Find agent skills by outcome

- Partial: Exposure

adjacent work

- Expert: Multiple examples

leadership

- Include emerging tools/standards (e.g.

GenAI

[Repeat sections

ordered by descending goal fit]

Role: [Role → Role – Company

Date Range]

[1-paragraph bio: years exp

companies

- Sources: Aggregated recent job trends (LinkedIn Economic Graph

Indeed Hiring Lab

Focus: Goal-first optimization for ATS

recruiter scans

5. Llama (Meta): Budget option

but may require more prompting for precision.

USER INPUT (raw bullets

stories

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

e.g.

February 04

2026

For optimal results

use this prompt with the following AI models

- Prioritize factual accuracy

ATS keywords (e.g.

- If user requests interview style

prep mode

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

changelog updates

Professionals in tech

cybersecurity

Create a polished

ATS-optimized markdown document summarizing skills

- Use [USER NAME]

[USER JOB GOAL]

Include post-clearing tips (e.g.

proper piling/drainage to avoid pooling/refreeze

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

produce a concise summary of the recommended action

Master Skills & Experience Summary Generator

# Prompt Name: Master Skills & Experience Summary Generator

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