copilot-usage-metrics.md

title	Data available in Copilot usage metrics
allowTitleToDifferFromFilename	true
shortTitle	Copilot usage metrics data
intro	{% data variables.product.prodname_copilot_short %} usage metrics data is available through the dashboard and APIs, using a consistent set of fields to represent adoption, usage, and code generation activity.
permissions	{% data reusables.copilot.usage-metrics-permissions %}
versions	fpt ghec * *
type	reference
category	Copilot usage metrics Understand available data Track Copilot usage

The {% data variables.product.prodname_copilot_short %} 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.

• The {% data variables.product.prodname_copilot_short %} usage metrics dashboards are available at the enterprise and organization level.
• The {% data variables.product.prodname_copilot_short %} usage metrics APIs support enterprise-, organization-, and user-level records.

For guidance on how to read and interpret these metrics, see AUTOTITLE.

{% data variables.product.prodname_copilot_short %} usage dashboard metrics

These metrics appear directly in the {% data variables.product.prodname_copilot_short %} usage dashboard. These charts do not include {% data variables.copilot.copilot_cli_short %} usage.

Metric	Description
Agent adoption	Percentage of {% data variables.product.prodname_copilot_short %}-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 {% data variables.product.prodname_copilot_short %} on a given day.
Weekly active users	Number of unique users who used {% data variables.product.prodname_copilot_short %} during a seven-day window.
Total active users	Licensed users active in the current calendar month.
Language usage	Distribution of programming languages used with {% data variables.product.prodname_copilot_short %}.
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 {% data variables.product.prodname_copilot_short %} 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 last 28 days.
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 in the last 28 days.
Agent contribution	Percentage of lines of code added and deleted by agents (including edit, agent, and custom modes) in the last 28 days.
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 {% data variables.product.prodname_copilot_short %} usage metrics APIs. They provide daily records at the enterprise, organization, or user scope, depending on the metric.

Field	Description
agent_edit	Captures lines added and deleted when {% data variables.product.prodname_copilot_short %} (in agent and edit mode) writes changes directly into your files in the IDE. agent_edit is not included in suggestion-based metrics and may not populate suggestion-style fields (for example, user_initiated_interaction_count). Counts edits from custom agents as well.
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.
organization_id (API only)	Unique ID of the organization.
user_id / user_login	Unique identifier and {% data variables.product.github %} username for the user.
user_initiated_interaction_count	Number of explicit prompts sent to {% data variables.product.prodname_copilot_short %}. 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.
chat_panel_agent_mode	Captures user-initiated interactions in the chat panel with agent mode selected.
chat_panel_ask_mode	Captures user-initiated interactions in the chat panel with ask mode selected.
chat_panel_custom_mode	Captures user-initiated interactions in the chat panel with a custom agent selected.
chat_panel_edit_mode	Captures user-initiated interactions in the chat panel with edit mode selected.
chat_panel_unknown_mode	Captures user-initiated interactions in the chat panel where the mode is unknown.
code_generation_activity_count	Number of distinct {% data variables.product.prodname_copilot_short %} 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 {% data variables.product.prodname_copilot_short %} suggested to add (completions, inline chat, chat panel, etc.; excludes agent edits).
loc_suggested_to_delete_sum	Lines of code {% data variables.product.prodname_copilot_short %} 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 {% data variables.product.prodname_copilot_short %} 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 {% data variables.copilot.copilot_chat_short %} extension version detected for each user.
daily_active_cli_users	Number of unique users in the enterprise who used {% data variables.product.prodname_copilot_short %} via the CLI on a given day. This field is independent of IDE active user counts and is not included in IDE-based active user definitions. Omitted for enterprises with no CLI usage on that day.
totals_by_cli	Breakdown of CLI-specific metrics for the enterprise on a given day. Independent of IDE metrics—CLI usage is not reflected in other fields such as totals_by_ide or totals_by_feature. Omitted for enterprises with no CLI usage on that day. See {% data variables.copilot.copilot_cli_short %} metrics fields below.

{% data variables.copilot.copilot_cli_short %} metrics fields (API only)

The totals_by_cli object contains the following nested fields when CLI usage is present. These metrics are currently only available in the enterprise-level reports.

Field	Description
totals_by_cli.session_count	Number of distinct CLI sessions initiated on this day.
totals_by_cli.request_count	Total number of requests made to {% data variables.product.prodname_copilot_short %} via the CLI on this day, including both user-initiated prompts and automated agentic follow-up calls.
totals_by_cli.token_usage.output_tokens_sum	Total number of output tokens generated across all CLI requests on this day.
totals_by_cli.token_usage.prompt_tokens_sum	Total number of prompt tokens sent across all CLI requests on this day.
totals_by_cli.token_usage.avg_tokens_per_request	Average number of output and prompt tokens per CLI request, computed as (output_tokens_sum + prompt_tokens_sum) ÷ request_count.

Pull request activity fields (API only)

Important

Organization- and enterprise-level reports may show different totals due to differences in user deduplication and attribution timing. For guidance on interpreting pull request metrics across scopes, see AUTOTITLE.

These fields capture daily pull request creation, review, merge, and suggestion activity at the enterprise or organization scope, including activity performed by {% data variables.product.prodname_copilot_short %}.

Field	Description
pull_requests.total_created	Total number of pull requests created on this specific day. Creation is a one-time event. Each pull request is counted only on the day it is created.
pull_requests.total_reviewed	Total number of pull requests reviewed on this specific day. The same pull request may be counted on multiple days if it receives reviews on multiple days. Within a single day, each pull request is counted once, even if multiple review actions occur.
pull_requests.total_merged	Total number of pull requests merged on this specific day. Merging is a one-time event. Each pull request is counted only on the day it is merged.
pull_requests.median_minutes_to_merge	Median time, in minutes, between pull request creation and merge for pull requests merged on this specific day. Median is used to reduce the impact of outliers from unusually long-running pull requests.
pull_requests.total_suggestions	Total number of pull request review suggestions generated on this specific day, regardless of author.
pull_requests.total_applied_suggestions	Total number of pull request review suggestions that were applied on this specific day, regardless of author.
pull_requests.total_created_by_copilot	Number of pull requests created by {% data variables.product.prodname_copilot_short %} on this specific day.
pull_requests.total_reviewed_by_copilot	Number of pull requests reviewed by {% data variables.product.prodname_copilot_short %} on this specific day. A pull request may be counted on multiple days if {% data variables.product.prodname_copilot_short %} reviews it on multiple days.
pull_requests.total_merged_created_by_copilot	Number of pull requests created by {% data variables.product.prodname_copilot_short %} that were merged on this specific day. Each pull request is counted only on the day it is merged.
pull_requests.median_minutes_to_merge_copilot_authored	Median time, in minutes, between pull request creation and merge for pull requests created by {% data variables.product.prodname_copilot_short %} and merged on this specific day.
pull_requests.total_copilot_suggestions	Number of pull request review suggestions generated by {% data variables.product.prodname_copilot_short %} on this specific day.
pull_requests.total_copilot_applied_suggestions	Number of pull request review suggestions generated by {% data variables.product.prodname_copilot_short %} that were applied on this specific day.