GitHub’s organization-level Code Quality Trends tab shows how the total number of open findings has changed across repositories over a selected 7-, 14-, or 30-day period. It can help you spot where counts are moving, but it does not show when individual findings were introduced or fixed. Treat it as a short-term signal to investigate—not proof, by itself, that code quality improved or worsened.
What the Trends tab shows
GitHub announced the organization-level Trends tab on August 19, 2026. Its chart summarizes open-finding counts across repositories where Code Quality is enabled. You can view findings grouped by health score or severity, along with the current total and the net change since the beginning of the selected period. Repository tables rank where finding counts changed most. GitHub describes the feature as showing how code quality has changed across repositories over time.
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This differs from the Health tab’s point-in-time view: Trends adds a historical series of daily snapshots. The series is about the count of findings that remain open, not a record of each finding’s lifecycle. A falling total does not identify which findings were resolved, and a rising total does not reveal when or why each finding appeared.
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GitHub’s August 19, 2026 announcement says the feature is generally available to GitHub Team and GitHub Enterprise Cloud organizations with Code Quality enabled, including Enterprise Cloud with data residency. GitHub Enterprise Server is not supported according to that announcement. These are dated eligibility details; check GitHub’s current documentation or your organization’s available settings if access is decisive.
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What appears in the dashboard also depends on permissions. Organization owners can see all repositories where Code Quality is enabled. Other members see only repositories for which they can view findings; GitHub documents a maximum of 3,000 repositories. Consequently, a member’s organization-level total may not cover the same repositories as an owner’s view.
How to open the dashboard and find changes
- Open your organization page and choose Security and quality.
- Under Insights, select Code quality, then open Trends.
- Choose a period: 7, 14, or 30 days. Review the open-finding chart, its current total, and net change for that period.
- Use the available filters to narrow findings by reliability or maintainability score, standard or AI findings, topic, team, visibility, or custom organization properties.
- Inspect the repository rankings to identify which repositories account for the largest count changes, then investigate those repositories’ findings and context.
GitHub documents the navigation, visibility behavior, filters, and repository limit in its guide to exploring Code Quality results in an organization.
How to interpret the trend responsibly
Check what is included
Before comparing totals, confirm that you have the same access scope and filters. A change in visible repositories, team, topic, visibility, score, or finding type changes the set being counted. For meaningful comparisons between teams or periods, keep those choices consistent.
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The history is built from daily snapshots, and a day may have no point if no analysis ran. If snapshots have only recently begun, the available history may be shorter than the selected window. A missing point is not evidence that the count was zero or unchanged.
Look beyond the total
Findings are not interchangeable: their severity and health-score context matter, and the aggregate count does not explain the cause of a change. Use the chart to find a signal, then examine repository-level findings and their severity or score before drawing conclusions. A smaller count can be useful evidence, but alone it does not establish that maintainability or reliability improved.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Where it fits alongside engineering metrics
Code Quality Trends measures open code findings. It is not a software delivery or service-stability metric. DORA’s Core Model is a research-derived guide for practitioners, while its Four Keys project covers deployment frequency, lead time for changes, time to restore services, and change failure rate. Those measures can provide organizational context, but they do not measure the same thing as code findings. Four Keys is designed for projects with deployments; a release-only library may not fit its data model.
Organizations that need customized engineering measures can also explore the source-available projects listed in DORA’s resources, including Apache DevLake, which collects, analyzes, and visualizes engineering data. Such tools are alternatives for building broader or tailored metrics, not equivalent implementations of GitHub’s Code Quality count.
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