Millennial Crowd: Policy Impact Exploration
When to Activate
Use this skill when the user requests:
- •Policy impact analysis on Australian millennials
- •Testing how different demographic groups would react to policy changes
- •Exploring millennial perspectives on political issues
- •Focus group-style feedback on ideas, policies, or narratives
- •User explicitly mentions "millennial crowd", "millennial focus group", or "policy personas"
What It Does
Runs a policy question through 10 data-grounded Australian millennial personas in parallel. Each persona responds from their specific circumstances:
| Persona | Profile |
|---|---|
| Sophie Chen | Inner-city tech worker, priced out of housing |
| Matt Thompson | Outer suburbs tradie with mortgage stress |
| Bec O'Brien | Regional ED nurse, sees health system strain |
| Jordan Nguyen | Gig economy worker, crushed by HECS |
| Daniel Costa | Small business cafe owner |
| Priya Sharma | Canberra public servant |
| Ryan Mitchell | FIFO mining worker |
| Ash Williams | Disengaged warehouse worker |
| Jess Taylor | Stay-at-home mum, left career for kids |
| Tom Fitzgerald | Elder millennial who built wealth early |
Invocation
bash
python3 ~/.claude/skills/millennial-crowd/millennial_crowd.py "Your policy question here"
Options
bash
# List all personas python3 ~/.claude/skills/millennial-crowd/millennial_crowd.py --list # Increase parallel workers (faster, but more API load) python3 ~/.claude/skills/millennial-crowd/millennial_crowd.py -w 5 "Question here" # Simple output (no rich formatting) python3 ~/.claude/skills/millennial-crowd/millennial_crowd.py --simple "Question here"
Example Queries
- •"How would you react to a $50k HECS debt forgiveness cap?"
- •"What do you think about abolishing negative gearing?"
- •"Would you support a 4-day work week mandate?"
- •"How would higher immigration affect your life?"
- •"What's your reaction to the Voice referendum result?"
Output
Returns individual responses from each persona, grounded in their:
- •Income and housing situation
- •HECS debt status
- •Political lean
- •Lived experiences (COVID, housing crisis, health system)
- •Personal circumstances and internal tensions
Limitations
- •These are synthetic personas, not real survey data
- •Useful for hypothesis generation, not prediction
- •Should prompt real consultation, not replace it