Find agent skills by outcome

- Partial: Exposure

adjacent work

- Expert: Multiple examples

leadership

[1-paragraph bio: years exp

companies

- Sources: Aggregated recent job trends (LinkedIn Economic Graph

Indeed Hiring Lab

5. Llama (Meta): Budget option

but may require more prompting for precision.

For optimal results

use this prompt with the following AI models

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.

February 04

2026

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

changelog updates

- Prioritize factual accuracy

ATS keywords (e.g.

- If user requests interview style

prep mode

Professionals in tech

cybersecurity

- Use [USER NAME]

[USER JOB GOAL]

Create a polished

ATS-optimized markdown document summarizing skills

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

produce a concise summary of the recommended action

Include post-clearing tips (e.g.

proper piling/drainage to avoid pooling/refreeze

Master Skills & Experience Summary Generator

# Prompt Name: Master Skills & Experience Summary Generator

- Forecasted snowfall

precipitation type

First

determine the user's location. If not clearly provided in the query or the above section

If the user has not filled in driveway details in the section above (or provided them in the query)

**ask for relevant ones early** (especially slope

# - Other preferences/factors: [e.g.

pet-safe only

If helpful

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