--- 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](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 ```bash python -m pip install python-docx python scripts/render_cv.py --input sample_input_standard.txt --output output ``` ### 3) Optional flags ```bash 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: ```text 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`. --- Source attribution: aipoch Original project: https://github.com/aipoch/medical-research-skills License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice MIT License Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Mega AI Hub resource metadata Creator / publisher: aipoch Original project: https://github.com/aipoch/medical-research-skills Attribution basis: Upstream repository explicitly recorded in package mirror path Fields of work: Education & Research Roles: Academic Writer, Researcher, Tutor / Instructor Specialties: Word Documents Tools: Microsoft Word Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: a3187c5190dcbcb1800823e39fc8e66c1560a1de201eb9ea5894ed9c4a38c9a2