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ATS Resume Scanner Simulator

## ATS Resume Scanner Simulator (Hardened v2.0 - "Reasoned Logic" Edition) **Author:** Scott M **Last Updated:** 2026-03-14 ## CHANGELOG - v2.0: Added

CategoryJob search › Resume
TagsAnalyzingReviewingJob seekerChecklist
Prompt
## ATS Resume Scanner Simulator (Hardened v2.0 - "Reasoned Logic" Edition)
**Author:** Scott M
**Last Updated:** 2026-03-14

## CHANGELOG
- v2.0: Added Chain-of-Thought reasoning block. Added Negative Constraints (Zero-Synonym rule). Added Multi-Persona audit (Bot vs. Recruiter).
- v1.9: Added Exact-Match Title rule. Added Synonym-Trap check. 
- v1.8: Added AI Stealth check. Added PDF font integrity.

## GOAL
Simulate a high-accuracy legacy ATS. **Constraint:** Do NOT be "nice." If it isn't an exact match, it is a failure. Use multi-step reasoning to ensure score accuracy.

---

## EXECUTION STEPS

### Step 1: Internal Reasoning (Hidden/Pre-Analysis)
*Before writing the output*, reason through these points:
1. **Extract:** What are the top 3 "must-haves" in the JD?
2. **Compare:** Does the resume have those *exact* phrases? (Apply Negative Constraint: Synonyms = 0 points).
3. **Format:** Is there a table or header that will likely "scramble" the text for a 2010-era parser?

### Step 2: Strategic Extraction
- Identify 15–25 high-importance keywords.
- Identify the "Target Job Title" from the JD.

### Step 3: The Multi-Persona Audit
- **Persona A (The Legacy Bot):** Look for "Scanner Sinkers" (Tables, columns, headers, footers, non-standard bullets, image-PDF layers).
- **Persona B (The Cynical Recruiter):** Look for "AI Fluff" (delve, tapestry, passion, visionary) and "Employment Gaps."

### Step 4: Knockout & Synonym Check
- **Exact-Match Title:** Must match JD header exactly.
- **Synonym-Trap:** Flag "Customer Success" if JD asks for "Account Management."
- **Naked Acronyms:** Flag "PMP" if it's not spelled out.

### Step 5: Scoring Model (Strict Calculation)
- **Exact Match Keywords (30%):** 0 points for synonyms.
- **Knockout Compliance (20%):** -10% for each missing mandatory item.
- **Formatting Integrity (15%):** -5% for each "Sinker" found.
- **AI Stealth & Tone (15%):** Penalize generic AI-generated summaries.
- **LinkedIn Alignment (10%)**
- **Acronym & Spelling (10%)**

---

## MANDATORY OUTPUT FORMAT

### 1. REASONING LOGIC
* Briefly explain why you gave the scores below based on the "Bot vs. Recruiter" audit.*

### 2. CORE METRICS
* **ATS Match Score:** XX%
* **AI Stealth Score:** XX/100 (Human-tone rating)
* **Job Title Match:** [Pass/Fail]

### 3. THE "HIT LIST"
* **Exact Keywords Matched:** (List 8–10)
* **Synonym Traps (Fix These):** (e.g., Change "X" to "Y")
* **Missing Must-Haves:** (Degree, Years, Certs)

### 4. TECHNICAL AUDIT
* **Parseability Red Flags:** (List formatting errors)
* **AI "Crutch" Words Found:** (List any "bot-speak" found)

### 5. OPTIMIZATION PLAN
* (4–6 direct, non-fluff steps to hit 85%+)

---

## USER VARIABLES
- **TARGET JD:** [Paste text/URL]
- **RESUME:** [Paste text/File]

What this prompt does

Useful for a strict ATS-style review of a resume against a job description. It includes exact-match keyword rules with no synonym credit and audits from both bot and recruiter perspectives.

Model comparison

Claude best follows the format and supports its scoring. Gemini is specific but risks embellishment, while ChatGPT is concise yet makes major exact-match errors.

ClaudeTop overall
42/ 50

+ Most complete scoring breakdown with fact-based revision guidance.

- It speculates about the gap and LinkedIn score and runs somewhat long.

Gemini
41/ 50

+ Precisely identifies the table, title mismatch, and AI clichés.

- Its sample and title reframing could falsely imply five years of PM work.

ChatGPT
40/ 50

+ Presents key disqualifiers and fixes concisely and clearly.

- It counts non-JD terms as matches and wrongly flags the Business degree.

CriterionChatGPTClaudeGeminiLeader
Instruction following898Claude +13%
Accuracy687Claude +14%
Specificity899Tie
Structure999Tie
Right length978ChatGPT +13%

Scored 1–10 by gpt-5.6-sol with model names hidden (2026-09-24). This is an AI review, not a measurement.

Read full answers

We gave three models the same input and copied their answers unedited. Each ran in its CLI (an agent harness), and answers in the ChatGPT or Claude apps or on the web may differ. Outputs are in Korean.

Input used
[Pasted material]
TARGET JD:
Senior Product Manager, Payments – Meridian Pay (Singapore, Hybrid)
We are looking for a Senior Product Manager, Payments to own our cross-border payment roadmap.
Requirements:
- 5+ years of Product Management experience, ideally in fintech or payments
- Bachelor's degree in Business, Computer Science, or related field
- Proven track record shipping B2B SaaS products
- Strong stakeholder management and data-driven decision making
- PMP or CSPO certification is a plus
Responsibilities:
- Own the end-to-end roadmap for cross-border remittance features
- Partner with Engineering, Design, and Compliance teams
- Define and track KPIs for payment success rate and fraud reduction

RESUME:
Daniel Jung
Seoul, South Korea | daniel.jung.pm@gmail.com | linkedin.com/in/danieljungpm

Summary
Passionate and visionary professional with a proven ability to delve into complex problems and deliver impactful results across the product tapestry.

Experience
Customer Success Manager, Payments Team — Finlytics Inc. (2021–2024)
| Achievement | Metric |
|---|---|
| Reduced churn | 12% |
| Improved NPS | +8 pts |
- Led account management for enterprise clients
- Collaborated with engineering on feature requests

Associate PM, Mobile App — Finlytics Inc. (2019–2021)
- Coordinated backlog grooming and sprint planning

Education
B.A. Business Administration, Yonsei University

Certifications: PMP
gpt-5.6-luna (codex CLI · 에이전트 하네스) · Run on 2026-09-24

1. REASONING LOGIC

  • 핵심 필수조건은 5+ years of Product Management, B2B SaaS products 출시 경험, cross-border payment roadmap입니다. 이력서에는 세 문구가 정확히 일치하지 않습니다.
  • Payments, engineering, account management, PMP 등 일부 키워드는 있으나 동의어는 점수로 인정하지 않았습니다.
  • 경력에 Markdown 표가 포함되어 있어 2010년대 레거시 ATS에서 열·행 순서가 섞일 위험이 있습니다.
  • 봇 기준으로는 직함과 핵심 경력 요건이 부족하고, 채용담당자 기준으로도 PM 경력이 2년에 불과해 Senior 레벨과 거리가 있습니다.

2. CORE METRICS

  • ATS Match Score: 34%
  • AI Stealth Score: 35/100
  • Job Title Match: Fail

3. THE “HIT LIST”

Exact Keywords Matched

  • Payments
  • Engineering
  • Product Management 관련 직함: Associate PM
  • Account Management
  • Feature requests
  • Backlog grooming
  • Sprint planning
  • Business
  • PMP
  • LinkedIn

Synonym Traps (Fix These)

  • Customer Success Manager → Product Manager 또는 실제 수행 범위에 맞는 정확한 PM 직함
  • Led account management → stakeholder management
    단, 실제 이해관계자 조율 경험이 있어야 함
  • feature requests → cross-border remittance features
    실제 결제 송금 기능 경험이 있을 때만 수정
  • Improved NPS → data-driven decision making
    KPI 분석 및 의사결정 사례를 구체적으로 추가해야 함
  • PMP → Project Management Professional (PMP)

Missing Must-Haves

  • 5+ years of Product Management experience
  • B2B SaaS products 출시 실적
  • Cross-border payment 또는 remittance roadmap 소유 경험
  • Payment success rate 및 fraud reduction KPI
  • Compliance 팀과의 협업
  • Product Manager 정확 직함
  • PMP/CSPO의 정식 명칭
  • Computer Science 또는 관련 전공 여부

4. TECHNICAL AUDIT

Parseability Red Flags

  • Achievement | Metric Markdown 표: 열 데이터가 뒤섞일 수 있음
  • 표 대신 각 성과를 일반 불릿으로 작성하는 편이 안전함
  • — 및 특수 구분기호 사용: 일부 구형 파서에서 분리 오류 가능
  • 회사·직함·기간을 표준 형식으로 분리하지 않음
  • PDF 원본이 이미지 기반일 경우 OCR 및 텍스트 레이어 검증 필요
  • 헤더, 푸터, 다단 구성 여부는 제공된 텍스트만으로 확인 불가

AI “Crutch” Words Found

  • Passionate
  • visionary
  • delve
  • impactful
  • tapestry
  • proven ability

5. OPTIMIZATION PLAN

  1. 실제 경험에 근거해 Product Manager 역할과 담당 기간을 정확히 기재합니다.
  2. B2B SaaS 제품 출시 사례를 제품명, 고객 유형, 출시 결과와 함께 추가합니다.
  3. 결제·송금 기능, payment success rate, fraud reduction, KPI 수치를 구체적으로 작성합니다.
  4. Engineering, Design, Compliance와 협업한 사례를 일반 불릿으로 추가합니다.
  5. 요약문에서 AI식 수식어를 제거하고 5+년 PM 요건과 결제 도메인 경험을 첫 문장에 배치합니다.
  6. 표를 제거하고 직함 | 회사 | 기간 및 표준 불릿 구조로 재작성합니다.

현재 이력서는 Senior Product Manager, Payments 포지션 기준으로는 핵심 경력과 직함 불일치 때문에 85% 이상으로 올리기 어렵습니다.

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