How well does your city match your biology?

Enter any city in the world. Groq's language model retrieves local lifestyle data — dining culture, work norms, nightlife patterns, sunlight hours — and scores it against your chronotype's biological preferences.

Groq API key required. This feature uses Groq's free API to retrieve city data. Your key is stored only in your browser. How to get a free key.

Configure your sync check

Stored in your browser only. Never sent to our servers.

Getting a free Groq API key

Groq offers a generous free tier that is more than sufficient for this feature.

Step 1
Visit console.groq.com
Create a free account — no credit card required.
Step 2
Navigate to API Keys
In the left sidebar, click "API Keys" then "Create API Key."
Step 3
Copy your key
The key starts with "gsk_". Copy it and paste it into the field above.
Step 4
Your key is stored locally
PeakBio saves your key in your browser's localStorage. It is never transmitted to our servers.

Why does your city's rhythm matter?

Chronobiologists have documented significant variation in how different cities and cultures organize time. The concept of "social zeitgebers" — social time-givers — describes how meal times, business hours, nightlife patterns, and commuting norms act as external cues that entrain your biological clock. If your internal clock is misaligned with your city's social clock, the result is a form of chronic social jetlag.

Research by Till Roenneberg's group found that social jetlag — the discrepancy between biological sleep timing and socially required sleep timing — affects roughly two-thirds of the working population to some degree. When the mismatch is large, the consequences resemble shift work: poorer metabolic health, increased cardiovascular risk markers, and reduced cognitive performance during socially required waking hours.

Cities differ considerably in their chronobiological profile. Barcelona's famous late dining culture (dinner at 9–10 PM, bars open until 3 AM) inherently favors Wolf-type chronotypes. Tokyo's precision commuter culture and early business norms align better with Lion and early Bear types. Melbourne's blend of Mediterranean café culture and outdoor lifestyle tends to suit Bears well.

The City Sync Score is not about where you should live — it is about understanding how much your current city is working with or against your biology, and what adjustments might help close the gap.

How the sync score is calculated

The algorithm compares your chronotype's ideal parameters — work start time, dinner time, sunlight preference, noise sensitivity, and nightlife compatibility — against the city's cultural profile as retrieved by the Groq language model. Five factors contribute to the final score:

  • Work schedule alignment — how closely the city's typical work start time matches your chronotype's optimal work window
  • Dining culture — whether meal times align with your digestive rhythm
  • Nightlife compatibility — whether the city's evening energy works for or against your chronotype
  • Sunlight availability — annual sunlight hours affect serotonin and melatonin regulation
  • Noise and commute stress — factors that measurably impair sleep quality

The resulting score is a rough heuristic, not a precise measurement. It is meant to prompt reflection, not dictate choices.

Your key is stored in your browser's localStorage only. PeakBio is a static website — there is no server, no database, and no analytics that could capture your key. You can verify this by checking the network requests in your browser's developer tools.
Groq's language model provides reasonable approximations based on the cultural and geographical knowledge in its training data. For major world cities, the data will generally be representative. For smaller cities, the model may extrapolate from regional norms. The score should be treated as an indicative estimate.
Yes, you can enter any place name. For very small towns, the model will likely use regional or national averages as a proxy. Results will be less precise for places with very limited data.