Skill-Details

tech-resume-optimizer

Directly optimizes resumes for technical roles.

ÜbereinstimmungDirektGeprüft für lebenslauf
Quelleparamchoudhary/resumeskillsExterne Quelle
Gemeldete Installationen6,026Nur Popularitätssignal

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SKILL.md

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---
name: tech-resume-optimizer
description: Optimize resumes for software engineering, PM, and technical roles
---

# Tech Resume Optimizer

## When to Use This Skill

Use this skill when the user:
- Is applying for software engineering roles
- Wants to optimize a technical resume
- Needs help with developer/PM/technical job applications
- Mentions: "tech resume", "software engineer resume", "developer resume", "technical resume", "SWE resume", "PM resume"

## Core Capabilities

- Optimize resumes for technical roles (SWE, PM, Data, DevOps)
- Structure technical skills sections effectively
- Highlight projects and technical achievements
- Balance technical depth with business impact
- Format for both ATS and technical recruiters
- Include GitHub, portfolio, and technical links

## Tech Resume Philosophy

**What Tech Recruiters Look For:**
1. Relevant technical skills (languages, frameworks, tools)
2. Scale and impact (users, transactions, data size)
3. Problem-solving abilities
4. System design understanding
5. Collaborative abilities
6. Growth trajectory

## Tech Resume Structure

### Recommended Order

```
1. Contact Information (including GitHub, Portfolio)
2. Professional Summary (optional but helpful)
3. Technical Skills (critical for ATS)
4. Work Experience (with technical achievements)
5. Projects (especially for early career)
6. Education
7. Certifications (if relevant)
```

### Contact Section for Tech

```
John Developer
San Francisco, CA
[email protected] | (555) 123-4567
LinkedIn: linkedin.com/in/johndev
GitHub: github.com/johndev
Portfolio: johndev.io
```

**Include:**
- GitHub (required for SWE roles)
- Portfolio/personal website
- LinkedIn
- Tech blog (if you have one)

**Don't Include:**
- Address (city/state is enough)
- Photo
- Social media (unless relevant)

## Technical Skills Section

### Organization Strategies

**Option 1: By Category**
```
Languages: Python, JavaScript, TypeScript, Go, SQL
Frameworks: React, Node.js, Django, FastAPI
Databases: PostgreSQL, MongoDB, Redis, Elasticsearch
Cloud/Infrastructure: AWS (EC2, S3, Lambda, RDS), Docker, Kubernetes, Terraform
Tools: Git, JIRA, CI/CD, Datadog, Grafana
```

**Option 2: By Proficiency** (use carefully)
```
Expert: Python, React, PostgreSQL, AWS
Proficient: Go, TypeScript, MongoDB, Docker
Familiar: Rust, GraphQL, Kubernetes
```

**Option 3: Flat List** (ATS-friendly)
```
Skills: Python, JavaScript, TypeScript, React, Node.js, Django, PostgreSQL, MongoDB, AWS, Docker, Kubernetes, Git
```

### What to Include

**Languages:**
- List languages you can code in confidently
- Order by relevance to target role
- Include query languages (SQL, GraphQL)

**Frameworks/Libraries:**
- Web: React, Vue, Angular, Django, Flask, Express
- Data: Pandas, NumPy, TensorFlow, PyTorch
- Testing: Jest, Pytest, Selenium

**Databases:**
- Relational: PostgreSQL, MySQL, SQL Server
- NoSQL: MongoDB, DynamoDB, Cassandra
- Caching: Redis, Memcached

**Cloud/DevOps:**
- Cloud: AWS, GCP, Azure (specific services)
- Containers: Docker, Kubernetes
- CI/CD: Jenkins, GitHub Actions, CircleCI
- IaC: Terraform, CloudFormation

### What NOT to Include
- ❌ Microsoft Office (assumed)
- ❌ Operating systems (unless DevOps role)
- ❌ Outdated tech (unless specifically required)
- ❌ Skill bars or ratings (subjective and break ATS)
- ❌ Every technology you've touched once

## Experience Section for Tech Roles

### The Technical Bullet Formula

**[Action Verb] + [Technical What] + [Scale/Impact] + [Technology Used]**

**Examples:**

❌ **Weak Technical Bullet:**
```
- Worked on backend services
- Helped improve system performance
- Built features for the product
```

✅ **Strong Technical Bullet:**
```
- Architected microservices migration from monolith, reducing deployment time from 2 hours to 15 minutes and enabling independent team deployments
- Optimized PostgreSQL queries and implemented Redis caching, reducing API latency by 60% (from 500ms to 200ms) for 100K daily active users
- Built real-time not
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