Customizable Job Scanner
# 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?
LinkedIn Summary Crafting Prompt
# LinkedIn Summary Crafting Prompt
## Author
Scott M.
## Goal
The goal of this prompt is to guide an AI in creating a personalized, authentic LinkedIn "About" section (summary) that effectively highlights a user's unique value proposition, aligns with targeted job roles and industries, and attracts potential employers or recruiters. It aims to produce output that feels human-written, avoids AI-generated clichés, and incorporates best practices for LinkedIn in 2025–2026, such as concise hooks, quantifiable achievements, and subtle calls-to-action. Enhanced to intelligently use attached files (resumes, skills lists) and public LinkedIn profile URLs for auto-filling details where relevant. All drafts must respect the current About section limit of 2,600 characters (including spaces); aim for 1,500–2,000 for best engagement.
## Audience
This prompt is designed for job seekers, professionals transitioning careers, or anyone updating their LinkedIn profile to improve visibility and job prospects. It's particularly useful for mid-to-senior level roles where personalization and storytelling can differentiate candidates in competitive markets like tech, finance, or manufacturing.
## Changelog
- Version 1.0: Initial prompt with basic placeholders for job title, industry, and reference summaries.
- Version 1.1: Converted to interview-style format for better customization; added instructions to avoid AI-sounding language and incorporate modern LinkedIn best practices.
- Version 1.2: Added documentation elements (goal, audience); included changelog and author; added supported AI engines list.
- Version 1.3: Minor hardening — added subtle blending instruction for references, explicit keyword nudge, tightened anti-cliché list based on 2025–2026 red flags.
- Version 1.4: Added support for attached files (PDF resumes, Markdown skills, etc.); instruct AI to search attachments first and propose answers to relevant questions (#3–5 especially) before asking user to confirm.
- Version 1.5: Added Versioning & Adaptation Note; included sample before/after example; added explicit rule: "Do not generate drafts until all key questions are answered/confirmed."
- Version 1.6: Added support for user's public LinkedIn profile URL (Question 9); instruct AI to browse/summarize visible public sections if provided, propose alignments/improvements, but only use public data.
- Version 1.7: Added awareness of 2,600-character limit for About section; require character counts in drafts; added post-generation instructions for applying the update on LinkedIn.
## Versioning & Adaptation Note
This prompt is iterated specifically for high-context models with strong reasoning, file-search, and web-browsing capabilities (Grok 4, Claude 3.5/4, GPT-4o/4.1 with browsing).
For smaller/older models: shorten anti-cliché list, remove attachment/URL instructions if no tools support them, reduce questions to 5–6 max.
Always test output with an AI detector or human read-through. Update Changelog for changes. Fork for industry tweaks.
## Supported AI Engines (Best to Worst)
- Best: Grok 4 (strong file/document search + browse_page tool for URLs), GPT-4o (creative writing + browsing if enabled).
- Good: Claude 3.5 Sonnet / Claude 4 (structured prose + browsing), GPT-4 (detailed outputs).
- Fair: Llama 3 70B (nuance but limited tools), Gemini 1.5 Pro (multimodal but inconsistent tone).
- Worst: GPT-3.5 Turbo (generic responses), smaller LLMs (poor context/tools).
## Prompt Text
I want you to help me write a strong LinkedIn "About" section (summary) that's aimed at landing a [specific job title you're targeting, e.g., Senior Full-Stack Engineer / Marketing Director / etc.] role in the [specific industry, e.g., SaaS tech, manufacturing, healthcare, etc.].
Make it feel like something I actually wrote myself—conversational, direct, with some personality. Absolutely no over-the-top corporate buzzwords (avoid "synergy", "leverage", "passionate thought leader", "proven track record", "detail-oriented", "game-changer", etc.), no unnecessary em-dashes, no "It's not X, it's Y" structures, no "In today's world…" openers, and keep sentences varied in length like real people write. Blend any reference styles subtly—don't copy phrasing directly. Include relevant keywords naturally (pull from typical job descriptions in your target role if helpful). Aim for 4–7 short paragraphs that hook fast in the first 2–3 lines (since that's what shows before "See more").
**Important rules:**
- If the user has attached any files (resume PDF, skills Markdown, text doc, etc.), first search them intelligently for relevant details (experience, roles, achievements, years, wins, skills) and use that to propose or auto-fill answers to questions below where possible. Then ask for confirmation or missing info—don't assume everything is 100% accurate without user input.
- If the user provides their LinkedIn profile URL, use available browsing/fetch tools to access the public version only. Summarize visible sections (headline, public About, experience highlights, skills, etc.) and propose how it aligns with target role/answers or suggest improvements. Only use what's publicly visible without login — confirm with user if data seems incomplete/private.
- Do not generate any draft summaries until the user has answered or confirmed all relevant questions (especially #1–7) and provided clarifications where needed. If input is incomplete, politely ask for the missing pieces first.
- Respect the LinkedIn About section limit: maximum 2,600 characters (including spaces, line breaks, emojis). Provide an approximate character count for each draft. If a draft exceeds or nears 2,600, suggest trims or prioritize key content.
To make this spot-on, answer these questions first so you can tailor it perfectly (reference attachments/URL where they apply):
1. What's the exact job title (or 1–2 close variations) you're going after right now?
2. Which industry or type of company are you targeting (e.g., fintech startups, established manufacturing, enterprise software)?
3. What's your current/most recent role, and roughly how many years of experience do you have in this space? (If attachments/LinkedIn URL cover this, propose what you found first.)
4. What are 2–3 things that make you different or really valuable? (e.g., "I cut deployment time 60% by automating pipelines", "I turned around underperforming teams twice", "I speak fluent Spanish and have led LATAM expansions", or even a quirk like "I geek out on optimizing messy legacy code") — Pull strong examples from attachments/URL if present.
5. Any big, specific wins or results you're proud of? Numbers help a ton (revenue impact, % improvements, team size led, projects shipped). — Extract quantifiable achievements from resume/attachments/URL first if available.
6. What's your tone/personality vibe? (e.g., straightforward and no-BS, dry humor, warm/approachable, technical nerd, builder/entrepreneur energy)
7. Are you actively job hunting and want to include a subtle/open call-to-action (like "Open to new opportunities in X" or "DM me if you're building cool stuff in Y")?
8. Paste 2–4 LinkedIn About sections here (from people in similar roles/industries) that you like the style of—or even ones you don't like, so I can avoid those pitfalls.
9. (Optional) What's your current LinkedIn profile URL? If provided, I'll review the public version for headline, About, experience, skills, etc., and suggest how to build on/improve it for your target role.
Once I have your answers (and any clarifications from attachments/URL), I'll draft 2 versions: one shorter (~150–250 words / ~900–1,500 chars) and one fuller (~400–500 words / ~2,000–2,500 chars max to stay safely under 2,600). Include approximate character counts for each. You can mix and match from them.
**After providing the drafts:**
Always end with clear instructions on how to apply/update the About section on LinkedIn, e.g.:
"To update your About section:
1. Go to your LinkedIn profile (click your photo > View Profile).
2. Click the pencil icon in the About section (or 'Add profile section' > About if empty).
3. Paste your chosen draft (or blended version) into the text box.
4. Check the character count (LinkedIn shows it live; max 2,600).
5. Click 'Save' — preview how the first lines look before "See more".
6. Optional: Add line breaks/emojis for formatting, then save again.
Refresh the page to confirm it displays correctly."
