Find agent skills by outcome

- Partial: Exposure

adjacent work

- Prioritize [LOCATION if specified

else national/remote/US trends].

- Expert: Multiple examples

leadership

- Include emerging tools/standards (e.g.

GenAI

[1-paragraph bio: years exp

companies

- Sources: Aggregated recent job trends (LinkedIn Economic Graph

Indeed Hiring Lab

- If live postings are limited/blocked

fall back to aggregated trend reports and common required/preferred skills.

Focus: Goal-first optimization for ATS

recruiter scans

USER INPUT (raw bullets

stories

USER JOB GOAL: [THEIR TARGET ROLE/INDUSTRY – be as specific as possible

e.g.

5. Llama (Meta): Budget option

but may require more prompting for precision.

For optimal results

use this prompt with the following AI models

- Treat this output as a version-controlled master document: Include patch versioning

changelog updates

- Prioritize factual accuracy

ATS keywords (e.g.

February 04

2026

Professionals in tech

cybersecurity

- If user requests interview style

prep mode

- Use [USER NAME]

[USER JOB GOAL]

Create a polished

ATS-optimized markdown document summarizing skills

Master Skills & Experience Summary Generator

# Prompt Name: Master Skills & Experience Summary Generator

After considering all factors (weather + user/driveway details)

produce a concise summary of the recommended action

Advise on ice melt usage (if any)

including timing (pre-storm prevention vs. post-clearing anti-refreeze)

Include post-clearing tips (e.g.

proper piling/drainage to avoid pooling/refreeze

If helpful

compare scenarios: clearing immediately/during/after storm vs. waiting for passive melting