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Agent skill

Tech Resume Optimizer

by davila7 in davila7/claude-code-templates

Optimize resumes for software engineering, product management, and technical roles.

MITAuto-check passedBusiness, Finance & HR

Install Tech Resume Optimizer

skills CLI
$ npx skills add davila7/claude-code-templates --skill tech-resume-optimizer -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install davila7/claude-code-templates tech-resume-optimizer --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/davila7/claude-code-templates.git skills-src && mkdir -p .claude/skills && cp -r skills-src/cli-tool/components/skills/career/tech-resume-optimizer .claude/skills/tech-resume-optimizer && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
tech-resume-optimizer
GitHub stars
32k
Used in
1 other repo
Token cost
~2.7k tokens
SKILL.md length
631 words
Files
1
Skills in repo
477
Repo updated
First seen
Licence
MIT

At a glance

Optimize resumes for software engineering, product management, and technical roles.

  • Works in 6 steps: Relevant technical skills (languages,… → Scale and impact (users, transactions,… → Problem-solving abilities → …
  • The user mentions software engineer
  • SKILL.md covers When to Use This Skill, Core Capabilities, Tech Resume Philosophy and Tech Resume Structure, plus 7 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Tech Resume Optimizer is an agent skill from davila7/claude-code-templates. Optimize resumes for software engineering, product management, and technical roles. Use when the user mentions software engineer, developer, PM, data scientist, ML, DevOps, or other technical role resumes.

Its SKILL.md is about 2.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Business, Finance & HR, covering Resume and CV writing. The repository describes itself as: CLI tool for configuring and monitoring Claude Code. The licence is MIT.

When your agent uses it

  • The user mentions software engineer
  • Other technical role resumes

Example prompts

  • “/tech-resume-optimizer”

Requirements

  • Python 3
  • Node.js
  • Docker

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  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

What it can do on your machine

Read from SKILL.md and the folder at commit 14680ec. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Tech Resume Optimizer loads about 2.7k tokens when it runs. Until then it costs about 57 tokens; SKILL.md has 631 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~57
When it runs · the whole SKILL.md, loaded when a task matches
~2.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from davila7/claude-code-templates at commit 14680ec, republished under its MIT licence (© davila7). 631 words, ~2,659 tokens.

Download SKILL.mdSave it as .claude/skills/tech-resume-optimizer/SKILL.md (or your agent's skills folder).
name
tech-resume-optimizer
description
Optimize resumes for software engineering, product management, and technical roles. Use when the user mentions software engineer, developer, PM, data scientist, ML, DevOps, or other technical role resumes.

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

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
john@email.com | (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 notification system using WebSockets and AWS SNS, handling 1M+ messages daily with 99.9% delivery rate
Technical Metrics to Include

Scale:

  • Users: "serving 500K DAU"
  • Requests: "handling 10K requests/second"
  • Data: "processing 50TB daily"
  • Uptime: "maintaining 99.99% availability"

Performance:

  • Latency: "reduced from Xms to Yms"
  • Speed: "improved by X%"
  • Load time: "decreased by X seconds"

Efficiency:

  • Cost: "reduced AWS costs by 40%"
  • Time: "cut deployment time from X to Y"
  • Resources: "reduced memory usage by X%"

Business:

  • Revenue: "features drove $XM revenue"
  • Conversion: "improved checkout by X%"
  • Engagement: "increased DAU by X%"
Show full SKILL.md (256 more words)Show less
Role-Specific Bullet Examples

Software Engineer:

• Designed and implemented authentication service using OAuth 2.0 and JWT, securing 2M+ user accounts with zero security incidents
• Led migration to Kubernetes, achieving 99.99% uptime and reducing infrastructure costs by 35% ($200K annually)
• Mentored 3 junior engineers through code reviews and pair programming, improving team velocity by 25%

Data Engineer:

• Built data pipeline processing 100M+ events daily using Apache Kafka and Spark, reducing data latency from hours to minutes
• Designed data warehouse schema in Snowflake, enabling self-service analytics for 50+ business users
• Implemented data quality monitoring with Great Expectations, catching 95% of data issues before impacting downstream systems

DevOps/SRE:

• Implemented infrastructure as code using Terraform, reducing provisioning time from 2 days to 30 minutes
• Built monitoring and alerting system with Prometheus and Grafana, reducing MTTR from 4 hours to 30 minutes
• Automated deployment pipeline with GitHub Actions, enabling 50+ daily deployments with zero-downtime releases

Product Manager (Technical):

• Led API platform roadmap for developer tools used by 10K+ developers, driving 40% increase in API adoption
• Defined technical requirements for ML recommendation engine, resulting in 25% increase in user engagement
• Partnered with engineering to reduce technical debt by 30%, improving release velocity from bi-weekly to weekly

Projects Section

Critical for:

  • Junior engineers
  • Career changers
  • Bootcamp graduates
  • Anyone with gaps
Project Format
Project Name | Technologies | Link
• Description of what it does
• Technical highlights and challenges solved
• Scale or usage metrics if available
Example Projects Section
PROJECTS

Distributed Task Queue | Python, Redis, Docker | github.com/user/taskqueue
• Built distributed task queue handling 10K+ jobs/hour with automatic retries and dead letter queue
• Implemented priority queuing and rate limiting for multi-tenant support

Real-time Chat App | React, Node.js, WebSocket, MongoDB | chatapp.demo.com
• Full-stack chat application supporting 100+ concurrent users with real-time messaging
• Implemented end-to-end encryption and message persistence

ML Price Predictor | Python, TensorFlow, FastAPI | github.com/user/predictor
• Trained regression model on 1M+ data points achieving 92% accuracy for price prediction
• Deployed as REST API with automatic model retraining pipeline
What Makes a Good Project

Do Include:

  • Projects with real users
  • Open source contributions
  • Technical blog posts
  • Hackathon projects (especially winners)
  • Complex personal projects

Don't Include:

  • Tutorial follow-alongs
  • Trivial to-do apps
  • Incomplete projects
  • Coursework (unless exceptional)

Education Section for Tech

Standard Format
B.S. Computer Science | Stanford University | 2020
GPA: 3.8/4.0 (include if above 3.5)
Relevant Coursework: Distributed Systems, Machine Learning, Database Systems
For Bootcamp Graduates
Software Engineering Certificate | App Academy | 2023
- 1000+ hour immersive program
- Full-stack JavaScript, React, Node.js, PostgreSQL

B.A. Economics | UCLA | 2020
For Self-Taught Engineers
Professional Certifications:
- AWS Solutions Architect Associate | 2023
- MongoDB Certified Developer | 2023

Relevant Education:
- MIT OpenCourseWare: Algorithms, Data Structures
- Coursera: Machine Learning Specialization (Stanford)

Tech-Specific Tips

GitHub Profile Optimization

Make sure your GitHub shows:

  • Pinned repositories (your best 6)
  • Green contribution graph (activity)
  • README for profile
  • Complete project READMEs

Project READMEs should include:

  • What the project does
  • Technologies used
  • How to run it
  • Screenshots/demos
  • Your contributions (for collaborative projects)
Dealing with Tech Stacks

If you match their stack:

  • Lead with those technologies
  • Quantify your experience with them

If you don't match exactly:

  • Emphasize transferable skills
  • Show learning ability
  • Highlight similar technologies
  • Example: "Django" → "Extensive Python web framework experience (Django); quick to ramp on new frameworks"
Technical Interviews Prep Note

Tech resumes should support your interview:

  • Only claim technologies you can discuss deeply
  • Be ready to explain every project listed
  • Know the architecture of systems you've built
  • Have stories ready for each bullet

Output Format

When optimizing a tech resume:

markdown
# TECH RESUME OPTIMIZATION

## Technical Skills Restructure
**Current:** [Their current skills section]
**Optimized:**
Languages: [Ordered list]
Frameworks: [Ordered list]
Databases: [Ordered list]
Cloud/Tools: [Ordered list]

## Experience Improvements

### [Company/Role]

**Current Bullet 1:**
"Worked on backend services"

**Improved:**
"Designed and deployed 5 Node.js microservices handling 50K requests/minute, reducing system coupling and enabling independent team deployments"

**Current Bullet 2:**
[Continue for each bullet]

## Projects to Highlight
[Suggestions based on their background]

## GitHub Recommendations
- [ ] Add READMEs to pinned repos
- [ ] Pin X project (most relevant)
- [ ] Add profile README

## Technical Gaps to Address
- [Missing skill] → [How to address in resume/cover letter]

ATS + Tech Recruiter Balance

Remember: Your resume must pass ATS AND impress technical recruiters.

For ATS:

  • Include exact skill keywords
  • Use standard section headers
  • Avoid tables and graphics

For Tech Recruiters:

  • Show technical depth
  • Include metrics and scale
  • Demonstrate problem-solving
  • Show you understand systems

© davila7, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in cli-tool/components/skills/career/tech-resume-optimizer of davila7/claude-code-templates.

Open the folder on GitHubat commit 14680ec

Used in 1 other repository

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in davila7/claude-code-templates, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Tech Resume Optimizer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Tech Resume Optimizer compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Tech Resume Optimizer this skilldavila7/claude-code-templates32k1 repos~2.7kAutomated safety check: PassMIT
Backend and Agent Project Selectorlishuangqiang/backend-agent-resume-scout347—~1.4kAutomated safety check: PassApache-2.0
Resume Jd Optimizer Cncoinluu/resume-jd-optimizer-cn1901 repos~1.3kAutomated safety check: PassMIT
Autothesun4sky/jobstack143—~2.9kAutomated safety check: NotesMIT
Build Tailored ResumeSankaiAI/ats-optimized-resume-agent-skill106—~4.4kAutomated safety check: NotesMIT
Career Historythesun4sky/jobstack143—~2.3kAutomated safety check: NotesMIT

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Categories

Questions about Tech Resume Optimizer

What does Tech Resume Optimizer do?

Optimize resumes for software engineering, product management, and technical roles. Tech Resume Optimizer is an agent skill from davila7/claude-code-templates. Optimize resumes for software engineering, product management, and technical roles.

When should I use Tech Resume Optimizer?

Tech Resume Optimizer fits situations like: the user mentions software engineer; other technical role resumes.

How do I install Tech Resume Optimizer in Claude Code?

Run `npx skills add davila7/claude-code-templates --skill tech-resume-optimizer -a claude-code`. Or copy the skill folder (cli-tool/components/skills/career/tech-resume-optimizer in davila7/claude-code-templates) into .claude/skills/tech-resume-optimizer in your project. Claude Code loads it when a task matches its description.

How do I install Tech Resume Optimizer in Codex?

Run `npx skills add davila7/claude-code-templates --skill tech-resume-optimizer -a codex`. Or copy the skill folder (cli-tool/components/skills/career/tech-resume-optimizer in davila7/claude-code-templates) into .agents/skills/tech-resume-optimizer in your project. Codex loads it when a task matches its description.

Can I use Tech Resume Optimizer in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add davila7/claude-code-templates --skill tech-resume-optimizer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/tech-resume-optimizer, .gemini/skills/tech-resume-optimizer, .github/skills/tech-resume-optimizer and .opencode/skills/tech-resume-optimizer in your project.

What does Tech Resume Optimizer need to run?

SKILL.md names no scripts, command-line tools or credentials: Tech Resume Optimizer is instructions for the agent only. Our summary lists: Python 3; Node.js; Docker.

Does Tech Resume Optimizer access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Tech Resume Optimizer safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Tech Resume Optimizer use?

Tech Resume Optimizer is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Tech Resume Optimizer use?

About 2.7k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Tech Resume Optimizer?

Skills that share tags, products or a category with Tech Resume Optimizer: Backend and Agent Project Selector (lishuangqiang/backend-agent-resume-scout, 347 stars), Resume Jd Optimizer Cn (coinluu/resume-jd-optimizer-cn, 190 stars), Auto (thesun4sky/jobstack, 143 stars) and Build Tailored Resume (SankaiAI/ats-optimized-resume-agent-skill, 106 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Tech Resume Optimizer?

davila7 (a GitHub user) maintains it in davila7/claude-code-templates, which has 32,463 GitHub stars. The repository holds 477 skills in this directory. The repository was last updated on October 8, 2026.

Source: davila7/claude-code-templates on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.