[Calendar Load] Calendar Load Report — Week of 2026-06-09

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📅 Calendar Load Report — Week of 2026-06-09

⚠️ This report uses fixture data. Configure GOOGLE_CALENDAR_TOKEN to run against live calendar data.
Signal-only report. Data surfaces patterns; humans decide what (if anything) to change.

Summary

Contributor	Meeting Hours	Days w/ Deep Work Block	Fragmentation Flags	Status
Alex Chen	5.5 hrs	3/5 days	Mon	🟢 OK
Priya Nair	7.5 hrs	2/5 days	Tue	🟡 Watch
Sam Wilson	10 hrs	2/5 days	Mon, Wed	🔴 High
Jordan Mills	8.5 hrs	2/5 days	Tue, Wed	🔴 High
Casey Rivera	6 hrs	4/5 days	—	🟢 OK

Status key: 🟢 OK (≥3 days with deep work block, load < 15h) | 🟡 Watch (1–2 days with deep work block, or load 12–15h) | 🔴 High (0 days with deep work block, or load > 15h, or 3+ fragmented days)

Signals this week

🔴 No deep work blocks found:

• [contributor name]: zero 90-minute gaps on any day this week. Longest available window: N min on [day].

🟡 High fragmentation days:

• Priya Nair on Tuesday: 4 meetings spread across 6 hours (fragmentation score: 4.0). Longest gap: 30 min.

📊 Healthiest schedule:

• Alex Chen: 5.5 hours of meetings clustered in the morning. 3 days with 90+ min deep work blocks. Longest block: 150 min on Friday.

Meeting type breakdown

This week, standups and reviews dominated the schedule, primarily in the mornings, with scattered 1:1s in the afternoons.

Suggested conversation starters

• Sam Wilson attended 5 meetings on Monday with no gap over 60 minutes. Is that typical for his workload?
• Consider whether clustering 1:1s for Priya Nair could allow for more focused time later in the week.

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Auto-generated by the Calendar Load Report workflow. Data source: Google Calendar (fixture mode if credentials not configured). [Research basis: Kreamer & Rogelberg 2024 — meeting dispersion, not quantity, predicts productivity loss.]

Generated by Calendar Load Report · 21.8 AIC · ⌖ 8.74 AIC · ⊞ 15.8K · ◷

• expires on Jun 19, 2026, 6:13 PM UTC