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academic-cv-generator

academic-cv-generator

【文档与办公】Generate structured academic CVs from free-form Chinese/English text and export to Word (.docx). Use this skill when you are asked to organize, generate, or optimize an academic CV (e.g., publications/projects/awards) into a consistent, formatted document with uniform-colored section headers and optional bilingual output.

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技能说明

GitHub

name: academic-cv-generator description: Generate structured academic CVs from free-form Chinese/English text and export to Word (.docx). Use this skill when you are asked to organize, generate, or optimize an academic CV (e.g., publications/projects/awards) into a consistent, formatted document with uniform-colored section headers and optional bilingual output. license: MIT author: AIPOCH

Source: https://github.com/aipoch/medical-research-skills

When to Use

  • You receive a messy, free-form CV draft (Chinese or English) and need it reorganized into a standard academic structure.
  • You are asked to compile and format Publications from raw citation strings without changing their original citation format.
  • You need to extract and normalize Education and Project Experience entries, then sort them by degree level or time.
  • You must generate a Word (.docx) academic CV that matches a predefined visual style (uniform header color, bold headers, bullet lists).
  • The user requests a polished CV output file with a fixed naming convention: Name-Academic-CV.docx.

Key Features

  • Classifies free-form input into: Personal Information, Educational Background, Project Experience, Publications, Awards (optional), Skills.
  • Normalizes content into a required intermediate Markdown outline before rendering.
  • Omits the Awards section entirely when no awards are provided.
  • Infers a minimal Skills section from project descriptions when explicit skills are missing.
  • Renders a Word document aligned to the reference layout output/ZhangWei-Academic-CV.docx.
  • Applies consistent styling rules: single-line section titles, larger than body text, bold, and one uniform header color.

Dependencies

  • Python 3.x
  • python-docx (install via pip install python-docx)

Example Usage

1) Prepare input (free-form text)

Create or use the provided example input file:

  • sample_input_standard.txt

2) Generate the Word CV

python -m pip install python-docx
python scripts/render_cv.py --input sample_input_standard.txt --output output

3) Optional flags

python scripts/render_cv.py \
  --input sample_input_standard.txt \
  --output output \
  --lang en \
  --header-color random

Supported options:

  • --lang zh|en
  • --header-color purple|cyan|green|red|random

4) Expected output

  • Output file: Name-Academic-CV.docx (saved under the --output directory)
  • Reference sample: sample_output.docx

Implementation Details

1) End-to-end workflow

  1. Parse the input and classify content into:
    • Personal Information
    • Educational Background
    • Project Experience
    • Publications
    • Skills
    • Awards (optional)
  2. Convert the classified result into the required Markdown layout (mandatory intermediate step).
  3. If Awards is empty, omit the section from both Markdown and DOCX.
  4. If Skills is empty, infer skills from project experience and output a minimal skills list.
  5. Render the CV into Word using the same visual structure as output/ZhangWei-Academic-CV.docx.
  6. Ensure section titles are single-line, bold, larger than body text, and share one uniform color.
  7. Save as Name-Academic-CV.docx.

2) Classification rules

  • Personal Information: name, title, organization, email, phone.
  • Educational Background: degree (PhD/Master/Bachelor), major, school, year; sort from highest to lowest degree.
  • Project Experience: project name + time range + responsibilities/description; sort by time (most recent first).
  • Publications: keep original citation strings exactly as provided (no reformatting).
  • Skills: use explicit skills if present; otherwise infer from project content.

3) Required Markdown output format (intermediate representation)

The classified content must be normalized into the following Markdown outline:

Personal Information
Name|Title|Organization|Email|Phone

Educational Background
Degree, Major, School, Year
Degree, Major, School, Year

Project Experience
Project Name (Project Period): Key responsibilities or work content
Project Name (Project Period): Key responsibilities or work content

Publications
Original citation entries (keep input format)
Original citation entries (keep input format)

Awards
Year, Award
Year, Award

Skills
Programming Languages: ...
Technical Fields: ...
Tools & Technologies: ...

Rules:

  • If Awards is empty, omit the entire section.
  • If Skills is empty, infer and output a minimal skills list (e.g., Technical Fields: Blockchain / Machine Learning / Systems Development).

4) Word rendering rules

  • Do not print the “Personal Information” section title in the DOCX.
  • Print the name as the first line in bold.
  • Print the contact line as: Title | Organization | Email | Phone.
  • Section titles (Educational Background / Project Experience / Publications / Awards / Skills):
    • bold
    • single-line
    • larger than body text
    • all use one uniform color chosen from: purple, cyan, green, red (or random)
  • All items under each section are rendered as bullet points.

5) Output rules

  • Output format must be Word (.docx).
  • Output filename must be: Name-Academic-CV.docx.
  • Treat “Publications / Published Literature / Published Papers” as standalone publication sections.
  • The final layout should match the reference: output/ZhangWei-Academic-CV.docx.
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