Last sync: 4 min ago·GitLab ·Jira ·Sentry ·Microsoft 365 All sources healthy
Activity intelligence
Engineering activity over the last 14 days compared to the previous 14 days.
14 days8 people
Total commits
247
↓ 12% vs prev
MRs merged
34
↑ 6% vs prev
Reviews given
89
↓ 22% vs prev
Active days avg
8.4
≈ prev period
Team Health Signal
68
↓ 4 vs prev
1
14-day snapshot — Key engineering metrics compared to the previous period. These aren't just counters — drops in reviews and activity signal feed the overload and disengagement detectors automatically. Leave periods are excluded from all calculations. No manual rule-setting needed.
Team Health Signal pattern
Daily team average across active members (leave periods excluded). Sustained drops trigger the disengagement detector.
⬇ Declining
May 17May 20May 23May 26May 30
2
Team Health Signal pattern — A sustained downward trend over 14 days is an early warning for disengagement. The system detects this and automatically flags at-risk team members. Leave periods are excluded from the calculation. You don't have to watch graphs — the engine watches for you.
Workload distribution
Ranked by activity signal. Outliers on either end trigger overload and disengagement detections. Leave periods excluded.
Name
Activity level
Δ prev
Commits
Reviews
Trend
Status
SJSara Jensen
94
↑ +38
87
14
Attention needed
TBTom Brooks
78
↑ +4
42
23
Healthy
EPEmma Park
72
≈ 0
38
19
Healthy
AKAlex Kim
54
↓ −18
12
4
Watch
LWLin Wei
51
↓ −3
31
11
Healthy
MCMarcus Chen
—
on leave
—
—
On leave
3
Workload distribution — Sara is the outlier on the high end. Alex is trending down. Marcus is on approved leave — his row is greyed out and excluded from detection logic for the leave period. A healthy team sits in the middle. Go to the People page to click on a person and see their full operational profile.