cv-tailor

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Optimize resumes by matching keywords to the job description, rewriting experience with the quantified STAR method, and checking ATS compatibility. Triggered when users ask for resume help, review, or polishing, mention JD matching, STAR method, ATS, or want to tailor their resume for a specific role.

AI & Automation 4,617 stars 463 forks Updated today MIT

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Skill Content

# CV Tailor **Three pillars of resume optimization**: Analyze keyword alignment against the target JD, rewrite experience bullets using the STAR method with quantified results, and run an ATS compatibility check — producing a highly targeted, high-pass-rate optimized resume. ## Quick Start The user provides their resume (content or file) and the target JD. The agent then automatically completes the optimization following the workflow below: ``` User: Help me optimize my resume — I'm applying for this role [attaches JD + resume] Agent: [Follows the SOP workflow and outputs optimization recommendations plus a rewritten resume] ``` ## SOP Workflow ### Phase 1: Input Collection & Initial Analysis **Goal**: Gather the user's resume and target JD; establish an optimization baseline. **Steps**: 1. **Collect materials**: - Obtain the user's resume content (pasted text or file path) - Obtain the target JD (pasted text or role description) - If no JD is provided, ask about the target role direction (industry + position + level) 2. **Resume baseline parsing**: - Identify resume sections (education, work experience, projects, skills, etc.) - Count resume length, number of experience entries, and time span - Note the current resume format type (reverse-chronological / functional / hybrid) 3. **JD core element extraction**: - Job title and level - Core responsibilities (Top 5) - Hard requirements (must-haves) - Nice-to-haves - Key skill terms and...

Details

Author
zebbern
Repository
zebbern/claude-code-guide
Created
1 years ago
Last Updated
today
Language
Python
License
MIT

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