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>
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skills/resume-architect.md
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skills/resume-architect.md
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# Resume Architect
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**Generate ATS-optimized, role-targeted resumes from your career data.**
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One resume does not fit all. This skill builds a tailored resume for every application.
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## Philosophy
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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.
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Resume Architect treats your resume like a **conversion funnel**:
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1. **ATS Parse** — Machine-readable format that scanners love
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2. **Keyword Match** — Language pulled directly from the job post
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3. **Impact First** — Quantified achievements, not responsibilities
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4. **Scan Hook** — Top 6 seconds tell the whole story
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## Input Required
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Before running, gather:
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- Your current resume or career notes (any format)
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- The target job posting (URL or pasted text)
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- Your LinkedIn profile (optional but recommended)
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- Any portfolio/GitHub/project links
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## Workflow
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### Phase 1: Job Post Reverse Engineering
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```
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Extract from job posting:
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- Required skills (hard skills with versions)
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- Preferred skills (bonus points)
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- Required experience (years, domains)
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- Key responsibilities (action verbs used)
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- Company language/style (formal, casual, startup)
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- Implicit needs (read between lines)
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```
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**Output:** Job fingerprint — a structured list of keywords, competencies, and signals.
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### Phase 2: Career Data Extraction
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From your raw materials, extract:
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```
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For each role:
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- Company, title, dates
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- Technologies used (with versions)
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- Quantified achievements (X% improvement, $Y revenue, Z users)
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- Scope (team size, budget, user base)
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- Promotions or expanded responsibilities
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```
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### Phase 3: Resume Assembly
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**Structure (ATS-friendly, single-column):**
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```
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[Full Name]
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[City, State] | [Phone] | [Email] | [LinkedIn] | [GitHub/Portfolio]
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PROFESSIONAL SUMMARY
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2-3 lines. Mirror their language. Lead with years of experience in [their domain].
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SKILLS
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Grouped by category. Keywords from job post first.
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Languages: [their stack first, then yours]
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Frameworks: [matched to their needs]
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Tools: [relevant only]
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Platforms: [cloud, infra matching their stack]
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EXPERIENCE
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[Most Recent Company] | [Title] | [Dates]
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- Achievement with metric matching their stated need
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- Achievement with metric matching their stated need
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- Achievement showing scope they care about
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(3-5 bullets, never responsibilities without outcomes)
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[Previous Company] | [Title] | [Dates]
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- Same format, prioritize relevance over chronology
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EDUCATION
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[Degree] | [School] | [Year]
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- Only include GPA if 3.7+ and recent grad
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- Relevant coursework ONLY if career changer or junior
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CERTIFICATIONS
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- Only include if relevant to THIS role
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```
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### Phase 4: Keyword Optimization
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```
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Compare resume keywords vs job post keywords:
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Job requires: Resume has:
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React 18 React (update to "React 18")
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AWS ✅
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CI/CD GitHub Actions (add "CI/CD")
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Microservices ✅
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PostgreSQL MySQL (add PostgreSQL if applicable)
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Fill gaps honestly. Never fabricate — use "familiar with" or "exposure to" for weaker skills.
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```
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### Phase 5: ATS Compliance Check
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Verify:
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- [ ] Single-column layout
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- [ ] Standard section headers (Experience, Education, Skills)
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- [ ] No tables, headers/footers, or text boxes
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- [ ] Standard fonts (Arial, Calibri, Georgia)
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- [ ] No images or graphics
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- [ ] Date format consistent (MMM YYYY – MMM YYYY)
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- [ ] File saved as .docx or .pdf (check job post preference)
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- [ ] Under 2 pages (under 1 page for < 5 years experience)
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## Templates
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### Entry-Level (0-2 years)
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```
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[Name] | [Location] | [Contact]
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PROFESSIONAL SUMMARY
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Motivated [Role] with [X] years of experience in [domain].
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Built [project] serving [metric]. Strong foundation in [their stack].
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TECHNICAL SKILLS
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Languages: [job post languages]
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Frameworks: [job post frameworks]
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Tools: [matching tools]
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PROJECTS
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[Project Name] | [Tech Stack]
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- Built [what] achieving [metric]
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- Implemented [feature] using [tech]
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- [GitHub link]
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EXPERIENCE
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[Company] | [Title] | [Dates]
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- Achievement with number
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- Achievement with number
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EDUCATION
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[Degree] | [School] | [Year]
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```
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### Mid-Level (3-7 years)
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```
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[Name] | [Location] | [Contact]
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PROFESSIONAL SUMMARY
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[Role] with [X] years building [domain] systems.
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Led [scope] delivering [impact]. Expert in [their core stack].
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SKILLS
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[Grouped, job-post keywords first]
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EXPERIENCE
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[Company] | [Title] | [Dates]
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- Impact metric matching their need
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- Technical depth showing seniority
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- Leadership/collaboration signal
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- Scope of responsibility
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[Previous Company] | [Title] | [Dates]
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- Relevant achievements
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EDUCATION
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[Degree] | [School]
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```
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### Senior/Staff (8+ years)
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```
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[Name] | [Location] | [Contact]
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PROFESSIONAL SUMMARY
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Senior [Role] with [X]+ years driving [domain] strategy.
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Scaled [system] to [metric]. Built and led teams of [size].
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Deep expertise in [their domain].
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SKILLS
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[Strategic + technical keywords from job post]
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EXPERIENCE
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[Company] | [Senior Title] | [Dates]
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- Strategic impact (org-level metric)
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- Technical leadership (architecture decisions)
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- Team building (mentoring, hiring, growing)
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- Cross-functional collaboration
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[Previous roles — 2-3 bullets each, decreasing detail]
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NOTABLE ACHIEVEMENTS (optional section for staff+)
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- [Portfolio of impact across roles]
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EDUCATION
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[Degree] | [School]
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```
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## Career Changer Mode
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For switching industries:
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1. Lead with **transferable skills** in summary
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2. Create a **Relevant Projects** section above experience
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3. Reframe past roles using target industry language
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4. Include certifications/coursework showing commitment
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5. Objective statement explaining the pivot
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## Output Formats
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- **Markdown** — For review and editing
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- **LaTeX** — For academic/scientific roles
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- **PDF** — Final output via nano-pdf skill
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- **JSON** — Structured data for programmatic use
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## Integration with Other Skills
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- **nano-pdf**: Generate final formatted PDF
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- **jobhunter-master**: Receives job post data for keyword matching
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- **cover-letter-craft**: Uses same job fingerprint for consistency
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## Files
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- `memory/resume-base.md` — Your master career data
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- `memory/resumes/[company]-[role].md` — Per-application versions
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