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Resume Section Builder

CommunityPopular
Paramchoudhary
resume-section-builder

Create targeted resume sections optimized for different experience levels and roles

Overview

PublisherParamchoudhary
RepositoryResumeSkills
Skill nameresume-section-builder
Stars
2.3K
Forks
197
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Paramchoudhary on GitHub. Read the source before you install it.

Installation

Install the Resume Section Builder AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Paramchoudhary/ResumeSkills.git /tmp/ResumeSkills
mkdir -p .claude/skills
cp -r /tmp/ResumeSkills/skills/resume-section-builder .claude/skills/resume-section-builder
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Resume Section Builder in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Resume Section Builder on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Resume Section Builder is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Resume Section Builder

When to Use This Skill

Use this skill when the user:

  • Needs help with specific resume sections
  • Wants to optimize a particular part of their resume
  • Is unsure what to include in a section
  • Needs section-specific guidance
  • Mentions: "resume sections", "skills section", "summary section", "experience section", "what to include"

Core Capabilities

  • Build targeted professional summaries
  • Structure skills sections effectively
  • Optimize experience sections
  • Create education sections appropriately
  • Add supplementary sections strategically
  • Tailor sections for different career stages

Professional Summary Section

When to Include

Include Summary If:

  • Career changers (need to explain transition)
  • Senior professionals (distill long career)
  • Returning to workforce (address gaps)
  • Highly specialized role (emphasize fit)

Skip Summary If:

  • Entry level with limited experience
  • Straightforward career progression
  • Space is at a premium

Summary Framework

Formula: [Title/Identity] + [Years/Experience] + [Key Skills] + [Value Proposition]

By Career Stage

Entry Level:

Recent Computer Science graduate from UC Berkeley with internship experience in full-stack development. Skilled in Python, React, and AWS. Seeking to leverage academic projects in machine learning and user-facing application development in a software engineering role.

Mid-Career:

Product Manager with 6 years driving B2B SaaS products from concept to scale. Track record of launching products that generated $10M+ ARR through data-driven roadmap prioritization and cross-functional leadership. Expert in API products, developer tools, and enterprise sales motions.

Senior/Executive:

Technology executive with 15+ years building and scaling engineering organizations from 50 to 500+ across global markets. Proven success leading digital transformation initiatives, M&A integration, and platform modernization. P&L ownership of $100M+ with track record of 40%+ efficiency improvements.

Career Changer:

Sales professional transitioning to Customer Success, bringing 5 years of consultative selling experience and proven ability to build lasting client relationships. Skilled in needs assessment, solution design, and stakeholder management. Seeking to apply relationship-building expertise to drive customer retention and expansion.

Summary Don'ts

  • ❌ "Seeking a challenging position..."
  • ❌ "Hard-working team player..."
  • ❌ "Results-oriented professional..."
  • ❌ Third person ("John is a...")
  • ❌ Objectives (what you want vs. what you offer)

Skills Section

Organization Options

Option 1: Simple List

SKILLS
Python, JavaScript, SQL, React, Node.js, AWS, Docker, Git, Agile, JIRA

Best for: ATS optimization, space constraints

Option 2: Categorized

TECHNICAL SKILLS
Languages: Python, JavaScript, TypeScript, SQL
Frameworks: React, Node.js, Django, FastAPI
Cloud: AWS (EC2, S3, Lambda), GCP, Docker, Kubernetes
Tools: Git, JIRA, Confluence, Datadog

Best for: Technical roles, extensive skill sets

Option 3: Proficiency Levels (use carefully)

SKILLS
Expert: Python, SQL, Product Management
Advanced: AWS, Data Analysis, Stakeholder Management
Proficient: Machine Learning, Figma, Financial Modeling

Best for: Roles requiring specific proficiency, honest representation

What to Include

Technical/Hard Skills:

  • Programming languages
  • Software and tools
  • Methodologies (Agile, Lean)
  • Platforms (Salesforce, SAP)
  • Certifications

Functional Skills:

  • Project management
  • Financial analysis
  • Data analysis
  • Market research

Industry Knowledge:

  • Domain expertise
  • Regulatory knowledge
  • Industry certifications

What to Exclude

  • ❌ Microsoft Office (assumed)
  • ❌ "Basic" skills
  • ❌ Skills you can't discuss in interview
  • ❌ Soft skills (show, don't list)
  • ❌ Outdated technologies

Experience Section

Standard Format

COMPANY NAME | City, State
Job Title | Start Date - End Date

• Achievement bullet with metric and impact
• Achievement bullet with metric and impact
• Achievement bullet with metric and impact

Bullet Guidelines by Career Stage

Entry Level (0-2 years):

  • 3-5 bullets per role
  • Include relevant projects
  • Quantify where possible
  • Show initiative and learning

Mid-Career (3-10 years):

  • 4-6 bullets for recent roles
  • 2-3 bullets for older roles
  • Focus on achievements over duties
  • Strong metrics throughout

Senior (10+ years):

  • 5-6 bullets for recent roles
  • 2-3 bullets for older roles
  • Emphasize leadership and strategy
  • Show increasing scope

Handling Different Situations

Multiple Roles at Same Company:

COMPANY NAME | City, State
Senior Manager | 2021 - Present
• [Bullets for current role]

Manager | 2019 - 2021
• [Bullets for previous role]

Analyst | 2017 - 2019
• [Bullets for earliest role]

Short Tenure:

  • Include if relevant experience
  • Frame around project or achievement
  • Don't apologize or explain in resume

Contract/Freelance:

Freelance Product Consultant | 2022 - Present
Clients include: Company A, Company B, Company C
• [Achievement with Client A]
• [Achievement with Client B]

Education Section

Standard Format

EDUCATION

Bachelor of Science in Computer Science
University of California, Berkeley | 2020
GPA: 3.8/4.0 | Honors: Magna Cum Laude

What to Include by Career Stage

Entry Level:

  • Degree, major, school, year
  • GPA (if 3.5+)
  • Honors and awards
  • Relevant coursework
  • Academic projects
  • Study abroad

Mid-Career:

  • Degree, major, school, year
  • GPA only if exceptional
  • Skip coursework (replaced by experience)

Senior:

  • Degree, school
  • May skip year (age discrimination)
  • Professional development more relevant

Advanced Degrees

MBA, Finance & Strategy
Harvard Business School | 2022
• Leadership Fellow
• Relevant coursework: Corporate Finance, M&A Strategy

M.S. in Computer Science
Stanford University | 2018
• Specialization: Artificial Intelligence
• Thesis: "Title of Thesis"

Certifications

CERTIFICATIONS
AWS Solutions Architect Associate | Amazon Web Services | 2023
PMP (Project Management Professional) | PMI | 2022
Google Analytics Certified | Google | 2023

Additional Sections

When to Include Each

Projects Section:

  • Entry level with limited work experience
  • Career changers showing new skills
  • Technical roles with personal projects

Volunteer Section:

  • Relevant volunteer experience
  • Leadership roles
  • Fills employment gaps meaningfully

Languages:

  • If relevant to role/company
  • List proficiency levels accurately
  • Only if beyond basic conversational

Publications/Patents:

  • Academic positions
  • Research roles
  • Technical thought leadership

Awards/Recognition:

  • Significant industry awards
  • Company-wide recognition
  • Relevant honors

Format Examples

Projects:

PROJECTS
E-commerce Platform | React, Node.js, PostgreSQL | github.com/user/project
• Built full-stack marketplace with 500+ active users
• Implemented payment processing with Stripe integration

Volunteer:

VOLUNTEER EXPERIENCE
Board Member | Local Nonprofit | 2021 - Present
• Led fundraising committee, increasing annual donations by 40%

Languages:

LANGUAGES
English (Native) | Spanish (Professional) | Mandarin (Conversational)

Section Order by Role Type

Standard Order

  1. Contact
  2. Summary (optional)
  3. Skills
  4. Experience
  5. Education
  6. Additional

Technical Roles

  1. Contact
  2. Skills (prioritized)
  3. Experience
  4. Projects
  5. Education
  6. Certifications

Recent Graduate

  1. Contact
  2. Education (prioritized)
  3. Skills
  4. Experience/Internships
  5. Projects
  6. Activities

Executive

  1. Contact
  2. Executive Summary
  3. Career Highlights
  4. Experience
  5. Board Roles
  6. Education

Career Changer

  1. Contact
  2. Summary (explaining transition)
  3. Skills (transferable)
  4. Experience (reframed)
  5. Bridge Experience
  6. Education

Output Format

When building resume sections:

markdown
# RESUME SECTION RECOMMENDATIONS

## For: [User's situation/role]

### Recommended Section Order
1. [Section] - [Why]
2. [Section] - [Why]
...

### Section Details

#### Professional Summary
**Recommendation:** [Include/Skip]
**Draft:**
[Written summary if recommended]

#### Skills Section
**Format:** [Simple/Categorized/Proficiency]
**Content:**
[Organized skills list]

#### Experience Section
**Format:** [Standard/Functional/Hybrid]
**Bullets per Role:**
- Recent: [X] bullets
- Older: [X] bullets

#### Education Section
**Include:**
- [Items to include]
**Exclude:**
- [Items to exclude]

#### Additional Sections
**Recommended:** [Section name] because [reason]
**Skip:** [Section name] because [reason]

Section-Building Checklist

  • ✅ Section order optimized for role
  • ✅ Summary is concise and targeted (if included)
  • ✅ Skills are relevant and organized
  • ✅ Experience bullets are achievement-focused
  • ✅ Education appropriate for career stage
  • ✅ Additional sections add value (not filler)
  • ✅ Consistent formatting throughout
  • ✅ All sections support the target role
  • ✅ Nothing irrelevant or outdated included
  • ✅ Total length appropriate (1-2 pages)

Frequently asked questions

What does the Resume Section Builder AI skill do?

Create targeted resume sections optimized for different experience levels and roles

Why use Resume Section Builder on TypingMind?

Because you install it once and use it with any model. Resume Section Builder is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Resume Section Builder in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Paramchoudhary/ResumeSkills/tree/main/skills/resume-section-builder. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Resume Section Builder?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Resume Section Builder?

As many as you like. As long as a model supports skills, you can use Resume Section Builder with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Resume Section Builder AI skill free?

Yes. It is published on GitHub by Paramchoudhary under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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