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BytesAgain β€Ί Skills β€Ί CV Skill
πŸ¦€ ClawHub

CV Skill

by @jasoncodespace

Create professional Harvard-style resumes, CVs, and matching cover letters from user-provided candidate descriptions, structured data, or existing resumes. U...

Versionv1.1.0
Downloads871
#writing#legal#hr
TERMINAL
clawhub install cv-skill

πŸ“– About This Skill

name: cv-skill description: Create professional Harvard-style resumes and CVs 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. version: 1.0.0

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 β€œθ΄£δ»»εΏƒεΌΊβ€ or β€œη»“ζžœε―Όε‘β€
  • 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