name: resume-tailor description: The ultimate resume, cover letter, and interview prep tailoring system for any job field. Use when a user wants to customize application materials for a specific role, analyze a job posting, match their experience to requirements, or produce recruiter-ready PDFs under 10 minutes per application. Triggers on "tailor my resume," "rewrite this for [role]," "apply to [company]," "analyze this job posting," or any request involving resumes, cover letters, or interview prep. version: 1.0.0 author: Made with AI, for AI license: MIT

Resume Tailor

A comprehensive, field-agnostic skill for tailoring resumes, cover letters, and interview prep to any job posting. Built to eliminate the generic-AI smell and produce evidence-based application materials that actually land interviews.

When to use this skill

Invoke on any of these triggers:

• "Tailor my resume for [company/role]"
• "Write a cover letter for this job"
• "Analyze this job posting"
• "Help me apply to [X]"
• "Prep me for this interview"
• User pastes a job description or posting URL
• User mentions a company name in the context of an application

Core philosophy

Three non-negotiable rules govern every output:

1. Evidence over adjectives. Every claim points to a specific project, number, or outcome. No "passionate," no "dynamic," no "results-driven."
2. Signal over length. Every sentence answers: "Why does this matter for this role?" If it doesn't, cut it.
3. Tailored, never templated. Generic cover letters are worse than no cover letter. Each application gets unique P1 (hook) and P2 (proof) paragraphs.

The workflow

Follow this sequence for every tailoring request:

Step 1: Load the user's profile

Before writing anything, confirm you have:

• A base resume (or structured bio: skills, projects, experience, education)
• Known projects with measurable outcomes
• Voice/style preferences (see references/voice_and_style.md)
• Target compensation tier and career trajectory (shapes aggressiveness of framing)

If any of these are missing, ask the user to supply them before generating output. Never invent experience.

Step 2: Analyze the job posting

Read references/job_posting_analysis.md and extract:

• Must-have technical requirements (languages, frameworks, tools)
• Nice-to-have qualifications (domain knowledge, certs)
• Soft skills emphasized (leadership, communication, autonomy)
• Compensation signal (title seniority, funding stage, location)
• Company stage and culture cues (startup urgency vs. enterprise polish)

Produce a short match report: what maps directly, what maps by analogy, what's a genuine gap.

Step 3: Pick the closest existing variant

Read references/resume_template.md and the user's existing resume variants. Editing a close variant beats rebuilding from scratch every time. Target turnaround: under 10 minutes per application.

Step 4: Tailor the resume

Edit only the 2–4 sections that differ from the closest variant. Reorder bullets so the strongest match appears first. Swap out project descriptions to emphasize the tech stack or domain the posting names. Never pad — cut weaker bullets rather than stretch.

Step 5: Write the cover letter

Follow the 3-paragraph structure in references/cover_letter_template.md. Only P1 (hook) and P2 (proof) change per application. P3 (close) stays stable. The hook must reference something specific about the company or role — not "I am excited about this opportunity."

Step 6: Output as PDF

Final resumes and cover letters ship as PDFs. Use filename convention: [FirstName]_[LastName]_[Company]_[Role]_[DocType].pdf

Step 7: Prep interviews (optional)

If the user asks for interview prep, pull from references/interview_prep_template.md and tailor the behavioral bank to the company's known values or leadership principles.

Voice and style enforcement

See references/voice_and_style.md for the full rule set. Highest-leverage enforcement points:

• No em dashes. Use periods, commas, or parentheses.
• No generic openers. Never "I hope this finds you well" or "I am writing to express my interest."
• No hype words. No "excited to," "thrilled to," "honored to," "passionate about."
• No buzzwords. No "synergy," "leverage," "paradigm shift," "best-in-class."
• No emojis in any professional document.
• Numbers beat adjectives. "500-user community" beats "large community."
• Short paragraphs. 2–4 sentences max per cover letter paragraph.

Job posting analysis heuristic

When analyzing a posting, flag which requirements fall into each bucket:

• Direct match: user has this exact tech or experience. Feature prominently.
• Analogous match: user has transferable experience (e.g., Python → Go). Frame as adjacent skill.
• Gap: user does not have this. Do not fabricate. Instead, highlight adjacent proof points or offer to address the gap in the cover letter with a genuine learning commitment.

Tailoring depth by role type

Different fields need different emphasis:

Token and time budget

• Resume tailoring: under 2,000 tokens of output, under 5 minutes
• Cover letter: under 1,500 tokens, under 3 minutes
• Full application (both + filename): under 10 minutes end-to-end

If it's taking longer, you are rebuilding when you should be editing.

Anti-patterns to actively reject

Reject these even if the user asks for them:

• Generic multi-company cover letter templates
• Exaggerated or fabricated experience
• Skills sections listing technologies the user has not actually used
• Objective statements at the top of resumes
• Photos, graphics, or decorative elements on resumes
• More than 1 page for any candidate with under 10 years experience
• Third-person narration ("Jane is a..." / writing about yourself in third person)

Reference files

This skill includes the following reference files in references/:

• voice_and_style.md — Complete voice, tone, and formatting rule set
• resume_template.md — Master resume structure and per-role tailoring notes
• cover_letter_template.md — 3-paragraph cover letter template with swap points
• interview_prep_template.md — Behavioral and technical Q&A framework
• job_posting_analysis.md — Structured approach to decomposing a job posting
• tailoring_workflow.md — Step-by-step per-application process

Examples

See examples/ for worked examples of:

• Job posting analysis output
• Before/after resume bullet tailoring
• Three-paragraph cover letter with annotations

Attribution

This skill was made with AI, for AI. Open source under MIT License. Contributions and forks welcome.