GitHub Copilot Usage API Names Custom Skills, Agents, and MCP Servers: How to Read the Report
Named entries improve adoption analysis, while client versions and telemetry can still undercount usage
Key takeaways
GitHub updated the Copilot usage metrics API on October 22, 2026, so customer-defined skills, agents, MCP servers, slash commands, and plugins can appear by configured name instead of being grouped entirely under other or custom. Each totals_by_* list now includes as many as 25 entries per record, up from five. This article helps administrators turn the change into a reliable adoption report. It covers required Copilot CLI and SDK versions, a naming review before reports are shared, one-day and 28-day comparisons, and a reconciliation check against known pilots. It also explains why historical days, path-like names, outdated clients, and blocked telemetry can still undercount activity. The metrics are useful for trends and enablement, not exact billing.
By ENHE AI · 2026-10-24 · AI-assisted drafting and editorial checks.
Direct answer: validate coverage before comparing adoption trends
The new fields can show which internal skills, agents, or MCP servers are used, but interpretation depends on client versions, naming, and telemetry coverage. Start with a known pilot, confirm its expected name appears, and only then expand the report.
Keep both one-day and 28-day views, plus client-version distribution and uncovered surfaces. A missing entry does not prove zero use, and interaction_count is not a direct measure of time saved or business output.
Confirmed field and entry-count changes
Enterprise and organization reports now show configured names in totals_by_skill, totals_by_custom_agent, totals_by_mcp, totals_by_slash_cmd, and totals_by_plugin. Each list can include up to 25 entries per record, compared with five previously.
Remaining activity beyond the limit is still grouped into a trailing other entry. The calculation of interaction_count and distinct_*_use_count is unchanged, so finer labels do not change the underlying count definitions.
Entry point, version requirements, naming review, and expected result
Read per-user one-day and 28-day reports and aggregated reports from the Copilot usage metrics API. Prompt mode, the Copilot app, and ACP integrations require Copilot CLI 1.0.97 or later; the Copilot SDK requires version 1.0.21 or later.
Standardize internal names without sensitive details or file paths. The expected result is a named pilot whose active dates broadly match pilot records. If it remains under other, inspect path-like naming, outdated clients, and blocked telemetry.
Why it matters: trends can guide enablement, not billing or performance decisions
GitHub explicitly warns that client telemetry can undercount, while earlier history remains under other or custom. Use the report for adoption trends, enablement needs, and long-unused tools—not as the sole basis for billing, individual performance, or forced retirement.
FAQ
Why are old reports not backfilled with names?
Names begin with report days processed after the release; earlier days remain under other or custom.
Does every built-in IDE chat report these names?
No. Built-in IDE chat telemetry does not report the names; distinguish SDK-based agent experiences from built-in chat.
Related tools and reading
These pages support the same task, workflow, or risk boundary.
- Claude and Codex agent activity API
- Copilot IDE usage-metric attribution fix
- Copilot impact-dashboard ROI boundaries
Conclusion
Validate names, versions, and dates against a known pilot before using the report for trend and enablement decisions. Do not present client telemetry as exact billing or individual performance.
What this means for everyday users
GitHub explicitly warns that client telemetry can undercount, while earlier history remains under other or custom. Use the report for adoption trends, enablement needs, and long-unused tools—not as the sole basis for billing, individual performance, or forced retirement.
Related tutorials
[[zh]][[/zh]][[en]]Review a public website[[/en]]
SearchScope SEO/GEO
[[zh]][[/zh]][[en]]Access and usage guide[[/en]]
AI Prompt Management System | 418 Bilingual Prompts for Writing, SEO and AI Creation
High-Frequency AI Prompts for Work, Learning, and Teaching guide
High-Frequency AI Prompts for Work, Learning, and Teaching
Related reading
GitHub Copilot Impact Dashboard Adds an ROI View
On August 7, 2026, GitHub added a Potential return on investment section to the Copilot impact dashboard. The view compares adoption phases and shows average cost per developer, pull-request output, and merge-rate signals. It is useful for asking whether spending and workflow adoption deserve a closer review, but it is not a financial audit or proof that Copilot caused a business result. A defensible first review fixes the organization and time window, reconciles AI-credit usage and active developers, samples pull-request quality and rework, and separates tool metrics from delivery and business outcomes. Teams should avoid ranking individuals on one number or expanding budgets before the measurement definition is stable.
GitHub Copilot Usage Metrics Adds Agent-App Activity
GitHub announced on August 7, 2026 that the Copilot Usage Metrics API now reports activity from third-party agent apps. Enterprise, organization, enterprise-user, and organization-user reports can expose the activity in one-day and 28-day windows. The new totals_by_3rd_party_agent data includes a stable agent_id and a display name that may change; the identifier should be the join key. This gives administrators a finer view of cost, permissions, and workflow adoption, but it does not automatically explain business value. Start with a read-only sample, reconcile time zones, pagination, and overlapping windows, then associate agent activity with AI credits, members, repositories, and permission changes before changing budgets or access.
GitHub Fixes Missing Copilot Agent Metrics and Lists Required IDE Updates
GitHub said on October 6, 2026 that some IDE versions moved Copilot agent sessions to the Copilot SDK without identifying the originating IDE. As a result, agent activity and agent lines-of-code metrics were omitted from reports, while some activity was attributed to Copilot CLI. VS Code 1.139.0 and later contain the fix; Visual Studio, JetBrains IDEs, Eclipse, and Xcode were scheduled to receive fixed releases between October and November. Historical activity on affected versions cannot be recovered after updating, and billing was not affected. This guide shows administrators how to inventory IDE versions, mark the reporting gap, update clients, compare post-update dashboard and API data, and avoid treating an instrumentation decline as proof that developers stopped using Copilot.
From Chat Boxes to Personal AI Companions: AI Assistants Are Entering the Desktop Execution Era
AI assistants are moving from answering questions toward continuing real tasks. AI agents, MCP tool ecosystems, personal memory, and local workbenches are pushing this shift together. For users, the real value is not another chat box, but less repeated context setup and more continuity from thinking to doing.
GitHub Copilot Impact Dashboard Adds Industry Comparisons: How to Read the Median and Top Decile
GitHub added an Industry comparison section to the Copilot impact dashboard on October 22, 2026. Eligible enterprises and standalone organizations can opt in to compare agent-first or multi-agent adoption and pull-request merge-rate leverage with aggregated participating peers. When enough peers participate, scores are placed against a 28-day median and, as the group grows, a top-decile reference. This article explains how to decide whether to opt in and how to avoid overreading the result. It covers company-size and industry groups, fallback to broader peer groups when samples are small, regional separation for data-residency customers, daily refreshes, and 30-day deletion of aggregated benchmarks. The comparison is context for planning, not a complete industry census or employee ranking.
Amazon Polly Upgrades Generative Speech: Validate 14 New Voices Without Breaking Existing Apps
Amazon Polly upgraded its Generative engine on October 22, 2026, adding 14 voices across nine locales and making generative Hindi and Finnish generally available. Existing voice names and API calls remain unchanged, so applications do not need a code migration, but generated audio can still change. This article gives creators, course teams, contact-center operators, and accessibility teams a reversible acceptance test. It uses one multilingual script to compare pronunciation, pauses, latency, loudness, and fallback behavior before increasing traffic. It also separates the larger voice catalog from a key limitation: generative voices still do not provide speech marks, so workflows that synchronize captions, highlighting, or animation must keep a compatible engine or another timing source.