• Firefighting — The team is mostly reacting to urgent issues.
• Consolidation — The team is stabilizing what was built and reducing pressure.
• Expansion — The team is adding new capabilities with healthy delivery.
• Steady — The team is operating at a stable, predictable pace.
• Maintenance — The team is focused on upkeep and small improvements.
• Unknown — There is not enough data to classify the current state.

Additional detail

• Firefighting: Team is spending energy reacting to instability (more rework, more pressure).
• Consolidation: Team is reducing complexity and risk while still delivering; stabilizing what exists.
• Expansion: Team is growing system scope and complexity in a controlled way.
• Steady: No major shift; delivery and system pressure are relatively stable.
• Maintenance: Mostly upkeep and incremental improvements, with little structural change.
• Unknown: Not enough data to classify the current state.

Structural fragility shows how dependent delivery is on a small number of people. High fragility means key progress depends on too few contributors. Low fragility means delivery is healthier and less dependent on individual heroes.

Work momentum shows whether delivery pace is improving, stable, or slowing down over time, compared with the previous period.

New vs Existing reflects how much of the work is adding new surface versus modifying recently changed code. It is derived from change patterns (churn), not a literal count of brand new lines.

Team signals provide a quick health view of delivery quality and execution stability in the selected period versus the previous one.

• Complexity — How demanding the delivered work is.
• Rework — How much effort is spent revisiting recent work.
• Technical risk — How exposed the team is to delivery problems if current patterns continue.
• Core / Critical / Churn / Hotspot — Supporting indicators that show concentration, instability, and pressure areas.

Key insights are short highlights that explain what changed in team execution and why it matters for delivery.

• Concentration insights — Show where difficulty, rework, or churn is concentrated, so you can spot dependency and bottleneck risk.
• Shift insights — Show whether work is becoming more distributed or more concentrated compared with the previous period.
• Risk insights — Call out patterns that can hurt delivery reliability, such as rising risk during expansion or hard work without enough test support.
• Mode insights — Explain why the current operating state was detected and what it suggests about team behavior.

Execution cost shows how much effort the team needs to produce results compared with the previous period.

• Rework — More effort is going into fixing or redoing work.
• Technical risk — More effort is needed because changes carry higher delivery risk.
• Difficulty — Work is becoming harder or easier to complete.
• Churn — Teams are changing the same areas repeatedly, which raises effort.

These are related but different signals:

• Churn — How much code is being re-touched after change. High churn means instability in implementation decisions or frequent adjustment in the same code paths.
• Hotspot — How concentrated delivery is in files that are touched repeatedly. High hotspot means pressure is accumulating in a small set of files, increasing dependency and bottleneck risk.
• Rework — How much effort is spent revisiting recent work instead of extending it. High rework means forward progress is being replaced by correction loops.

How to interpret when these signals rise in different combinations:

• Use churn to detect instability in change behavior.
• Use hotspot to detect where delivery risk is concentrating structurally.
• Use rework to detect execution inefficiency and avoidable rework loops.
• Read all three together before taking action; any single metric alone can be noisy.

The developers table shows each contributor's delivery load, risk profile, and work quality signals for the selected period.

• Activity and output — Shows who is active and how much work each person is delivering.
• Difficulty and risk — Highlights who is handling harder work and where execution risk may be building.
• Integration and rework — Shows whether work is flowing cleanly or coming back as rework.
• Concentration signals — Helps detect over-dependence on a few contributors.

Column reference