CV Skill

Create professional Harvard-style resumes, CVs, and matching cover letters from user-provided candidate descriptions, structured data, or existing resumes. Use when the user wants a polished one-page or role-targeted resume, needs multiple resume versions for different job directions, wants to convert raw candidate notes into structured bullets, or needs DOCX/PDF outputs in any language from structured input data.

Create role-targeted, black-and-white, Harvard-style resumes and matching cover letters from candidate descriptions, structured input, or existing resumes.

Use this skill when

• The user wants a professional resume or CV in .docx
• The user wants a concise cover letter matched to a role and employer
• The user gives a rough candidate description and wants the agent to draft the resume from scratch
• The user wants one candidate rewritten into multiple job-targeted versions
• The user provides a PDF, notes, or rough bullets and wants a polished resume
• The user wants tighter, more professional bullets without fluff
• The user wants a Harvard-style layout with larger spacing and clean hierarchy
• The user needs output in a language other than Chinese or English

Workflow

1. Gather candidate data

Use the structured schema in references/input-schema.md.

If you are starting from an existing resume, extract:

• contact info
• summary / positioning
• education
• work experience
• projects
• campus or extracurricular items
• tools, languages, certificates
• target job directions

2. Define track-specific positioning

For each job direction, rewrite:

• resume title
• 2-3 sentence summary
• bullet emphasis within experience
• skills ordering
• optional cover letter angle: opening fit, 1-2 proof examples, closing

Keep facts intact. Do not invent results or responsibilities.

3. Apply Harvard-style resume rules

Use references/harvard-hes-2024-notes.md as the quality checklist:

• tailor content to the target role or industry
• keep format consistent and easy to skim
• use reverse chronological order within sections unless relevance requires a different order
• start bullets with active verbs and include scope, skills, and impact
• quantify results when the source material supports it
• remove personal pronouns, photos, age, marital status, references, slang, and low-signal filler
• check contact email and phone are present before delivery

4. Generate the resume

Run:

python3 scripts/generate_resume.py --input assets/example_profile.json --track all --output-dir /tmp/cv-output

Generate a specific track:

python3 scripts/generate_resume.py --input candidate.json --track operations --output-dir /tmp/cv-output

Try PDF export when LibreOffice is installed:

python3 scripts/generate_resume.py --input candidate.json --track all --output-dir /tmp/cv-output --pdf

If python-docx is missing, install dependencies first:

python3 -m pip install -r requirements.txt

5. Draft a matching cover letter when requested

Use the same font family and general spacing as the resume.

Cover letter structure:

• recipient block when known; otherwise use a clean generic greeting
• opening paragraph naming the role, employer, and fit
• middle paragraph(s) connecting 1-2 specific examples to the role requirements
• closing paragraph restating interest and interview availability

Keep it concise, factual, and no longer than one page. Do not restate the whole resume.

6. Validate before delivery

Check that:

• no hardcoded personal info from unrelated candidates remains
• dates and headings are consistent
• bullets are role-targeted rather than generic
• low-signal items are removed or pushed down
• generated filenames are generic and safe
• resume and cover letter use matching typography
• exported PDF preserves layout and does not break bullets or spacing
• required contact info is present: email and phone

Layout rules

• Single column
• Black and white only
• Letter page size by default; A4 supported with style.page_size
• Section headers with strong hierarchy
• Balanced white space; avoid cramped default Word spacing
• Short, factual bullets
• Avoid self-evaluation phrases such as “责任心强” or “结果导向”
• Prefer evidence and scope over adjectives
• Contact line may include city, phone, email, LinkedIn, portfolio, or other relevant links
• Use section order by relevance; education may move down when experience is stronger

Safety rules

• Do not hardcode real candidate data into scripts
• Do not store secrets, API keys, tokens, or .env files in the skill folder
• Keep outputs outside the skill folder unless the user explicitly wants examples saved there
• Use assets/example_profile.json only as a redacted example

Files

• scripts/generate_resume.py: generic generator
• requirements.txt: Python dependencies
• references/input-schema.md: input contract
• references/rewriting-guide.md: track-specific rewriting guidance
• references/harvard-hes-2024-notes.md: Harvard Extension School resume and cover letter checklist
• assets/example_profile.json: safe sample input
• agents/openai.yaml: UI metadata