CV Skill

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

Use this skill when

• The user wants a professional resume or CV in .docx
• 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

Keep facts intact. Do not invent results or responsibilities.

3. 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

4. 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

Layout rules

• Single column
• Black and white only
• Section headers with strong hierarchy
• Larger spacing than default Word exports
• Short, factual bullets
• Avoid self-evaluation phrases such as “责任心强” or “结果导向”
• Prefer evidence and scope over adjectives

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
• references/input-schema.md: input contract
• references/rewriting-guide.md: track-specific rewriting guidance
• assets/example_profile.json: safe sample input
• agents/openai.yaml: UI metadata