
Improved accuracy and coverage in Copilot usage metrics reports
Quick Answer
GitHub has enhanced the Copilot usage metrics API with three key improvements, including the addition of suggested lines of code reporting.
Quick Take
These updates aim to provide more accurate and comprehensive usage metrics for developers utilizing GitHub Copilot, ensuring better insights into user engagement and feature effectiveness.
Key Points
- Copilot CLI now reports suggested lines of code for better insights.
- Improvements enhance the completeness of usage metrics reports.
- Developers will benefit from more accurate engagement data.
- Three key updates were implemented to the metrics API.
📖 Reader Mode
~3 min readWe’ve made three improvements to the Copilot usage metrics API that make its reports more complete and accurate: GitHub Copilot CLI now reports suggested lines of code, users seen only through server-side telemetry now have their IDE identified, and AI credit consumption is now attributed more completely.
What’s new
- GitHub Copilot CLI now reports suggested lines of code. CLI activity now contributes to the
loc_suggested_to_add_sumandloc_suggested_to_delete_sumfields, which previously always reported0for the CLI. Code generation counts are also more accurate on newer CLI versions, where suggested and accepted edits are de-duplicated so the same edit isn’t counted twice. - IDE identified for more users. Users who were previously visible only through server-side telemetry now have their IDE and plugin versions surfaced in
totals_by_ide, sototals_by_idereflects more of your Copilot users. - AI credits attributed more accurately. We fixed two issues that caused some users to show
0.0AI credits despite real usage. First, AI credit consumption not associated with an organization was being dropped. It’s now attributed to the correct organization or enterprise. Second, users seen only through server-side telemetry were not being matched to their billing data. Their consumption is now included. Thanks to these updates,ai_credits_usedtotals more completely reflect actual consumption.
Why this matters
- More complete coverage: Surfacing CLI suggested lines of code and identifying IDEs for server-side-only users means fewer blind spots in who is using Copilot and how.
- More trustworthy consumption data: Correcting AI credit attribution means
ai_credits_usedtotals more accurately reflect what your users actually consumed. - Consistent analysis across surfaces: As Copilot usage spans the IDE, CLI, and server-side surfaces, these updates keep the reports aligned with real activity.
Important notes
- These metrics are available to enterprise administrators and organization owners who have access to Copilot usage metrics through the REST API.
- Copilot CLI reports suggested lines of code from CLI version
1.0.57onward. Code generation de-duplication applies from version1.0.64onward. Between1.0.57and1.0.64, code generation activity may be slightly undercounted for the CLI. - AI credit totals for previously-missed usage will increase as a result of these attribution fixes—values that were already reported are unchanged.
Visit the Copilot usage metrics API documentation to learn more.
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— Originally published at github.blog
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