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AI Skill Report Card

Writing Technical Resumes

B+78·Feb 5, 2026·Source: Web

Technical Resume Writing

Create ATS-friendly tech resumes that get interviews by reverse engineering job descriptions and quantifying impact.

Quick Start

Input: Job description + current resume Output: Optimized resume with 90%+ keyword alignment and measurable outcomes

Target: "Backend Engineer - Python, AWS, microservices, 99.9% uptime"
Before: "Worked on backend services using Python"
After: "Developed Python microservices on AWS achieving 99.95% uptime for 500K+ users"
Recommendation▾
Add a concrete template section with actual resume format showing exact spacing, headers, and bullet structure that passes ATS systems
Workflow

Progress:

  • Analyze Job Description - Extract core skills, tools, metrics, and language patterns
  • Reverse Engineer Keywords - Map technical terms, certifications, and competency levels
  • Audit Current Resume - Identify gaps in skills, metrics, and terminology alignment
  • Quantify Impact - Convert duties to measurable outcomes using STAR/CAR framework
  • Optimize Content - Rewrite bullets with job-aligned language and keywords
  • Format for ATS - Ensure standard headings, no tables/graphics, clean parsing
  • Validate - Check keyword density and semantic matching
Recommendation▾
Include specific ATS testing tools or methods to validate keyword density and parsing compatibility
Examples

Example 1: Input: "Looking for DevOps Engineer - Kubernetes, CI/CD, monitoring" Current: "Managed deployments and infrastructure" Output: "Orchestrated Kubernetes deployments and CI/CD pipelines, reducing deployment time by 60% and improving system monitoring coverage to 95%"

Example 2: Input: "Frontend Developer - React, TypeScript, responsive design" Current: "Built web applications" Output: "Developed responsive React/TypeScript applications serving 100K+ users with 98% cross-browser compatibility"

Recommendation▾
Provide more granular before/after examples showing complete resume sections rather than single bullet points
Best Practices

Structure:

  • Strong technical summary with 3-5 core competencies
  • Skills section with proficiency levels (Expert/Advanced/Proficient)
  • Achievement-focused bullets: Action + Tool + Quantified Outcome
  • Keywords naturally integrated, not stuffed

Content Guidelines:

  • Use exact job posting terminology when possible
  • Include business impact alongside technical metrics
  • Show progression and increasing responsibility
  • Balance hard skills with relevant soft skills

ATS Optimization:

  • Standard section headers: "Professional Experience", "Technical Skills"
  • No headers/footers, tables, or graphics
  • Simple formatting with consistent fonts
  • Include both acronyms and full terms (ML/Machine Learning)
Common Pitfalls
  • Keyword stuffing - Integrate naturally within context
  • Vague metrics - "Improved performance" vs "Reduced latency by 40ms"
  • Generic bullets - Tailor each application to specific job requirements
  • Missing soft skills - Include leadership, communication, problem-solving
  • Outdated technologies - Focus on current/relevant tech stack
  • No business context - Always connect technical work to business outcomes
  • Poor formatting - Avoid creative layouts that break ATS parsing

Red Flags:

  • Tables for skills/experience sections
  • Multiple columns or text boxes
  • Images, logos, or graphics
  • Unusual section names or headers
  • Dense paragraphs instead of bullet points
0
Grade B+AI Skill Framework
Scorecard
Criteria Breakdown
Quick Start
11/15
Workflow
11/15
Examples
15/20
Completeness
15/20
Format
11/15
Conciseness
11/15
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