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Academic Cv Builder

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Paramchoudhary
academic-cv-builder

Format CVs for academic positions with publications, grants, and teaching

Overview

PublisherParamchoudhary
RepositoryResumeSkills
Skill nameacademic-cv-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 Academic Cv 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/academic-cv-builder .claude/skills/academic-cv-builder
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Academic Cv 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 Academic Cv 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 Academic Cv 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.

Academic CV Builder

When to Use This Skill

Use this skill when the user:

  • Is applying for academic positions (faculty, research, postdoc)
  • Needs to create or update a curriculum vitae
  • Wants to format publications, grants, and teaching experience
  • Is in academia or transitioning to academic careers
  • Mentions: "academic CV", "curriculum vitae", "faculty position", "research CV", "professor resume"

Core Capabilities

  • Structure CVs for academic positions
  • Format publications, presentations, and grants
  • Organize teaching and research experience
  • Include appropriate academic sections
  • Tailor for different academic roles (tenure-track, postdoc, lecturer)
  • Balance research, teaching, and service

Academic CV vs. Resume

ResumeAcademic CV
1-2 pages2-20+ pages (length increases with career)
Highlights relevant experienceComprehensive record
Results-focusedScholarship-focused
Industry keywordsDisciplinary expertise
Skills section prominentPublications prominent
Education minimalEducation detailed

Standard Academic CV Sections

Typical Order

1. Contact Information
2. Education
3. Research/Academic Positions
4. Publications
5. Presentations
6. Grants & Funding
7. Teaching Experience
8. Mentoring
9. Service
10. Professional Memberships
11. Honors & Awards
12. References (or "Available upon request")

Section Order Varies By:

  • Research position: Publications, grants, research experience first
  • Teaching position: Teaching, course development first
  • Administrative position: Leadership, service first

Section-by-Section Guide

1. Contact Information

FIRST MIDDLE LAST, Ph.D.
Department of [Field]
[University Name]
[Building, Room Number]
[City, State ZIP]

Email: email@university.edu
Phone: (555) 123-4567
Web: www.yoursite.edu
ORCID: 0000-0000-0000-0000

2. Education

Format: Degree, Field, Institution, Year

EDUCATION

Ph.D. in Molecular Biology, Stanford University, 2019
  Dissertation: "Title of Your Dissertation"
  Advisor: Dr. Jane Smith
  Committee: Dr. A, Dr. B, Dr. C

M.S. in Biology, UC Berkeley, 2015

B.S. in Biochemistry, UCLA, 2013
  Summa Cum Laude

Include:

  • All degrees (in reverse chronological order)
  • Dissertation/thesis title
  • Advisor(s)
  • Committee members (for PhD)
  • Honors (cum laude, etc.)
  • Relevant minors or certificates

3. Research/Academic Positions

ACADEMIC APPOINTMENTS

Assistant Professor of Biology, University of Michigan, 2022-Present
  Department of Molecular, Cellular, and Developmental Biology

Postdoctoral Fellow, MIT, 2019-2022
  Advisor: Dr. John Doe
  Lab: Computational Biology Lab

Graduate Research Assistant, Stanford University, 2014-2019
  Advisor: Dr. Jane Smith

4. Publications

Most Important Section for Research Positions

Formatting Options

Option 1: Numbered List (Common in Sciences)

PUBLICATIONS

Peer-Reviewed Journal Articles

15. Last, F.M., Co-Author, A.B., & Senior, C.D. (2023). Article title. Journal Name, 45(2), 123-145. doi:10.1000/xyz

14. Last, F.M., & Co-Author, A.B. (2022). Article title. Journal Name, 44(1), 10-25. doi:10.1000/abc

Option 2: Categories (Useful for Multiple Types)

PUBLICATIONS

Peer-Reviewed Journal Articles (15)

Book Chapters (3)

Books (1)

Under Review (2)

In Preparation (3)

Formatting Details:

  • Bold your name in author lists
  • Include DOIs when available
  • Note impact factors if requested/relevant
  • Indicate student co-authors with asterisk*
  • Some fields expect reverse chronological; others expect chronological

Categories to Consider:

  • Peer-reviewed journal articles
  • Books and book chapters
  • Conference proceedings
  • Technical reports
  • Non-peer-reviewed publications
  • Works under review
  • Works in preparation

5. Presentations

PRESENTATIONS

Invited Talks

"Talk Title," Conference Name, Location, Date.
"Talk Title," Department Seminar, University Name, Date.

Conference Presentations

"Poster/Talk Title," Conference Name, Location, Date. [Poster/Oral]

Categorize By:

  • Invited talks (keynotes, seminars)
  • Conference presentations
  • Campus talks
  • Public lectures/outreach

6. Grants & Funding

GRANTS AND FUNDING

Awarded

NIH R01 (Co-PI), "Project Title," 2023-2028, $2.5M total ($500K to my lab)

NSF CAREER Award (PI), "Project Title," 2022-2027, $650,000

Internal Grant (PI), "Project Title," 2021, $25,000

Pending

NIH R21 (PI), "Project Title," submitted January 2024

Not Funded (Optional)

[Some fields expect you to list unfunded submissions]

Include:

  • Funding agency and mechanism
  • Your role (PI, Co-PI, Co-I)
  • Project title
  • Dates
  • Total amount (and amount to your lab if split)

7. Teaching Experience

TEACHING EXPERIENCE

Courses Taught

BIOL 301: Molecular Biology (Instructor of Record)
  University of Michigan, Fall 2022, Fall 2023
  Enrollment: 45 students
  Developed new course curriculum

BIOL 101: Introduction to Biology (Lab Instructor)
  Stanford University, 2015-2018
  
Guest Lectures

"Topic," Course Name, Professor's Name, University, Date

Include:

  • Course number and title
  • Your role (Instructor, TA, Guest Lecturer)
  • Institution and dates
  • Enrollment numbers
  • Course development or new preparations
  • Teaching evaluations summary (if strong)

8. Mentoring

MENTORING

Graduate Students
- Student Name (Ph.D. expected 2025), Dissertation: "Title"
- Student Name (Ph.D. 2023), Current position: Postdoc at MIT

Postdoctoral Fellows
- Name (2021-2023), Current position: Assistant Professor at X

Undergraduate Researchers
- Name (2022-2023), Thesis: "Title," Current: PhD program at Y
- Name (2021-2022), Thesis: "Title," Current: Industry position

9. Service

SERVICE

To the Profession
- Editorial Board Member, Journal Name, 2022-Present
- Grant Reviewer, NIH Study Section XYZ, 2023
- Conference Organizer, Conference Name, 2022

To the University
- Graduate Admissions Committee, 2022-Present
- Faculty Search Committee, 2023
- Curriculum Committee, 2022-2023

To the Department
- Seminar Coordinator, 2022-Present
- Undergraduate Advisor, 2022-Present

10. Professional Memberships

PROFESSIONAL MEMBERSHIPS

American Society for Cell Biology (ASCB), 2015-Present
Society for Neuroscience (SfN), 2018-Present

11. Honors & Awards

HONORS AND AWARDS

NSF CAREER Award, 2022
Best Paper Award, Conference Name, 2021
Outstanding Graduate Student Award, Stanford University, 2018
National Science Foundation Graduate Research Fellowship, 2015-2018
Phi Beta Kappa, 2013

Role-Specific Emphasis

Tenure-Track Faculty

Emphasize:

  1. Publications (especially recent, high-impact)
  2. Grants (especially independent funding)
  3. Research trajectory and vision
  4. Teaching experience
  5. Mentoring record

Postdoctoral Position

Emphasize:

  1. Publications (from PhD and postdoc)
  2. Research experience and skills
  3. Collaboration experience
  4. Future research potential
  5. Any funding/fellowships

Lecturer/Teaching Faculty

Emphasize:

  1. Teaching experience (courses, evaluations)
  2. Course development
  3. Pedagogical training
  4. Mentoring undergraduates
  5. Teaching awards

Research Scientist

Emphasize:

  1. Publications
  2. Technical skills
  3. Grant writing experience
  4. Collaboration record
  5. Relevant research experience

Discipline-Specific Conventions

Sciences (Biology, Chemistry, Physics)

  • Author order matters (first author, last author = senior)
  • Impact factors sometimes included
  • Numbered publication lists common
  • Conference presentations less weighted than publications

Humanities (History, Literature, Philosophy)

  • Single-author publications highly valued
  • Book publications crucial
  • Conference presentations important
  • Public scholarship valued

Social Sciences

  • Both solo and collaborative work valued
  • Mix of journal articles and books
  • Funded research important
  • Policy impact valued

CV Length Guidelines

Career StageExpected Length
Graduate Student2-4 pages
Postdoc3-6 pages
Early Career Faculty5-10 pages
Mid-Career Faculty10-20 pages
Senior Faculty15-30+ pages

Rule: Your CV grows throughout your career. Don't pad, but don't artificially constrain length.

Output Format

When creating an academic CV:

markdown
# ACADEMIC CV STRUCTURE FOR [NAME]

## Recommended Section Order
[Based on position type and field]

1. [Section]
2. [Section]
...

## Section Content

### Education
[Formatted education section]

### Publications
[Formatted with appropriate style for field]

### [Other Sections]
[Formatted content]

---

## Formatting Notes
- [Field-specific conventions to follow]
- [Style guide recommendations]

## Things to Add/Update
- [ ] [Missing item]
- [ ] [Item needing update]

Academic CV Checklist

  • ✅ Contact information complete (including ORCID if applicable)
  • ✅ Education includes all degrees, advisors, dissertations
  • ✅ Publications properly formatted with your name highlighted
  • ✅ All grants listed with amounts and your role
  • ✅ Teaching experience comprehensive
  • ✅ Service documented
  • ✅ Consistent formatting throughout
  • ✅ Reverse chronological order (usually)
  • ✅ No unexplained gaps
  • ✅ Updated within last 6 months

Frequently asked questions

What does the Academic Cv Builder AI skill do?

Format CVs for academic positions with publications, grants, and teaching

Why use Academic Cv Builder on TypingMind?

Because you install it once and use it with any model. Academic Cv 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 Academic Cv Builder in TypingMind?

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

Which AI models can use Academic Cv 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 Academic Cv Builder?

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

Is the Academic Cv 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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