---
name: cv-forge
title: "CV Forge — Kreator & Optymalizator CV"
description: "Kreator i optymalizator CV maksymalizujący szanse na rozmowę rekrutacyjną. Przerabia istniejące CV pod konkretną rolę lub buduje od zera. Zawiera: Extraction Interview (wydobywanie ukrytego złota z kandydatów), Nothing-Left-Behind Principle, Page Density Algorithm, DOCX formatting specs (Classic + Modern), role-specific keyword patterns (Python/ML/QA/DevOps/Frontend), Strategic Truth-Stretching Framework, pełną bazę wiedzy ATS/Polish market. Obsługuje wszystkie branże i poziomy (junior/mid/senior), ze szczególną optymalizacją dla polskiego rynku IT."
category: workflow
tags:
  - cv
  - resume
  - rekrutacja
  - ATS
  - career
  - polish-market
  - junior
  - mid
  - senior
source: https://madejski.ai/skilloteka/cv-forge
locale: en
license: MIT
---

# CV Forge — Kreator & Optymalizator CV

## Philosophy

1. **Rekruter ma 6 sekund** — klarowność > kreatywność.
2. **ATS to bramkarz** — 75% CV odrzucane przed człowiekiem. Struktura i keywords > proza.
3. **Strategiczna prawda** — każde doświadczenie w najkorzystniejszym świetle. Każdy claim musi przeżyć "tell me more about that."
4. **Nic nie zostawiaj** — każda informacja z oryginalnego CV trafia do nowej wersji lub jest świadomie odrzucona z uzasadnieniem. Prawo jazdy, certyfikaty in-progress, interests — nic nie ginie po cichu.
5. **Jedna strona = pełna strona** — CV wypełnia CAŁĄ dostępną przestrzeń. Pusta dolna 1/3 to zmarnowana szansa.

## MODE A: CV Rewrite (Primary)

### Phase 1: Extraction Interview

**CRITICAL**: CV ZAWSZE zawiera mniej niż kandydat faktycznie zrobił. Ludzie nie umieją opisywać osiągnięć.

Po przeczytaniu CV, zadaj pytania o KAŻDE niedoopisane doświadczenie:
- "W stażu w firmie X — CO KONKRETNIE robiłeś? Jakie narzędzia? Co dostarczyłeś?"
- "Projekt Y — jaki stack? Ile osób? Kto co robił? Działa live? GitHub?"
- "Jakieś projekty poboczne, narzędzia, skrypty? Nawet małe?"
- "Ktoś używa czegoś co zbudowałeś? Nawet 2 osoby = 'adopted in production'."

**Zasada**: Staż opisany jako "gaining knowledge" ZAWSZE kryje konkretne taski. Wyciągnij je.

### Phase 2: Analysis & Diagnostic
- 🟢 Mocne strony (2-3) → 🔴 Do naprawy (2-3) → 🎯 Strategia
- Confirm direction before rewriting.

### Phase 3: Rewrite

Apply knowledge base. Nothing-Left-Behind Checklist before finalizing:
- [ ] Każda rola/staż z oryginału obecna (możliwie przeframowana)
- [ ] Każdy skill z oryginału gdzieś widoczny
- [ ] Prawo jazdy, certyfikaty (nawet in-progress), języki — przeniesione
- [ ] Interests — zachowane jeśli sygnalizują pasję domenową
- [ ] Linki (GitHub, LinkedIn) — obecne
- [ ] RODO — obecne, aktualna wersja

### Phase 4: DOCX Generation

**Classic Style (default for Polish market):**
- Times New Roman, 10-11pt body. Name: centered, 16-17pt, bold, all-caps, thick bottom border.
- Contact: centered, ♦ separators. Section headers: centered, all-caps, between two lines.
- A4, margins ~0.6" sides / 0.5" top-bottom (adjust to fill).

**Page Density Rules:**
- Fill 90-100% of page. NEVER leave bottom 1/3 empty.
- Underfill → increase font/spacing, expand bullets, add detail.
- Overflow → reduce font (min 10pt), tighten spacing, compress older roles, inline projects.
- Iterate: generate → check pages → adjust → regenerate.

### Phase 5: Output & Follow-up
- Deliver text + highlight changes + flag interview prep items
- Offer: cover letter, interview prep, DOCX, ATS match estimate

## MODE B: CV from Scratch
Interview → ask about: target role, experience, top projects, who uses your work, education/thesis, certs, languages, unfair advantage. Then Phase 3-5.

## Calibration Rules

### Junior (0-2 years)
- Aspiruj Junior+/Mid. NIGDY "szukam pierwszej pracy."
- Projekty = doświadczenie. Stack, rola, metryki.
- Thesis topic ZAWSZE. GitHub OBOWIĄZKOWY.
- Narzędzia używane przez innych (choćby 2 osoby) = "adopted in production."

### Mid (2-5 years)
- Aspiruj Mid+/Senior. Leadership, ADRs, cross-functional.
- Metryki w 60%+ bulletów.

### Senior (5+)
- Systems thinking, business impact, budżety, skale.
- 2 strony OK. Starsze role kompresuj.

### Role-Specific Patterns
See Knowledge Base below for per-role keyword lists and achievement patterns.

## Anti-Patterns (NEVER)
- Zero metrics. "Responsible for...". Generic objectives.
- Missing RODO. Fancy ATS-breaking formatting.
- Undefendable claims. >2 pages (<5y exp = 1 page).
- Skipping extraction. Dropping original info silently. Leaving page partially empty.

---

# Knowledge Base — Baza Wiedzy

## 1. ATS Survival (2025-2026)

### Parsing Rules
- 97.8% Fortune 500 uses ATS. Polish: Pracuj.pl, No Fluff Jobs, JustJoin IT, Bulldog Jobs all ATS/keyword-match.
- Average first-submission ATS score: below 40%. Target: 65-75%.
- ATS reads top-to-bottom. No tables, columns, graphics, headers/footers for critical info.
- .docx safest. PDF OK if text-selectable.
- Standard headers ONLY: "Work Experience"/"Doświadczenie zawodowe", "Skills"/"Umiejętności", "Education"/"Wykształcenie", "Projects"/"Projekty".
- Fonts: Arial, Calibri, Times New Roman, 10-12pt body, 14-16pt headings.
- Margins: 1 inch (min 0.5"). Single-column. Date format: MM/YYYY consistent.
- No emojis, icons, custom bullets. Dedicated Skills section critical.

### Keyword Strategy
- Mirror EXACT phrases from JD. Both full terms and acronyms: "CI/CD (Continuous Integration/Continuous Deployment)".
- Hard skills first → education → title alignment → soft skills.
- Target job title in summary. Skills in section AND proven in bullets.
- Polish market: mix Polish/English tech terms if ad does.

## 2. Polish Market Specifics

### Cultural Expectations
- Photo: optional in IT, expected in traditional. When in doubt for IT: omit.
- RODO clause MANDATORY: "Wyrażam zgodę na przetwarzanie moich danych osobowych dla potrzeb niezbędnych do realizacji procesu rekrutacji zgodnie z Rozporządzeniem Parlamentu Europejskiego i Rady (UE) 2016/679 z dnia 27 kwietnia 2016 r. (RODO)."
- Broader consent variant: add "...również na potrzeby przyszłych procesów rekrutacyjnych."
- Language: match job ad language. Address: city only. DOB/marital: skip in IT.

### Recruiter Behavior
- 5-30 seconds initial scan. Format, clarity, theme first.
- Then: company names, titles, tenure length.
- Job-hopping (<1 year) = flag. Professional summary = rare = competitive advantage.
- Cover letter: 40-50% read them. 60%+ candidates skip → opportunity.

## 3. Extraction Interview Techniques

### The Hidden Gold Problem
People chronically underreport what they did. Common patterns:
- **"Gaining experience"** = actually performed specific tasks (scripting, data mapping, testing, documentation). ALWAYS drill down.
- **"Helped with project"** = had a defined role with deliverables. Ask: what was YOUR part?
- **"Learning new tools"** = configured, operated, maybe customized tools. Ask: which tools? what did you produce?
- **Side projects not mentioned** = tools used by colleagues, scripts automating personal workflow, university projects with real users. Ask explicitly.

### Key Extraction Questions
1. For each role: "What tools did you touch daily? What did you produce/deliver/create?"
2. For vague bullets: "Can you give me ONE specific thing you built, fixed, or improved there?"
3. Production usage: "Does anyone else use something you made? Even 2 people counts."
4. Projects: "What was the tech stack? How many people? What was YOUR responsibility?"
5. Side work: "Any scripts, tools, automations you built for yourself or friends?"

### Transformation Patterns
- "Gaining knowledge" → "Configured EDI Mapper for data transformation"
- "Performing tasks" → "Created XML/XSLT templates for invoice visualization"
- "Observing others" → "Learned B2B integration standards, applied to mapping workflows"
- "Building relationships" → "Collaborated with senior engineers on data pipeline architecture"

## 4. Level-Specific Achievement Engineering

### Junior (0-2 years)
- "Built X using Y, resulting in Z" even for university projects.
- "Collaborated with team of X to deliver Y under Z deadline."
- "Self-taught [framework] and shipped [project] within [timeframe]."
- "Developed tool adopted by X users for [purpose]." — even 2-3 users counts.
- University thesis = legitimate project. Include stack, scope, outcome.

### Mid (2-5 years)
- "Reduced API response time by X% through [technique]."
- "Led migration from X to Y, reducing costs by Z%."
- "Mentored X juniors, increasing team PR throughput by Y%."
- "Introduced CI/CD pipeline cutting deployment time from X to Y."

### Senior (5+ years)
- "Architected platform serving X million daily requests."
- "Led cross-functional team of X across Y timezones."
- "Reduced infrastructure costs by $X/year through [approach]."
- "Established engineering standards adopted by X teams."

## 5. Strategic Truth-Stretching Framework

### Scope Inflation (Legal and Safe)
- "Worked on" → "Contributed to the design and implementation of"
- "Fixed bugs" → "Improved system reliability by resolving X critical issues"
- "Used tool X" → "Leveraged X to optimize Y, resulting in Z"
- Solo → "Independently designed and delivered"
- Team → "Led the [module] of a [N]-person team"

### Metric Manufacturing (Defensible)
- No exact numbers → estimate conservatively. "~30% improvement" is defensible.
- Legitimate metrics: user counts, team sizes, transaction volumes, time savings.

### Title Normalization
- "Programista" doing architecture = "Software Engineer" is fair.
- "Stażysta" shipping production code = "Junior Developer (Internship)" is defensible.

### Gap Management
- 1-3 months: year-only dates. Longer: "Professional development" / "Freelance."

### Interview Defense Line
- Every claim must survive "Tell me more about that."
- Rule: speak for 2 minutes with specifics → it's on the CV.

## 6. Role-Specific Keyword Patterns

### Python Developer / Backend
**Keywords**: Python, Django/Flask/FastAPI, REST API, PostgreSQL/MySQL, Docker, Git, CI/CD, unit testing, microservices, async, ORM.
**Achievements**: API design, database optimization, deployment automation, code review, documentation.

### ML/AI Engineer
**Keywords**: PyTorch/TensorFlow, scikit-learn, pandas, NumPy, model training, feature engineering, MLOps, Jupyter, CNN/RNN/Transformer, hyperparameter tuning.
**Achievements**: model accuracy, training pipeline, dataset size, inference speed, A/B test results.

### Data Scientist
**Keywords**: pandas, SQL, statistical analysis, hypothesis testing, A/B testing, data visualization, Matplotlib/Seaborn, Jupyter, regression, classification.
**Achievements**: insights leading to decisions, dashboard adoption, prediction accuracy, cost savings.

### QA Engineer
**Keywords**: test automation, Selenium/Cypress/Playwright, pytest, test strategy, regression testing, API testing, CI integration, bug tracking, JIRA, test coverage.
**Achievements**: coverage %, bugs caught pre-release, test execution time reduction, automation ROI.

### DevOps / Cloud
**Keywords**: AWS/GCP/Azure, Terraform, Docker, Kubernetes, CI/CD, monitoring, Prometheus/Grafana, IaC, Linux.
**Achievements**: uptime %, deployment frequency, MTTR reduction, cost optimization.

### Frontend
**Keywords**: React/Vue/Angular, TypeScript, HTML/CSS, responsive design, accessibility, Webpack/Vite, state management, Core Web Vitals.
**Achievements**: load time improvement, user engagement, accessibility score, component reusability.

## 7. DOCX Formatting Specifications

### Classic Style (Default — Polish Market)
```
Font: Times New Roman
Body: 10-11pt (adjust to fill page)
Name: 16-17pt, bold, all-caps, centered, letter-spacing 100, thick bottom border
Contact: centered, 9.5-10pt, separated by ♦
Links: blue (#0000EE), underlined
Section headers: centered, 11-12pt, bold, all-caps, letter-spacing 60, between top+bottom lines
Job title: bold, followed by comma and dates
Company: bold, dash, location
Bullets: standard character, indent 360/200
Margins A4: ~0.55-0.65" sides, ~0.35-0.5" top/bottom
RODO: 7-7.5pt, italic, gray (#777), thin top border
```

### Modern Style (Alternative — International/Startup)
```
Font: Calibri, 10-11pt body
Name: 18-20pt, bold, left-aligned, navy (#1B2A4A)
Contact: left-aligned, pipe separators
Section headers: left-aligned, navy, bottom border only
Accents: blue (#2E75B6)
```

### Page Density Algorithm
1. Generate with default spacing
2. Convert to PDF, check page count
3. Overflow → reduce font 0.5pt, tighten spacing 20%, compress projects inline
4. Underfill → increase font 0.5pt, expand spacing 15%, add bullet detail
5. Repeat until 90-100% filled

## 8. Power Verbs by Level

**Junior**: Developed, Built, Implemented, Created, Contributed to, Collaborated on, Designed, Tested, Documented, Automated, Integrated, Configured, Deployed, Analyzed, Resolved

**Mid**: Led, Architected, Optimized, Migrated, Refactored, Mentored, Established, Introduced, Streamlined, Coordinated, Delivered, Scaled, Evaluated, Proposed, Drove

**Senior**: Spearheaded, Orchestrated, Pioneered, Championed, Transformed, Directed, Governed, Defined, Influenced, Strategized, Formulated, Oversaw, Aligned, Evangelized

## 9. Red Flags to Avoid
- Generic objectives → specific summary
- "Responsible for" → action verbs + results
- Every tech ever touched → curate for target
- Typos → automatic rejection
- Zero numbers → 50%+ bullets need metrics
- Dropping original CV info without reason
- Partially empty pages
- Ignoring in-progress certifications

## 10. Cover Letter Quick-Reference
Polish market differentiator (60%+ skip it).
- P1: Why THIS company. P2: Best achievement → their need. P3: Unfair advantage. P4: CTA.
- Never repeat CV. Expand 1-2 stories. Mirror company tone.

## 11. Nothing-Left-Behind Principle
After rewrite, DIFF against original. Every item must be:
- ✅ Present in new version (possibly reframed)
- ❌ Explicitly dropped with reason (e.g., "removed 'Willingness to learn' — soft skill filler")

Never silently omit driver's license, language skills, GitHub links, in-progress certifications, or domain-relevant interests.