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Customizable Job Scanner

# Customizable Job Scanner - AI Optimized **Author:** Scott M **Version:** 2.0 **Goal:** Surface 80%+ matching [job sector] roles posted within the sp

CategoryJob search › Resume
TagsAnalyzingSummarizingJob seekerTable
Prompt
# Customizable Job Scanner - AI Optimized
**Author:** Scott M  
**Version:** 2.0  
**Goal:** Surface 80%+ matching [job sector] roles posted within the specified window (default: last 14 days), using real-time web searches across major job boards and company career sites.  
**Audience:** Job boards (LinkedIn, Indeed, etc.), company career pages  
**Supported AI:** Claude, ChatGPT, Perplexity, Grok, etc.

## Changelog
- **Version 1.0 (Initial Release):**  
  Converted original cybersecurity-specific prompt to a generic template. Added placeholders for sector, skills, companies, etc. Removed Dropbox file fetch.
- **Version 1.1:**  
  Added "How to Update and Customize Effectively" section with tips for maintenance. Introduced Changelog section for tracking changes. Added Version field in header.
- **Version 1.2:**  
  Moved Changelog and How to Update sections to top for easier visibility/maintenance. Minor header cleanup.
- **Version 1.3:**  
  Added "Job Types" subsection to filter full-time/part-time/internship. Expanded "Location" to include onsite/hybrid/remote options, home location, radius, and relocation preferences. Updated tips to cover these new customizations.
- **Version 1.4:**  
  Added "Posting Window" parameter for flexible search recency (e.g., last 7/14/30 days). Updated goal header and tips to reference it.
- **Version 1.5:**  
  Added "Posted Date" column to the output table for better recency visibility. Updated Output format and tips accordingly.
- **Version 1.6:**  
  Added optional "Minimum Salary Threshold" filter to exclude lower-paid roles where salary is listed. Updated Output format notes and tips for salary handling.
- **Version 1.7:**  
  Renamed prompt title to "Customizable Job Scanner" for broader/generic appeal. No other functional changes.
- **Version 1.8:**  
  Added optional "Resume Auto-Extract Mode" at top for lazy/fast setup. AI extracts skills/experience from provided resume text. Updated tips on usage.
- **Version 1.9 (Previous stable release):**  
  - Added optional "If no matches, suggest adjustments" instruction at end.  
  - Added "Common Tags in Sector" fallback list for thin extraction.  
  - Made output table optionally sortable by Posted Date descending.  
  - In Resume Auto-Extract Mode: AI must report extracted key facts and any added tags before showing results.
- **Version 2.0 (Current revised version):**  
  - Added explicit real-time search instruction ("Act as a real-time job aggregator... use current web browsing/search capabilities") to prevent hallucinated or outdated job listings.  
  - Enhanced scoring system: added bonuses for verbatim/near-exact ATS keyword matches, quantifiable alignment, and very recent postings (<7 days).  
  - Expanded "Additional sources" to include Google Jobs, FlexJobs (remote), BuiltIn, AngelList, We Work Remotely, Remote.co.  
  - Improved output table: added columns for Location Type, ATS Keyword Overlap, and brief "Why Strong Match?" rationale (for 85%+ matches).  
  - Top Matches (90%+) section now uses bolded/highlighted rows for better visual distinction.  
  - Expanded no-matches suggestions with more actionable escalations (e.g., include adjacent titles, temporarily allow contract roles, remove salary filter).  
  - Minor wording cleanups for clarity, flow, and consistency across sections.  
  - Strengthened Top Instruction block to enforce live searches and proper sequencing (extract first → then search).

## Top Instruction (Place this at the very beginning when you run the prompt)
"Act as my dedicated real-time job scout with current web browsing and search access.  
First: [If using Resume Auto-Extract Mode: extract and summarize my skills, experience, achievements, and technical stack from the pasted resume text. Report the extraction summary including confidence levels (Expert/Strong/Inferred) before showing any job results.]  
Then: Perform live, current searches only (no internal/training data or outdated knowledge). Pull the freshest postings matching my parameters below. Use the scoring system strictly. Prioritize ATS keyword alignment, recency, and my custom tags/skills."

## Resume Auto-Extract Mode (Optional - For Lazy/Fast Setup)
If skipping manual Skills Reference:  
- Paste your full resume text here:  
  [PASTE RESUME TEXT HERE]  
- Keep the Top Instruction above with the extraction part enabled.  
The AI will output something like:  
"Resume Extraction Summary:  
- Experience: 12+ years in cybersecurity / DevOps / [sector]  
- Key achievements: Led X migration (Y endpoints), reduced Z by A%  
- Top skills (with confidence): CrowdStrike (Expert), Terraform (Strong), Python (Expert), ...  
- Suggested tags added: SIEM, KQL, Kubernetes, CI/CD  
Proceeding with search using these."

## How to Update and Customize Effectively
- Use Resume Auto-Extract when short on time; verify the summary before trusting results.  
- Refresh Skills Reference / tags every 3–6 months or after major projects.  
- Use exact phrases from job postings / your resume in tags for ATS alignment.  
- Test across AIs; if too few results → lower threshold, extend window, add adjacent titles/tags.  
- For new sectors: research top keywords via LinkedIn/Indeed/Google Jobs first.

## Skills Reference
(Replace manually or let AI auto-populate from resume)  
**Professional Overview**  
- [Years of experience, key roles/companies]  
- [Major projects/achievements with numbers]  

**Top Skills**  
- [Skill] (Expert/Strong): [tools/technologies]  
- ...  

**Technical Stack**  
- [Category]: [tools/examples]  
- ...

## Common Tags in Sector (Fallback)
If extraction is thin, add relevant ones here (1 point unless core). Examples:  
- Cybersecurity: Splunk, SIEM, KQL, Sentinel, CrowdStrike, Zero Trust, Threat Hunting, Vulnerability Management, ISO 27001, PCI DSS, AWS Security, Azure Sentinel  
- DevOps/Cloud: Kubernetes, Docker, Terraform, CI/CD, Jenkins, Git, AWS, Azure, Ansible, Prometheus  
- Software Engineering: Python, Java, JavaScript, React, Node.js, SQL, REST API, Agile, Microservices  
[Add your sector’s common tags when switching]

## Job Search Parameters
Search for [job sector e.g. Cybersecurity Engineer, Senior DevOps Engineer] jobs posted in the last [Posting Window].

### Posting Window
[last 14 days] (default) / last 7 days / last 30 days / since YYYY-MM-DD

### Minimum Salary Threshold
[e.g. $130,000 or $120K — only filters jobs where salary is explicitly listed; set N/A to disable]

### Priority Companies (check career pages directly if few results)
- [Company 1] ([career page URL])  
- [Company 2] ([career page URL])  
- ...

### Additional Sources
LinkedIn, Indeed, Google Jobs, Glassdoor, ZipRecruiter, Dice, FlexJobs (remote), BuiltIn, AngelList, We Work Remotely, Remote.co, company career sites

### Job Types
Must include: full-time, permanent  
Exclude: part-time, internship, contract, temp, consulting, C2H, contractor

### Location
Must match one of:  
- 100% remote  
- Hybrid (partial remote)  
- Onsite only if within [50 miles] of East Hartford, CT (includes Hartford, Manchester, Glastonbury, etc.)  
Open to relocation: [Yes/No; if Yes → anywhere in US / Northeast only / etc.]

### Role Types to Include
[e.g. Security Engineer, Senior Security Engineer, Cybersecurity Analyst, InfoSec Engineer, Cloud Security Engineer]

### Exclude Titles With
manager, director, head of, principal, lead (unless explicitly wanted)

## Scoring System
Match job descriptions against my tags from Skills Reference + Common Tags:  
- Core/high-value tags: 2 points each  
- Standard tags: 1 point each  
Bonuses:  
+1–2 pts for verbatim / near-exact keyword matches (strong ATS signal)  
+1 pt for quantifiable alignment (e.g. “manage large environments” vs my “120K endpoints”)  
+1 pt for very recent posting (<7 days)  

Match % = (total matched points / max possible points) × 100  
Show only jobs ≥80%

## Output Format
Table:  
| Job Title | Match % | Company | Posted Date | Location Type | Salary | ATS Overlap | URL | Why Strong Match? |

- **Posted Date:** Exact if available (YYYY-MM-DD or "Posted Jan 10, 2026"); otherwise "Approx. X days ago" or N/A  
- **Salary:** Only if explicitly listed; N/A otherwise (no estimates)  
- **Location Type:** Remote / Hybrid / Onsite  
- **ATS Overlap:** e.g. "9/14 top tags matched" or "Strong keyword overlap"  
- **Why Strong Match?:** 2–3 bullet highlights (only for 85%+ matches)  

Sort table by Posted Date descending (most recent first), then Match % descending.  
Remove duplicates (same title + company).  

Put 90%+ matches in a separate section at top called **Top Matches (90%+)** with bolded rows or clear highlighting.

If no strong matches:  
"No strong matches found in the current window."  
Then suggest adjustments:  
- Extend Posting Window to 30 days?  
- Lower threshold to 75%?  
- Add common sector tags (e.g. Splunk, Kubernetes, Python)?  
- Broaden location / include more hybrid options?  
- Include adjacent role titles (e.g. Cloud Engineer, Systems Engineer)?  
- Temporarily allow contract roles?  
- Remove/lower Minimum Salary Threshold?  
- Manually check priority company career pages for unindexed postings?

What this prompt does

This is useful for job seekers scanning job boards and company career pages. It includes real-time search, posted-date and salary filters, and resume auto-extraction, but assumes an environment that can search the web.

Model comparison

ChatGPT is better than Gemini because it refuses to fabricate live results, though both invent missing inputs; [C] is absent.

ChatGPTTop overall
32/ 50

+ It discloses limits and avoids fake listings.

- It invents inputs and gives an inaccurate date range.

Gemini
22/ 50

+ Clear tables and readable match rationales.

- It invents the resume, filters, dates, and jobs.

CriterionChatGPTGeminiLeader
Instruction following64ChatGPT +50%
Accuracy51ChatGPT +400%
Specificity53ChatGPT +67%
Structure88Tie
Right length86ChatGPT +33%

Scored 1–10 by gpt-5.6-sol with model names hidden (2026-09-25). 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]
[job sector]: 데이터 분석 / BI

## Resume Auto-Extract Mode
[PASTE RESUME TEXT HERE]
홍성민 | 데이터 분석가, 5년차
- 이커머스 스타트업 '그린마켓'에서 3년간 BI 대시보드 구축 (Tableau, Looker)
- SQL, Python(Pandas), GA4 기반 퍼널 분석으로 재구매율 12% 개선
- 이전 직장: 신한데이터시스템, 데이터 엔지니어 2년
기술: SQL(Expert), Python(Strong), Tableau(Expert), BigQuery(Strong), dbt(Inferred)

## 파라미터
- Posting Window: 최근 14일
- Location: 서울 강남/판교, 하이브리드 선호, 원격도 가능
- Job Types: 정규직
- Minimum Salary Threshold: 5,500만원
- 추가 태그: GA4, dbt, Amplitude, A/B 테스트
gpt-5.6-luna (codex CLI · 에이전트 하네스) · Run on 2026-09-24

이력서 추출 요약

  • 경력: 데이터 분석가 3년 + 데이터 엔지니어 2년, 총 5년
  • 핵심 역량:
    • SQL — Expert
    • Tableau — Expert
    • Python/Pandas — Strong
    • BigQuery — Strong
    • GA4 퍼널 분석 — Strong
    • dbt — Inferred
  • 주요 성과: 퍼널 분석을 통해 재구매율 12% 개선
  • BI 경험: Tableau·Looker 기반 대시보드 구축
  • 추가 검색 태그: Amplitude, A/B 테스트
  • 적합 직무: 데이터 분석가, BI Analyst, Product/Data Analyst, 마케팅 데이터 분석가, BI Engineer

현재 세션에서는 실시간 웹 브라우징 도구가 제공되지 않아 2026-09-10~2026-09-24 사이에 실제 게시된 공고를 검증할 수 없습니다. 따라서 공고·게시일·급여·URL을 임의로 생성하지 않았습니다.

검색 조건을 적용하면 다음 기준으로 선별해야 합니다.

  • 서울 강남·판교 중심, 하이브리드 우선 및 원격 허용
  • 정규직만 포함
  • 명시 급여 5,500만 원 이상
  • 데이터 분석·BI 관련 직무
  • SQL, Tableau, Python, BigQuery, GA4, dbt, Amplitude, A/B 테스트 키워드 우선
  • 최근 14일 이내 게시 공고만 포함
  • 동일 회사·동일 직무 중복 제거

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