step 2: Market Intelligence

Based on the resume profile, identify the top 3 AI skills currently in demand:

Common high-demand AI skills (2024-2025):

• RAG (Retrieval-Augmented Generation) pipelines
• Agentic AI workflows (LangGraph, AutoGen, CrewAI)
• LLMOps / MLOps (deployment, monitoring, fine-tuning)
• Prompt engineering & context optimization
• Vector databases & semantic search
• Multi-modal AI systems

Match resume skills to market demand to identify positioning strategy.

Step 3: LinkedIn Research

Use browsing-with-playwright skill or Playwright MCP to search LinkedIn for relevant jobs:

Search Strategy:

1. Navigate to LinkedIn Jobs: https://www.linkedin.com/jobs/
2. Search terms combining: [Primary Skill] + [Secondary Skill] + [Location/Remote]

• Example: "Agentic AI Developer Remote"
• Example: "RAG Engineer LLMOps"

1. Find 2 relevant job postings matching the profile
2. For each job, extract:

• Company name and job title
• Key technical requirements
• Company's AI focus/challenges (from description)
• Hiring manager name (if visible)

Step 4: Bridge the Capability Gap

For each job posting, create a PSI mapping:

Constraint: Never fabricate experience. Reframe existing resume data to address the job's specific challenges.

Step 5: Generate Cover Letters

Create 2 cover letters using the PSI template. See references/psi_template.md.

Requirements:

• Follow PSI format strictly (Problem -> Solution -> Impact)
• Integrate all 5 quality pillars from references/quality_pillars.md
• Maintain professional, technical, impact-oriented tone
• Ensure "Translation Layer" is evident (explaining AI to stakeholders)
• Hyper-personalize to each company's context

Quality Checklist:

• [ ] Problem identifies company's specific AI challenge
• [ ] Solution uses concrete tools/methods from resume
• [ ] Impact includes quantified metrics
• [ ] Mentions Responsible AI / ethics alignment
• [ ] Demonstrates learning velocity (current tech awareness)
• [ ] References company-specific information
• [ ] Written with clarity for non-technical readers

Output Format

Deliver 2 complete cover letters, each with:

1. Header (name, LinkedIn, GitHub)
2. Subject line targeting company's challenge
3. PSI body paragraphs
4. Professional closing

Save as: cover_letter_[company_name].md