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Job-Hunter-Linkedin-Skill-H…/skills/resume-architect.md
admin 2abc5dbf7e Expand to Career Arsenal: 8 AI-powered career skills collection
- Restructured repo from single skill to skills collection
- Added 7 new skills: Resume Architect, Cover Letter Craft,
  Interview Commander, Salary Negotiator, Career GPS,
  LinkedIn Optimizer, Job Switch Advisor
- Rewrote README as collection hub with pipeline diagram,
  integration map, and usage-by-stage guides

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-04-21 12:08:32 +00:00

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Resume Architect

Generate ATS-optimized, role-targeted resumes from your career data. One resume does not fit all. This skill builds a tailored resume for every application.

Philosophy

Your resume has one job: get past the ATS scanner and into a human's hands. Most resumes fail at step one because they're generic, keyword-poor, and formatted for aesthetics over parseability.

Resume Architect treats your resume like a conversion funnel:

  1. ATS Parse — Machine-readable format that scanners love
  2. Keyword Match — Language pulled directly from the job post
  3. Impact First — Quantified achievements, not responsibilities
  4. Scan Hook — Top 6 seconds tell the whole story

Input Required

Before running, gather:

  • Your current resume or career notes (any format)
  • The target job posting (URL or pasted text)
  • Your LinkedIn profile (optional but recommended)
  • Any portfolio/GitHub/project links

Workflow

Phase 1: Job Post Reverse Engineering

Extract from job posting:
- Required skills (hard skills with versions)
- Preferred skills (bonus points)
- Required experience (years, domains)
- Key responsibilities (action verbs used)
- Company language/style (formal, casual, startup)
- Implicit needs (read between lines)

Output: Job fingerprint — a structured list of keywords, competencies, and signals.

Phase 2: Career Data Extraction

From your raw materials, extract:

For each role:
- Company, title, dates
- Technologies used (with versions)
- Quantified achievements (X% improvement, $Y revenue, Z users)
- Scope (team size, budget, user base)
- Promotions or expanded responsibilities

Phase 3: Resume Assembly

Structure (ATS-friendly, single-column):

[Full Name]
[City, State] | [Phone] | [Email] | [LinkedIn] | [GitHub/Portfolio]

PROFESSIONAL SUMMARY
2-3 lines. Mirror their language. Lead with years of experience in [their domain].

SKILLS
Grouped by category. Keywords from job post first.

  Languages:     [their stack first, then yours]
  Frameworks:    [matched to their needs]
  Tools:         [relevant only]
  Platforms:     [cloud, infra matching their stack]

EXPERIENCE
[Most Recent Company] | [Title] | [Dates]
  - Achievement with metric matching their stated need
  - Achievement with metric matching their stated need
  - Achievement showing scope they care about
  (3-5 bullets, never responsibilities without outcomes)

[Previous Company] | [Title] | [Dates]
  - Same format, prioritize relevance over chronology

EDUCATION
[Degree] | [School] | [Year]
  - Only include GPA if 3.7+ and recent grad
  - Relevant coursework ONLY if career changer or junior

CERTIFICATIONS
  - Only include if relevant to THIS role

Phase 4: Keyword Optimization

Compare resume keywords vs job post keywords:

Job requires:        Resume has:
React 18             React (update to "React 18")
AWS                  ✅
CI/CD                GitHub Actions (add "CI/CD")
Microservices        ✅
PostgreSQL           MySQL (add PostgreSQL if applicable)

Fill gaps honestly. Never fabricate — use "familiar with" or "exposure to" for weaker skills.

Phase 5: ATS Compliance Check

Verify:

  • Single-column layout
  • Standard section headers (Experience, Education, Skills)
  • No tables, headers/footers, or text boxes
  • Standard fonts (Arial, Calibri, Georgia)
  • No images or graphics
  • Date format consistent (MMM YYYY MMM YYYY)
  • File saved as .docx or .pdf (check job post preference)
  • Under 2 pages (under 1 page for < 5 years experience)

Templates

Entry-Level (0-2 years)

[Name] | [Location] | [Contact]

PROFESSIONAL SUMMARY
Motivated [Role] with [X] years of experience in [domain].
Built [project] serving [metric]. Strong foundation in [their stack].

TECHNICAL SKILLS
  Languages: [job post languages]
  Frameworks: [job post frameworks]
  Tools: [matching tools]

PROJECTS
[Project Name] | [Tech Stack]
  - Built [what] achieving [metric]
  - Implemented [feature] using [tech]
  - [GitHub link]

EXPERIENCE
[Company] | [Title] | [Dates]
  - Achievement with number
  - Achievement with number

EDUCATION
[Degree] | [School] | [Year]

Mid-Level (3-7 years)

[Name] | [Location] | [Contact]

PROFESSIONAL SUMMARY
[Role] with [X] years building [domain] systems.
Led [scope] delivering [impact]. Expert in [their core stack].

SKILLS
  [Grouped, job-post keywords first]

EXPERIENCE
[Company] | [Title] | [Dates]
  - Impact metric matching their need
  - Technical depth showing seniority
  - Leadership/collaboration signal
  - Scope of responsibility

[Previous Company] | [Title] | [Dates]
  - Relevant achievements

EDUCATION
[Degree] | [School]

Senior/Staff (8+ years)

[Name] | [Location] | [Contact]

PROFESSIONAL SUMMARY
Senior [Role] with [X]+ years driving [domain] strategy.
Scaled [system] to [metric]. Built and led teams of [size].
Deep expertise in [their domain].

SKILLS
  [Strategic + technical keywords from job post]

EXPERIENCE
[Company] | [Senior Title] | [Dates]
  - Strategic impact (org-level metric)
  - Technical leadership (architecture decisions)
  - Team building (mentoring, hiring, growing)
  - Cross-functional collaboration

[Previous roles — 2-3 bullets each, decreasing detail]

NOTABLE ACHIEVEMENTS (optional section for staff+)
  - [Portfolio of impact across roles]

EDUCATION
[Degree] | [School]

Career Changer Mode

For switching industries:

  1. Lead with transferable skills in summary
  2. Create a Relevant Projects section above experience
  3. Reframe past roles using target industry language
  4. Include certifications/coursework showing commitment
  5. Objective statement explaining the pivot

Output Formats

  • Markdown — For review and editing
  • LaTeX — For academic/scientific roles
  • PDF — Final output via nano-pdf skill
  • JSON — Structured data for programmatic use

Integration with Other Skills

  • nano-pdf: Generate final formatted PDF
  • jobhunter-master: Receives job post data for keyword matching
  • cover-letter-craft: Uses same job fingerprint for consistency

Files

  • memory/resume-base.md — Your master career data
  • memory/resumes/[company]-[role].md — Per-application versions