resume-bullet-extraction

DanielPodolsky's avatarfrom DanielPodolsky

Auto-invoke after task completion to generate powerful resume bullet points from completed work.

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When & Why to Use This Skill

The Resume Bullet Extraction skill automates the transformation of completed technical tasks into high-impact, professional resume bullet points. By utilizing a structured formula—Action Verb + Task + Technical Context + Impact—it ensures that every achievement is documented with quantifiable metrics and technical depth, helping users build a powerful 'highlight reel' of their career impact in real-time.

Use Cases

  • Post-Task Documentation: Automatically generating a professional achievement statement immediately after finishing a complex coding task or feature implementation.
  • Quantifying Technical Impact: Translating abstract improvements, such as database refactoring, into specific metrics like 'reducing API response time by 70%' for recruiter visibility.
  • STAR Method Preparation: Compiling a library of technical stories and bullets during a project to simplify future interview preparation and resume updates.
  • Recruiter-Friendly Translation: Converting highly specialized technical work into concise, value-driven sentences that demonstrate business impact to non-technical hiring managers.
nameResume Bullet Extraction
descriptionAuto-invoke after task completion to generate powerful resume bullet points from completed work.

Resume Bullet Extraction

"Your resume isn't a job description. It's a highlight reel of impact."

Purpose

Transform completed work into powerful resume bullet points that demonstrate value and technical competence.


The Bullet Formula

[Strong Action Verb] + [What You Did] + [Technical Context] + [Impact/Result]

Components

Component Purpose Example
Action Verb Shows initiative Engineered, Architected, Optimized
What You Did The accomplishment JWT authentication system
Technical Context Shows skill using React, Node.js, Redis
Impact Why it matters reducing auth errors by 40%

Strong Action Verbs

Building/Creating

  • Engineered
  • Architected
  • Developed
  • Implemented
  • Built
  • Designed

Improving

  • Optimized
  • Enhanced
  • Refactored
  • Modernized
  • Streamlined
  • Accelerated

Problem Solving

  • Resolved
  • Debugged
  • Eliminated
  • Reduced
  • Prevented
  • Mitigated

Leading/Collaborating

  • Led
  • Spearheaded
  • Collaborated
  • Mentored
  • Coordinated

Impact Quantification

Always try to quantify. If you can't measure directly, estimate reasonably.

Performance

  • "reducing load time by 60%"
  • "improving response time from 2s to 200ms"
  • "handling 10,000+ concurrent users"

Reliability

  • "achieving 99.9% uptime"
  • "eliminating production errors"
  • "reducing bug reports by 50%"

Business

  • "increasing user retention by 25%"
  • "supporting 50,000 monthly active users"
  • "saving 10 hours/week of manual work"

Scale

  • "processing 1M+ transactions daily"
  • "managing 500GB of user data"
  • "serving 100+ API endpoints"

Bullet Templates

Feature Implementation

[Verb] [feature] using [technologies] that [impact]

Examples:
- Engineered JWT authentication with refresh token rotation using Node.js and Redis, eliminating session hijacking vulnerabilities
- Built real-time notification system using WebSockets and React, improving user engagement by 35%

Performance Optimization

[Verb] [what] by [how], resulting in [metric]

Examples:
- Optimized database queries through index analysis and query restructuring, reducing API response time by 70%
- Accelerated page load performance by implementing code splitting and lazy loading, improving Core Web Vitals by 40%

Bug Fix / Problem Solving

[Verb] [problem] by [solution], preventing [impact]

Examples:
- Resolved race condition in checkout flow by implementing optimistic locking, preventing duplicate charges
- Eliminated memory leak in React components through proper cleanup, reducing crash reports by 90%

Architecture / Refactoring

[Verb] [system] from [old] to [new], enabling [benefit]

Examples:
- Migrated monolithic application to microservices architecture using Docker and Kubernetes, enabling independent team deployments
- Refactored authentication module from session-based to JWT, reducing server memory usage by 60%

Quality Checklist

  • Starts with strong action verb (not "Responsible for")
  • Includes specific technologies
  • Has quantifiable impact OR clear business value
  • Is one concise sentence
  • Avoids jargon recruiters won't understand
  • Demonstrates ownership ("I" is implied)
  • Would make sense to a technical interviewer

Bad vs Good Examples

Bad

❌ "Worked on the login system"
   - No action verb, no specifics, no impact

❌ "Responsible for user authentication"
   - Passive, no accomplishment shown

❌ "Helped with performance improvements"
   - Vague, no ownership, no metrics

Good

✅ "Engineered JWT authentication with refresh token rotation, reducing session vulnerability surface and supporting 50,000+ daily active users"

✅ "Optimized PostgreSQL queries through index analysis, reducing average API response time from 800ms to 120ms"

✅ "Built responsive dashboard using React and D3.js, enabling real-time visualization of 1M+ daily events"

Extraction Flow

Step 1: Identify the Highlight

"What's the most impressive aspect of what you just built?"

Options:

  • Technical complexity solved
  • Business problem addressed
  • Performance improved
  • Scale achieved
  • Security enhanced

Step 2: Draft the Bullet

Use the formula: Verb + What + Technical Context + Impact

Step 3: Quantify

"Can we add numbers? How much faster? How many users? What percentage improvement?"

Step 4: Polish

  • Remove weak words ("helped", "assisted", "worked on")
  • Add specific technologies
  • Ensure it stands alone (no context needed)

Resume Section Placement

Bullet Type Resume Section
Feature/System built Projects or Experience
Performance optimization Experience (shows impact)
Architecture decision Experience or Technical Skills
Learning/Growth Skills or Side Projects

Socratic Bullet Questions

  1. Finding impact: "If this feature didn't exist, what would break?"
  2. Quantifying: "How many users does this affect? How much time does it save?"
  3. Technical depth: "What would you tell a technical interviewer about how this works?"
  4. Differentiation: "What makes your implementation better than a basic solution?"

Save Location

Bullets are compiled in STAR story files:

mentorspec/career/stories/[date]-[feature-name].md

The resume bullet appears at the end of each story for easy extraction.