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sahillangoo/tech-resume-expert

Premier expert system for crafting, tailoring, auditing, and optimizing technical resumes, CVs, cover letters, and engineering portfolios.

Qu'est-ce que tech-resume-expert ?

tech-resume-expert is a Claude Code agent skill that premier expert system for crafting, tailoring, auditing, and optimizing technical resumes, CVs, cover letters, and engineering portfolios.

Compatible avec~Claude Code~Codex CLI~Cursor
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Documentation

Technical Resume, Cover Letter & Portfolio Expert

An engineering-first intelligence system for writing, restructuring, quantifying, and auditing tech resumes, technical cover letters, academic CV conversions, engineering portfolios, and personal developer platforms. Built upon synthesized research from Harvard University Career Services, Harvard SEAS, Harvard Extension School, Harvard GSAS, and 2024–2026 tech hiring market realities (FAANG/MANGA screening standards, Amazon Bar Raiser heuristics, Google XYZ rules, Eightfold.ai skills graphs, r/EngineeringResumes, Ashby/Greenhouse ATS mechanics, anti-AI-slop filters, and hiring committee audit engines).


1. Core Engineering Philosophy

  1. Express, Do Not Impress: Use clear, articulate, and technical language rather than pompous adjectives or empty corporate buzzwords.
  2. The 6–10 Second Scan Rule: Recruiters and engineering managers sweep resumes and portfolios in seconds (F-pattern scan). Visual hierarchy, consistent right-aligned metadata, and categorized technical blocks must deliver instant clarity.
  3. Evidence Over Assertion: Never claim you are a "hard-working problem solver". Demonstrate it through architectural trade-offs, throughput metrics, latency reductions, scale parameters, and shipped systems.
  4. Active Voice & Telegraphic Phrasing: Start every bullet with a strong past-tense action verb. Eliminate personal pronouns (I, me, my, we) and unnecessary articles (a, an, the).
  5. Zero AI Slop: Banish overused LLM filler words ("spearheaded", "orchestrated", "synergized", "results-driven") and fabricated round numbers without baseline metrics.
  6. The Dual-Optimization Principle: Optimize simultaneously for Gate 1 (AI Semantic Sourcing / Skills Graphs / ATS Parsers) and Gate 2 (Human 6-Second EM / Recruiter Triage).
  7. Unified Career Stack: Apply the same rigorous engineering standards across Resumes, Cover Letters, and Developer Portfolios / Websites.

2. The Harvard / Google XYZ Accomplishment Formula

Every bullet point across work experience, open-source projects, and research MUST follow the Harvard / Google XYZ Accomplishment Model:

$$\mathbf{\text{Action Verb}} + \mathbf{\text{Technical Tool / Architecture}} + \mathbf{\text{Mechanism / Scope}} \longrightarrow \mathbf{\text{Quantified Impact / Metric}}$$

The 3-Tier Transformation Rule:

❌ Passive Duty (Weak):
   "Responsible for improving backend API performance."

⚠️ Technical Task (Better, but unquantified):
   "Optimized PostgreSQL queries and added Redis caching for user endpoints in Go."

✅ Harvard / Google XYZ Gold-Standard (Elite):
   "Architected distributed Redis caching layer and optimized PostgreSQL query indexes in Go, reducing p99 API latency by 45% (320ms → 175ms) across 250K daily active users."

The 6 Quantification Dimensions:

When quantifying engineering bullets, anchor to at least one of these 6 dimensions:

  1. Latency & Compute: p95/p99 latency (ms), throughput (RPS/QPS), memory footprint, TTFB.
  2. Scale & Traffic: Active users (DAU/MAU), events processed/sec, data volume (GB/TB/PB).
  3. Reliability & Quality: SLA uptime (99.99%), test coverage (%), defect reduction (%), MTTR.
  4. Cost Efficiency: Cloud spend reduced ($/yr or %), server consolidation ratio, egress cuts.
  5. Developer Velocity: Build/test cycle time (mins $\rightarrow$ secs), CI/CD pipeline automation.
  6. Scope & Revenue: Squad size led, client organizations onboarded, ARR/GMV processed.

3. The 3 Pillars: Resumes, Cover Letters & Portfolios

┌────────────────────────────────────────────────────────────────────────────────────────┐
│                               THE UNIFIED CAREER STACK                                 │
├───────────────────────┬────────────────────────────────┬───────────────────────────────┤
│ 📄 ATS Resume         │ ✉️ Technical Cover Letter      │ 🌐 Engineering Portfolio      │
├───────────────────────┼────────────────────────────────┼───────────────────────────────┤
│ • 1-page single-column│ • 3-paragraph "Pain Letter"    │ • Dual-funnel evaluation      │
│ • Strict XYZ bullets  │ • < 280 words (or <120w InMail)│ • 5-part STAR-S case studies  │
│ • Categorized skills  │ • Targeted architectural hook  │ • Zero-JS video facades       │
│ • Verifiable metrics  │ • Concrete proof & low-risk CTA│ • LCP < 800ms, CLS = 0.00     │
└───────────────────────┴────────────────────────────────┴───────────────────────────────┘

4. Multi-Persona Recruiter & Hiring Committee Simulator

When asked to audit, critique, or score any document or portfolio, execute a 4-persona concurrent stress-test:

  1. Persona 1 (ATS Parser & Algorithms - Gate 1): Single-column flow, skill co-occurrence density, ISO date parsing, canonical title mapping.
  2. Persona 2 (Technical Recruiter - Gate 2): 6-second F-pattern scan, 1-line startup context, right-aligned date gutters, orthography blacklist check.
  3. Persona 3 (Engineering Manager - Gate 3): Google XYZ formula compliance, 6 quantification dimensions, low-level technical primitives, tutorial clone banishment.
  4. Persona 4 (Amazon Bar Raiser - Gate 4): 16 Leadership Principles proxies, operational excellence (SLAs, on-call), and the "30-Second Defense" against technical follow-ups.

100-Point Scoring Matrix & Decision Gates:

  • 90–100 pts: STRONG HIRE (Top 5% Tier 1 / FAANG L5+/Staff).
  • 80–89 pts: HIRE (Solid Senior / Enterprise Mid-Senior).
  • 70–79 pts: LEANING HIRE / REVISION REQUIRED (Mid-Level with metric gaps).
  • < 70 pts: NO HIRE (Auto-screen rejection risk; fails ATS or 6-second scan).

5. Review & Audit Workflow

When auditing or transforming a resume, cover letter, or portfolio:

  1. Step 1: Check Red-Flag Gates (12-Point List)
    • Check for multi-column tables, skill rating progress bars, photos, pronouns, AI slop words, tutorial clones, and page budget violations.
  2. Step 2: Score Across the 5 Dimensions (100-Point Matrix)
    • Score Bullet Formulation (25 pts), Metric Quantification (20 pts), Skills Architecture (20 pts), ATS Compliance (20 pts), and Visual Hierarchy (15 pts).
  3. Step 3: Generate Markdown Audit Table
    • Provide a structured table: | # | Location | Current Phrasing (Before) | Recommended Gold-Standard Rewrite (After) | Rationale & Metric Lift |.
  4. Step 4: Generate the "30-Second Interview Defense" Scripts
    • Provide the verbal defense script for each rewritten bullet using the Problem (0-8s) $\to$ Mechanism (8-20s) $\to$ Quantified Delta (20-30s) framework.
  5. Step 5: Output Production Document
    • Deliver the finalized, 100% compliant Markdown, LaTeX, or Typst code.

6. Progressive Disclosure & Reference Index

To handle specialized technical resume, cover letter, and portfolio requirements, consult these dedicated reference guides:

NeedResource FileSummary
Authoritative External Linksreferences/external-sources-and-authoritative-links.mdVerified canonical URLs: Harvard MCS, Google Careers, Amazon Jobs, Overleaf, RenderCV
Google Hiring & XYZ Formulareferences/google-hiring-standards-and-xyz-formula.mdLaszlo Bock principles, XYZ formula mechanics, Hiring Committee 4 pillars, SRE 50% rule
Amazon Hiring & Bar Raisersreferences/amazon-hiring-standards-and-bar-raiser.md16 LPs technical proxy mapping, telegraphic STAR method, 6 metric dimensions
Banned Words & AI Slop Datasetdata/banned-words-and-red-flags.jsonMachine-readable JSON linter dataset of 75+ rules, regex patterns & severities
Outbound Job Search & Cold Emailreferences/job-search-outbound-and-cold-email-engine.md4-pronged outbound system, 3-step cold email sequences, deliverability, CRM
LinkedIn Optimization & Presencereferences/linkedin-optimization-and-digital-presence.mdLinkedIn Recruiter algorithm, headline formulas, Story-to-Systems About, RCA posts
Resume Anatomy & Certificationsreferences/section-by-section-anatomy-and-certifications.mdPromotion nesting, company context formulas, umbrella consulting, cert weights
Recruiter & Committee Simulatorreferences/recruiter-audit-simulator-engine.md4-persona audit engine, 100-point rubric, 12 red flags, 30-sec defense
Engineering Portfolios & Case Studiesreferences/engineering-portfolios-and-case-studies.mdDual-funnel portfolio model, 5-part STAR-S case studies, video facades
Cover Letter Mastery & Outreachreferences/cover-letter-mastery-and-outreach.md3-paragraph Pain Letter, cold InMails (<120w), forwardable referral notes
Typography, Fonts & Page Budgetsreferences/typography-layouts-and-page-budgets.mdATS fonts (Inter/Calibri/Latin Modern), 1.15-page fix, Garamond trap
Open Source & JD Matchingreferences/open-source-skills-and-jd-matching.mdJSON Resume schemas, dense SBERT + BM25 diffing, clearances, patents
FAANG & Big Tech Screeningreferences/faang-and-big-tech-screening.mdBig Tech screening mechanics, Meta velocity, Apple craft, Netflix autonomy
Company Tiers & Tailoringreferences/company-tiers-and-tailoring.mdTailoring across FAANG vs Enterprise MNC vs Series A/B vs Seed startups
AI Recruiters & Skills Graphsreferences/ai-recruiters-and-skills-graphs.mdEightfold.ai, SeekOut, Paradox Olivia, skill co-occurrence graphs, career velocity
Master Keywords & Verbsreferences/master-keywords-and-power-verbs.md9 domain keywords taxonomies, banned words dictionary, 350+ domain action verbs
Recruiter Psychology & Heuristicsreferences/recruiter-psychology-and-heuristics.md1-line startup context, tech orthography blacklist, 15-min screening call defense
Modern ATS & Recruitersreferences/modern-ats-and-recruiter-intelligence.mdAshby/Greenhouse parsing, AI slop fatigue, 6-second scan, Boolean search
Technical Projects & Open Sourcereferences/technical-projects-and-open-source.mdBanned tutorial clones vs high-signal systems architectures, open-source PRs
AI & ML Resume Standardsreferences/ai-and-ml-resume-standards.mdEscaping wrapper traps, Hybrid RAG, LangGraph agents, MLOps evals, SLMs
Career Transitions & Gapsreferences/career-transitions-and-complex-scenarios.mdLayoffs, gaps, fractional umbrella consulting, stealth startups, side SaaS
ATS & Layout Standardsreferences/ats-and-formatting.mdMargins, fonts, single-column rules, ATS-safe headings, anti-patterns
Tooling & Verificationreferences/resume-tooling-and-verification.mdLaTeX ligature fixes, Typst, RenderCV, pdftotext/pdffonts CLI testing
Academic CV Conversionreferences/academic-cv-vs-industry.mdConverting PhD/Master's, research, papers, and CS Teaching Fellowships
Cover Letters & Correspondencereferences/cover-letters-and-correspondence.mdHarvard 4-paragraph cover letter structure & cold outreach emails
Review Rubricreferences/resume-review-rubric.md100-point scoring matrix and required review table formats

7. Bundled Production Templates

Template ModelTemplate FileUse Case
Standard 1-Page CS Modeltemplates/standard-cs-resume-template.md1-page CS, SWE, New Grad, and Full-Stack resume (Markdown)
Senior Systems Engineer / Leadtemplates/senior-systems-engineer-template.md1-to-2 page Senior Engineer, Lead, and Systems Architect resume (Markdown)
AI/ML & LLM Systems Engineertemplates/ai-ml-systems-engineer-template.md1-page Applied AI, LLMOps, RAG, and ML Systems resume (Markdown)
Jake's Resume (LaTeX)templates/jakes-resume-latex-template.texOfficial ATS-bulletproof Overleaf / LaTeX template with Unicode fixes
Modern Typst Resumetemplates/typst-resume-template.typInstantaneous compile Typst template with native CMap Unicode font embedding
RenderCV (Resume-as-Code)templates/rendercv-yaml-template.yamlYAML data configuration for automated Typst/PDF resume generation
Technical Cover Lettertemplates/harvard-cover-letter-template.md3-paragraph Value Proposition & Technical Pain Letter (<280 words)

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