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Prompts ATS Resume Scanner Simulator

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ATS Resume Scanner Simulator

Simulates a strict legacy ATS to scan a resume against a job description using chain-of-thought reasoning, multi-persona audits, exact-match keyword checks, and formatting analysis…

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]

INPUTS

TARGET_JD REQUIRED

Paste text/URL of the job description

RESUME REQUIRED

Paste text/file of the resume

REQUIRED CONTEXT

  • TARGET JD text/URL
  • RESUME text/file

ROLES & RULES

  1. Do NOT be "nice."
  2. If it isn't an exact match, it is a failure.
  3. Use multi-step reasoning to ensure score accuracy.
  4. Before writing the output, reason through these points.
  5. Apply Negative Constraint: Synonyms = 0 points.
  6. Must match JD header exactly.

EXPECTED OUTPUT

Format
structured_report
Schema
markdown_sections · REASONING LOGIC, CORE METRICS, THE "HIT LIST", TECHNICAL AUDIT, OPTIMIZATION PLAN
Constraints
  • Brief reasoning logic first
  • Core metrics with ATS Match Score as XX%, AI Stealth Score as XX/100, Job Title Match as Pass/Fail
  • Hit list with exact keywords (8-10), synonym traps, missing must-haves
  • Technical audit with parseability red flags and AI crutch words
  • 4-6 direct optimization steps

SUCCESS CRITERIA

  • Simulate high-accuracy legacy ATS strictly
  • Extract top must-haves and compare exactly
  • Perform Multi-Persona audit
  • Apply strict scoring model
  • Provide mandatory output format

FAILURE MODES

  • Overly lenient scoring
  • Allowing synonyms points
  • Missing formatting sinkers
  • Ignoring AI fluff detection
  • Incomplete reasoning log

CAVEATS

Dependencies
  • Requires TARGET JD text/URL
  • Requires RESUME text/File
Missing context
  • Handling instructions for JD/Resume provided as URLs or files (vs. pasted text).
  • Examples of expected inputs (sample JD and resume).
Ambiguities
  • Scoring criteria for 'LinkedIn Alignment (10%)' not specified.
  • Exact calculation formulas for Scoring Model percentages unclear (e.g., how to assign points within categories).
  • Definition of 'Employment Gaps' in Persona B not detailed.

QUALITY

OVERALL
0.90
CLARITY
0.85
SPECIFICITY
0.90
REUSABILITY
0.95
COMPLETENESS
0.85

IMPROVEMENT SUGGESTIONS

  • Add explicit formulas or rubrics for each scoring category (e.g., 'Exact Match Keywords: 3 points per match out of 10 keywords').
  • Provide a list of common 'AI Crutch Words' and 'Scanner Sinkers' with examples.
  • Clarify 'LinkedIn Alignment' metric (e.g., 'Check if resume mirrors typical LinkedIn profiles for the role').

USAGE

Copy the prompt above and paste it into your AI of choice — Claude, ChatGPT, Gemini, or anywhere else you're working. Replace any placeholder sections with your own context, then ask for the output.

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