MakiDevelop /cv-optimize — Resume Analysis & Optimization
Read a resume file (PDF / Markdown / DOCX), perform structured analysis, and produce a target-role-optimized PDF.
Phase 0: Collect Input
- Resume file: Read from user-provided path (supports PDF / Markdown)
- Target info (from arguments or ask user):
- Target role (e.g., "AI Engineer", "PM", "Data Scientist")
- Target company name (optional, for tailoring)
- JD content or link (optional, for keyword alignment)
- Emphasis points (e.g., "leadership", "bilingual", "career transition")
If no target role is provided, ask once:
What role are you optimizing for? (e.g., AI Engineer / PM / Data Scientist / general)
Any specific strengths you want to emphasize?
Phase 1: Resume Analysis
After reading the full resume, output a structured analysis:
## Resume Analysis — {Name}
### Basic Info
- Name / Target title / Total experience / Education
### Strengths (Keep)
1. ... (list 3-5 highlights worth keeping, especially quantified achievements)
### Issues (Needs Optimization)
| # | Issue | Severity | Description |
|---|-------|----------|-------------|
| 1 | ... | High/Med/Low | ... |
### Target Role Match Analysis
| Requirement | Candidate's Experience | Match Level |
|-------------|----------------------|-------------|
| ... | ... | Strong/Medium/Weak/Gap |
Mandatory checks (every resume):
- Title vs target alignment
- Summary is focused (no more than 3 key positioning statements)
- Each experience has quantified results
- Skills section aligned with target role (flag outdated skills)
- Timeline is clear and consistent
- Structure depth doesn't exceed 2 levels
- Space allocation proportional to relevance
- Each role includes Tech Stack
Phase 2: Reposition & Optimize
2.1 Positioning Adjustment
- Redefine subtitle (role positioning statement)
- Rewrite Summary (focus on 2-3 key differentiators with numbers)
- If emphasis points were specified, highlight them in Summary and highlight box
2.2 Experience Restructuring
- Add Tech Stack tags to each role (blockquote or meta style)
- Expand highly relevant experiences with section-label sub-blocks
- Condense less relevant experiences to 2-4 bullets
- Every bullet follows "Action verb + what you did + quantified result"
- Avoid weak verbs ("participated", "assisted") → use "led", "designed", "built", "optimized"
2.3 Skills Section Rebuild
- Remove skills irrelevant to target role
- Group by category (e.g., AI/ML, Data, Infrastructure, Tools)
- Ensure target role's core keywords all appear
2.4 Special Sections (add when appropriate)
- "Why I'm right for X" highlight box: when target is clear and emphasis points exist
- "Career transition trajectory": when candidate has obvious career pivots
- Selected side projects table: keep only 3-5 relevant to target
Phase 3: Generate Optimized PDF
Use uv run --with weasyprint to generate PDF.
3.1 HTML Structure
Element mapping:
- h1 → Name
- .subtitle → Role positioning statement
- .contact → Contact info
- h2 → Major section titles (Summary / Experience / Skills)
- .job-title → Job title per role
- .job-company → Company + location + dates
- .job-meta → Tech Stack (blue left-border blockquote)
- .section-label → Sub-section titles (gray background)
- ul > li → Bullet points (single level only, no nesting)
- table → Competencies / Skills / Projects
- .highlight-box → Special emphasis block (blue left-border + light gray background)
3.2 Layout Rules
- Target 2 pages (max 3, never leave a near-empty trailing page)
- Font size: headings 21-22pt / body 9-9.5pt / meta 8.5pt
- Line height 1.5-1.55
- Margins 16-18mm
- Table headers: dark blue background, white text; even rows light gray
- No 3+ level nesting — flatten deep structures
3.3 PDF Generation
# Zero-install execution with uv
uv run --with weasyprint python3 script.py
After generation:
- Use Read tool to verify PDF layout
- If trailing page is too empty, adjust margin/font-size and regenerate
- Confirm page count is reasonable, tell user the file path
3.4 Output File Naming
{original_file_directory}/{Name}_{Target_Role}_optimized.pdf
Phase 4: Change Summary
Output a concise comparison table:
| Item | Original | Optimized |
|------|----------|-----------|
| Positioning | ... | ... |
| Summary | ... | ... |
| Skills | ... | ... |
| Length | ... | ... |
Plus notes (e.g., sections where the candidate needs to provide specific numbers).
Design Principles
- One resume, one narrative — all bullets serve the same positioning story
- Quantify > describe — "improved 67%" beats "significantly improved" every time
- Delete > shrink > keep — irrelevant experience: cut to 2 lines, don't waste half a page
- ATS-friendly — ensure target role's core keywords appear in Summary + Skills + Experience
- Clear visual hierarchy — 10-second scan reveals: name → positioning → 3 key numbers → timeline
- No empty words — delete "eager learner", "team player", "value creator" — they carry zero information
Color System
Primary (dark blue):
- Heading text: #0d1b2a
- Section titles: #1b263b
- Accent: #415a77
- Light background: #f0f4f8
- Table header: #1b263b (white text)
- Table even rows: #f8f9fa
- Section labels: #e8edf2