ATS Resume Matcher

Enterprise-grade resume-to-job-description matching with detailed scoring, gap analysis, and optimization suggestions.

Quick Start

When given a resume and job description:

Extract and parse both documents
Run the 7-category ATS analysis
Output the structured match report
Provide prioritized optimization suggestions

Input Handling

Supported Formats

Format	Resume	Job Description
PDF	Yes (extract text)	Yes
DOCX	Yes (extract text)	Yes
Markdown	Yes	Yes
Plain text	Yes	Yes
Pasted content	Yes	Yes

Extraction Priority

If file path provided → Read and extract text
If pasted content → Parse directly
If URL provided → Fetch and extract

ATS Matching Algorithm

Category Weights (Total: 100%)

Category	Weight	Description
Hard Skills	25%	Technical skills, tools, technologies, languages
Experience	20%	Years of experience, seniority level, scope
Keywords	15%	Exact phrase matches, industry terminology
Job Titles	12%	Title alignment, progression, relevance
Soft Skills	10%	Leadership, communication, collaboration
Education	10%	Degrees, certifications, training
Industry	8%	Domain experience, sector knowledge

Scoring Methodology

For each category, calculate:

Category Score = (Matched Items / Required Items) × 100

Weighted Score = Category Score × Category Weight

Overall Match = Σ(All Weighted Scores)

Match Classification

Score Range	Classification	Interpretation
85-100%	Excellent Match	Strong candidate, likely to pass ATS
70-84%	Good Match	Competitive candidate, minor gaps
55-69%	Moderate Match	Some gaps, optimization recommended
40-54%	Weak Match	Significant gaps, major revision needed
0-39%	Poor Match	Role mismatch or major skill gaps

Analysis Process

Step 1: Parse Job Description

Extract from JD:

Required skills (must-have)
Preferred skills (nice-to-have)
Experience requirements (years, level)
Education requirements (degree, field)
Certifications (required/preferred)
Job title keywords
Industry/domain terms
Soft skill indicators

Classify each requirement as:

REQUIRED - Explicitly stated as required/must-have
PREFERRED - Stated as preferred/nice-to-have/bonus
IMPLIED - Inferred from context

Step 2: Parse Resume

Extract from resume:

Technical skills (explicit and demonstrated)
Work experience (titles, duration, scope)
Education (degrees, institutions, dates)
Certifications (names, dates, status)
Achievements (quantified results)
Industry exposure (domains worked in)
Keywords (terminology used)

Step 3: Match Analysis

For each JD requirement, find resume evidence:

EXACT MATCH    → 100% credit (keyword appears exactly)
SYNONYM MATCH  → 85% credit (equivalent term used)
PARTIAL MATCH  → 50% credit (related but not equivalent)
TRANSFERABLE   → 30% credit (skill could apply)
NO MATCH       → 0% credit (not found)

Step 4: Generate Report

See output format below.

Output Format

Generate this exact structure:

# ATS Match Report

## Overall Score: [XX]% - [Classification]

**Resume**: [filename or "Provided content"]
**Position**: [Job title from JD]
**Company**: [Company name if available]
**Analysis Date**: [Current date]

---

## Score Breakdown

| Category | Score | Weight | Weighted | Status |
|----------|-------|--------|----------|--------|
| Hard Skills | XX% | 25% | X.X | [✓/⚠/✗] |
| Experience | XX% | 20% | X.X | [✓/⚠/✗] |
| Keywords | XX% | 15% | X.X | [✓/⚠/✗] |
| Job Titles | XX% | 12% | X.X | [✓/⚠/✗] |
| Soft Skills | XX% | 10% | X.X | [✓/⚠/✗] |
| Education | XX% | 10% | X.X | [✓/⚠/✗] |
| Industry | XX% | 8% | X.X | [✓/⚠/✗] |
| **TOTAL** | | **100%** | **XX.X** | |

Status: ✓ = 70%+, ⚠ = 50-69%, ✗ = <50%

---

## Detailed Analysis

### Hard Skills (XX%)

**Matched (X/Y required)**:
- ✓ [Skill] - Found: "[evidence from resume]"
- ✓ [Skill] - Found: "[evidence from resume]"

**Partial Matches**:
- ⚠ [Required skill] → [Related skill found] (XX% credit)

**Missing**:
- ✗ [Skill] - REQUIRED - Not found
- ✗ [Skill] - PREFERRED - Not found

### Experience (XX%)

**Requirements**:
- Required: [X] years in [domain]
- Found: [Y] years in [domain]
- Match: [Exceeds/Meets/Below] requirement

**Seniority Alignment**:
- Required level: [Senior/Mid/Junior]
- Demonstrated level: [Senior/Mid/Junior]
- Gap: [None/Minor/Significant]

**Scope Match**:
- Required: [team size, budget, scale from JD]
- Demonstrated: [evidence from resume]

### Keywords (XX%)

**Exact Matches (X/Y)**:
- ✓ "[keyword]" - Found [X] times
- ✓ "[keyword]" - Found [X] times

**Missing High-Value Keywords**:
- ✗ "[keyword]" - Appears [X] times in JD
- ✗ "[keyword]" - Industry-standard term

### Job Titles (XX%)

**Title Progression Analysis**:
| Your Title | Target Title | Alignment |
|------------|--------------|-----------|
| [Current] | [JD Title] | XX% |

**Title Keywords**:
- ✓ [Matched title keyword]
- ✗ [Missing title keyword]

### Soft Skills (XX%)

**Demonstrated**:
- ✓ [Soft skill] - Evidence: "[quote from resume]"

**Required but Missing**:
- ✗ [Soft skill] - Add evidence of this skill

### Education (XX%)

**Degree Match**:
- Required: [Degree] in [Field]
- Found: [Degree] in [Field]
- Status: [Meets/Exceeds/Below/Alternative]

**Certifications**:
- ✓ [Cert name] - Matches requirement
- ✗ [Required cert] - Not found

### Industry (XX%)

**Domain Experience**:
- Required: [Industry/Domain]
- Found: [Industries in resume]
- Relevance: [Direct/Adjacent/Transferable]

---

## Gap Summary

### Critical Gaps (Address First)
1. **[Gap]** - Impact: High - [Brief explanation]
2. **[Gap]** - Impact: High - [Brief explanation]

### Important Gaps
1. **[Gap]** - Impact: Medium - [Brief explanation]

### Minor Gaps
1. **[Gap]** - Impact: Low - [Brief explanation]

---

## Optimization Suggestions

### High Impact (Estimated +X-Y% improvement)

1. **[Suggestion title]**
   - Current: [What's in resume now]
   - Recommended: [What to add/change]
   - Where: [Which section to modify]
   - Example: "[Specific wording to consider]"

2. **[Suggestion title]**
   - Current: [What's in resume now]
   - Recommended: [What to add/change]
   - Where: [Which section to modify]
   - Example: "[Specific wording to consider]"

### Medium Impact (Estimated +X-Y% improvement)

1. **[Suggestion]**
   - [Details]

### Quick Wins (Estimated +X-Y% improvement)

1. **[Suggestion]** - [One-line actionable item]
2. **[Suggestion]** - [One-line actionable item]

---

## ATS Compatibility Notes

**Formatting Issues**:
- [Any detected formatting issues that might cause ATS parsing problems]

**Keyword Density**:
- Top JD keywords not in resume: [list]
- Recommendation: [specific advice]

**Section Headers**:
- [Any non-standard headers that ATS might not recognize]

---

## Confidence Level

Analysis confidence: [High/Medium/Low]
- [Reason for confidence level]

Keyword Matching Rules

Skill Synonyms

Apply these common equivalences:

JD Term	Also Accept
JavaScript	JS, ECMAScript, ES6+
Python	Python3, Py
Machine Learning	ML, Deep Learning, AI/ML
Amazon Web Services	AWS, Amazon Cloud
Google Cloud Platform	GCP, Google Cloud
Microsoft Azure	Azure, MS Azure
Continuous Integration	CI, CI/CD
Continuous Deployment	CD, CI/CD
Kubernetes	K8s, K8
PostgreSQL	Postgres, PSQL
MongoDB	Mongo
React.js	React, ReactJS
Node.js	Node, NodeJS
TypeScript	TS
GraphQL	GQL
REST API	RESTful, REST
Agile	Scrum, Kanban, Agile/Scrum
Project Management	PM, Program Management
People Management	Team Leadership, Engineering Management

Experience Level Mapping

JD Requirement	Acceptable Range
Entry level	0-2 years
Junior	1-3 years
Mid-level	3-5 years
Senior	5-8 years
Staff/Principal	8-12 years
Director	10+ years
VP/Head	12+ years

Education Equivalences

Requirement	Also Accept
Bachelor's required	Master's, PhD
Master's preferred	PhD, Bachelor's + 2 years
CS degree	Related technical degree + experience
MBA	Business degree + experience

Suggestion Generation Rules

Prioritization

Generate suggestions in this priority order:

Missing REQUIRED skills - Highest impact
Experience gaps - High impact
Missing exact keywords - Medium-high impact
Missing certifications - Medium impact
Soft skill evidence - Medium impact
Keyword optimization - Low-medium impact
Formatting improvements - Low impact

Suggestion Quality

Each suggestion must be:

Specific - Not generic advice
Actionable - Clear what to do
Evidenced - Based on actual gap found
Realistic - Achievable without lying

Example Suggestion Patterns

For missing skill:

Add [SKILL] to your skills section. Based on your experience with
[RELATED SKILL], you may have exposure to this. If you have any
experience, add a bullet point like: "Utilized [SKILL] for [USE CASE]"

For keyword gap:

The JD mentions "[KEYWORD]" [X] times. Consider incorporating this
terminology in your [SECTION]. For example, change "[CURRENT PHRASING]"
to "[SUGGESTED PHRASING WITH KEYWORD]"

For experience gap:

The role requires [X] years of [DOMAIN] experience. Your resume shows
[Y] years. Emphasize your [RELEVANT EXPERIENCE] and quantify impact
to demonstrate equivalent depth.

Edge Cases

When Resume > JD Requirements

Still note as "Exceeds" not 100%+
Flag potential overqualification concerns
Suggest tailoring to avoid rejection

When JD is Vague

Note confidence as "Medium" or "Low"
Make reasonable inferences
List assumptions made

When Resume Has Non-Standard Format

Extract what's possible
Note any parsing limitations
Provide best-effort analysis

References

For detailed information, see:

references/scoring-methodology.md - Detailed scoring algorithms and edge cases
references/keyword-extraction.md - Extended synonym lists and extraction patterns

ats-resume-matcher