CV

What This Skill Does

The CV skill is an advanced career documentation engine designed to transform raw professional experience into high-conversion, ATS-optimized assets. By applying rigorous structural frameworks, this skill ensures your professional history passes automated screening software and captures recruiter attention. It enforces data-driven bullet points using the CAR (Context-Action-Result) formula, helping you move from task-based descriptions to achievement-oriented narratives. Whether you are building a concise resume for a tech giant or a comprehensive CV for an international research role, this skill provides the strategic guidance to highlight your unique value proposition through metrics, industry-aligned keywords, and professional formatting.

Installation

To integrate this skill into your OpenClaw environment, execute the following command in your terminal: clawhub install openclaw/skills/skills/ivangdavila/cv

Use Cases

• Tech Recruitment: Tailoring resumes for software engineering, product management, or data science roles where technical skill highlighting is paramount.
• Academic & Research: Drafting exhaustive CVs for fellowships, grants, or university tenure-track positions, following international academic standards.
• Career Transitioning: Re-framing previous experience to align with new industry requirements by focusing on transferable skills and quantified impact.
• Performance Review Preparation: Using the structured bullet point generation to document yearly achievements for promotion cycles.

Example Prompts

1. "I am a Backend Developer with 5 years of experience. Help me draft a professional summary for a Senior role at a fast-growing fintech company, focusing on Python and AWS."
2. "Review these three work experience bullets and rewrite them using the CAR formula, ensuring I include specific metrics about the revenue I generated."
3. "I am applying for a research role in the EU. Can you format my education and research project list according to standard CV requirements?"

Tips & Limitations

• Quantification is Key: The AI relies on the numbers you provide. If you have vague data, focus on estimating scope, scale, or time saved to make bullets more impactful.
• ATS Best Practices: Avoid using tables, graphics, or columns in your final document. Stick to clean, standard text formatting to ensure 100% compatibility with ATS parsers.
• Privacy: Always strip sensitive personal data like full addresses or birth dates from the drafts provided by this skill.
• Scope: The skill is a document strategist. You should still perform a final human review to ensure tone consistency and factual accuracy regarding your career history.