Données disponibles dans les métriques d’utilisation de Copilot

The Copilot usage metrics dashboard and APIs display and export data using a consistent set of fields. This reference lists all available metrics and describes how to interpret their values in both dashboard visuals and NDJSON or API exports. To retrieve this data programmatically, see REST API endpoints for Copilot usage metrics.

For guidance on how to read and interpret these metrics, see GitHub Copilot usage metrics.

Copilot usage dashboard metrics

These metrics appear directly in the Copilot usage dashboard.

Metric	Description
Agent adoption	Percentage of Copilot-licensed active users who tried an agent in the current calendar month.
Average chat requests per active user	Average number of chat requests per active user.
Code completions (suggested/accepted)	Total number of inline code suggestions shown and accepted.
Code completion acceptance rate	Percentage of suggestions accepted by users.
Daily active users	Number of unique users who used Copilot on a given day.
Weekly active users	Number of unique users who used Copilot during a seven-day window.
Total active users	Licensed users active in the current calendar month.
Language usage	Distribution of programming languages used with Copilot.
Language usage per day	Daily breakdown of languages used.
Model usage	Distribution of AI models used for chat.
Model usage per day	Daily breakdown of chat model usage.
Model usage per chat mode	Model usage by Copilot feature (Ask, Edit, Agent).
Model usage per language	Distribution of languages broken down by model.
Most used chat model	The most frequently used chat model in the current calendar month.
Requests per chat mode	Number of chat requests by mode (Ask, Edit, Agent).

Code generation dashboard metrics

These metrics appear in the code generation dashboard and provide a breakdown of how code is being generated across user-initiated and agent-initiated activity. All values are derived from lines of code (LoC) added or deleted in the IDE.

Metric	Description
Lines of code changed with AI	Total lines of code added and deleted across all modes during the current calendar month.
Agent contribution	Percentage of lines of code added and deleted by agents (including Edit, Agent, and custom modes) during the current calendar month.
Average lines deleted by agent	Average number of lines automatically deleted by agents on behalf of active users during the current calendar month.
Daily total of lines added and deleted	Total number of lines added to and deleted from the codebase across all modes for each day.
User-initiated code changes	Lines suggested or manually added by users through code completions and chat panel actions (insert, copy, or apply).
Agent-initiated code changes	Lines automatically added to or deleted from the codebase by agents on behalf of users across Edit, Agent, and custom modes.
User-initiated code changes per model	User-initiated lines of code, grouped by model used in the IDE.
Agent-initiated code changes per model	Agent-initiated lines of code, grouped by model performing the agent actions.
User-initiated code changes per language	User-initiated lines of code, grouped by programming language.
Agent-initiated code changes per language	Agent-initiated lines of code, grouped by programming language.

API and export fields

These fields appear in the exported NDJSON reports and in the Copilot usage metrics APIs. They provide granular daily records for each user in the enterprise.

Field	Description
agent_edit	A dedicated bucket in the API and reports. Captures lines added and deleted directly by Copilot Agent and Edit mode. These are not included in suggested metrics, since agent edits don’t follow a simple suggestion to acceptance flow.
report_start_day / report_end_day	Start and end dates for the 28-day reporting period.
day	Calendar day this record represents.
enterprise_id	Unique ID of the enterprise or organization.
user_id / user_login	Unique identifier and GitHub username for the user.
user_initiated_interaction_count	Number of explicit prompts sent to Copilot. Only counts messages or prompts actively sent to the model. Does not include opening the chat panel, switching modes (for example, Ask, Edit, or Agent), using keyboard shortcuts to open the inline UI, or making configuration changes.
code_generation_activity_count	Number of distinct Copilot output events generated. Includes: All generated content, including comments and docstrings. Multiple blocks: Each distinct code block from a single user prompt counts as a separate generation. Note: This metric is not directly comparable to user_initiated_interaction_count, since one prompt can produce multiple generations.
code_acceptance_activity_count	Number of suggestions or code blocks accepted by users. Counts: All built-in accept actions, such as “apply to file,” “insert at cursor,” “insert into terminal,” and use of the Copy button. Does not count: Manual OS clipboard actions (for example, Ctrl+C). Granularity: Each acceptance action increments the count once, regardless of how many code blocks were generated by the initial prompt.
loc_suggested_to_add_sum	Lines of code Copilot suggested to add (completions, inline chat, chat panel, etc.; excludes Agent edits).
loc_suggested_to_delete_sum	Lines of code Copilot suggested to delete (future support planned).
loc_added_sum	Lines of code actually added to the editor (accepted completions, applied code blocks, agent/edit mode).
loc_deleted_sum	Lines of code deleted from the editor (currently from Agent edits).
totals_by_ide	Breakdown of metrics by IDE used.
totals_by_feature	Breakdown of metrics by Copilot feature (e.g., inline chat, chat panel).
totals_by_language_feature	Breakdown combining language and feature dimensions.
totals_by_model_feature / totals_by_language_model	Model-specific breakdowns for chat activity (not completions).
last_known_ide_version / last_known_plugin_version	The most recent IDE and Copilot Chat extension version detected for each user.