resume-project-analyzer

name

resume-project-analyzer

description

Transform codebases into authentic, interview-defensible resume project experience. Use when analyzing a codebase for: (1) Extracting resume-ready project descriptions, (2) Preparing for technical interview questions about past projects, (3) Understanding the engineering depth and value of a codebase, (4) Identifying defensible technical achievements. Prioritizes correctness and interview credibility over exaggeration.

Resume Project Analyzer

Core Principles

• Do NOT fabricate achievements or metrics
• Do NOT assume ownership or leadership without evidence
• When information cannot be reliably inferred from code, ask reflective follow-up questions
• Resume content must always be interview-defensible

Workflow

Follow this 5-step workflow to transform codebase analysis into authentic resume content.

---

STEP 1 — Project Analysis

Analyze the repository to understand the project's nature and technical scope.

Explore:

• Use Glob and Grep to understand the codebase structure
• Read key files: package.json, requirements.txt, go.mod, README, main entry points
• Identify project type, tech stack, and architecture

Document:

• Project type: backend, frontend, ML/AI, system, tool, library
• Tech stack: languages, frameworks, infra, storage, concurrency patterns, ML tooling
• Architecture: patterns, non-trivial components, integrations
• Overall complexity: shallow, medium, or deep engineering depth

Output format:

## Project Analysis

- **Type**: [project type]
- **Tech Stack**: [list technologies]
- **Architecture**: [brief description]
- **Complexity**: [shallow/medium/deep]

---

STEP 2 — Engineering Value Extraction

Identify the real technical problems solved and visible constraints.

Look for:

• Core technical problems: What is being solved? (performance, scalability, reliability, UX, data consistency)
• Visible constraints: What shaped the design? (SLAs, scale requirements, browser support, regulatory requirements)
• Engineering judgment indicators: Trade-offs, architecture choices, custom solutions vs libraries

Avoid:

• Boilerplate code that doesn't require real engineering
• Standard patterns without customization
• Claims not supported by visible evidence

Output format:

## Engineering Value

- **Core Problems Solved**: [list]
- **Visible Constraints**: [list]
- **Engineering Decisions**: [list with evidence]

---

STEP 3 — Confidence Classification

For each inferred contribution, classify confidence level.

Use analysis_framework.md as reference.

Level	Definition	When to Finalize
HIGH	Clearly supported by code	Can finalize immediately
MEDIUM	Reasonable but incomplete inference	Finalize ONLY after user clarification
LOW	Cannot be inferred safely	Finalize ONLY after user confirmation

Rule: Do NOT finalize MEDIUM or LOW confidence claims without user input.

---

STEP 4 — Reflective Questioning (CRITICAL)

Before writing resume bullets, ask targeted questions to resolve uncertainty.

Question guidelines:

• Be concrete and specific
• Reflect real interviewer thinking
• Help clarify responsibility, decisions, and impact

Good reflective questions:

• "Which modules here were you responsible for end-to-end?"
• "Was this design chosen due to performance issues or future scalability?"
• "What scale was this system designed for, even if not fully reached?"
• "What was the hardest technical trade-off you had to make?"
• "Did you implement [specific feature] or was it already there?"

Avoid generic questions:

• "What did you work on?" (too vague)
• "Is this accurate?" (yes/no, doesn't provide context)

Ask only what is necessary to improve resume accuracy and interview readiness.

---

STEP 5 — Resume & Interview Output

After receiving user clarification, generate the final output.

Use resume_templates.md for phrasing guidance.

Use interview_defense.md for interview prep.

Output Format (Fixed)

Generate this exact structure:

## Project Summary
[1-2 concise sentences describing the project]

## Resume-Ready Project Experience
- [Bullet 1: action + what + how + outcome]
- [Bullet 2: action + what + how + outcome]
- [Bullet 3: ...]

## Key Technical Highlights
- [Architecture / algorithms / infra / tooling that demonstrate depth]
- [Specific patterns, optimizations, or design decisions]

## Interview Defense Preparation
- [Likely interviewer follow-up questions with suggested explanation angles]
- [Areas where user should prepare detailed explanations]

## Confidence Notes
- [Which claims are strongly supported by code (HIGH)]
- [Which claims rely on user-provided clarification (MEDIUM)]

Style Constraints

• Sound like a real engineer, not marketing copy
• Prefer: action + constraint + outcome
• Be concise, technical, and honest
• Optimize for interview credibility, not impressiveness

Weak Verbs to Avoid

• "Responsible for"
• "Participated in"
• "Worked on"
• "Helped with"
• "Contributed to"

Strong Action Verbs

• Built / Designed / Engineered / Developed / Created
• Implemented / Integrated / Deployed / Delivered
• Optimized / Improved / Accelerated / Streamlined
• Scaled / Architected / Structured

Resources

references/analysis_framework.md

Detailed framework for:

• Confidence classification
• Engineering value extraction
• Project type indicators
• Depth assessment

references/resume_templates.md

Templates and guidelines for:

• Project description patterns by type
• Strong vs weak verbs
• Effective resume formula

references/interview_defense.md

Interview preparation for:

• Common follow-up questions
• Answer strategies
• STAR method
• Confidence levels by question type