
EAS Update Insights
FreeMonitor the health of your EAS updates from the CLI.
Free · Opens the source repo
What EAS Update Insights does
EAS Update Insights provides a command-line interface for developers to assess the performance and health of their published EAS updates. By utilizing this skill, users can obtain crucial metrics such as crash rates, install counts, unique user numbers, payload sizes, and the distribution of embedded versus over-the-air (OTA) users for each update channel. This functionality is essential for monitoring the success of app updates and ensuring a smooth user experience. The insights are derived from the same data that powers the Expo dashboard, allowing for a seamless transition from web-based monitoring to terminal commands.
The skill is particularly useful for teams that need to keep track of how their updates are performing in real-time. Developers can quickly answer questions about the health of their latest release, compare the performance of different updates, and make informed decisions about future rollouts. The CLI commands allow for both human-readable output and machine-readable JSON formats, making it easy to integrate into automated workflows or CI/CD pipelines.
To use the skill, developers must have the eas-cli installed and be logged into their Expo account. The commands available include querying insights for specific update groups, viewing detailed metrics, and listing recent updates. Each command is designed to provide a comprehensive overview of the update's performance, enabling users to detect issues early and respond accordingly. The skill is particularly valuable for post-publish monitoring and regression detection, ensuring that updates do not introduce new problems for users.
While EAS Update Insights offers robust aggregate data, it does not provide per-user crash details or device-level reporting, making it less suitable for scenarios where granular user data is required. This skill is best utilized in environments where teams need to maintain a high-level overview of update performance without delving into individual user metrics.
When to use it
Use EAS Update Insights when you need to evaluate the performance of your app updates, including crash rates and user engagement metrics.
When not to use it
Avoid using this skill if you require detailed per-user crash reports or device-level insights, as it focuses on aggregate data only.
What you can build with it
Post-Publish Monitoring
After releasing an update, use this skill to track its performance metrics and ensure it meets your quality standards.
Rollout Health Assessment
Evaluate the health of your app updates to determine if any changes negatively impact user experience.
Comparative Analysis of Updates
Compare the performance of different updates to identify trends in user engagement and stability.
How to install EAS Update Insights
View source1. Install with the skills CLI
npx skills add expo/skills/eas-update-insights --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by expoEAS Update Insights
EAS service - costs apply. Insights cover updates published through EAS Update, a paid Expo Application Services product with free-tier limits. Update delivery and the data behind these commands count against your plan's EAS Update usage. Review https://expo.dev/pricing.
Query the health of published EAS Update directly from the CLI: launches, failed launches, crash rates, unique users, payload size, the embedded-vs-OTA user split per channel, and the most popular updates per runtime version. The data is the same data that powers the update and channel detail pages on expo.dev; these commands expose it in the terminal in human and JSON form.
When to use this skill
Use this when the user wants to assess the health or adoption of a published EAS Update: crash rates, install counts, unique users, bundle size, or the split between embedded and OTA users on a channel.
Example prompts:
- "How is the latest update doing?"
- "Is the latest update healthy?"
- "Is the new release crashing more than the last one?"
- "How many users are on the latest update vs the embedded build?"
- "Which update is most popular on production right now?"
- "How big is our update bundle?"
Also fits: post-publish rollout monitoring and regression detection.
Don't use when the user needs per-user crash detail or device-level reporting; this skill only exposes aggregate EAS metrics.
Prerequisites
eas-cliinstalled (npm install -g eas-cli).- Logged in:
eas login. - For
channel:insights: run from an Expo project directory (the command resolves the project ID fromapp.json).update:insightsonly needs a login.
Commands at a glance
| Command | Purpose |
|---|---|
eas update:list | Discover recent update groups, their group IDs, and branch names |
eas update:insights <groupId> | Per-platform launches, failed launches, crash rate, unique users, payload size, daily breakdown |
eas update:view <groupId> --insights | Update group details + the same metrics appended |
eas channel:insights --channel <name> --runtime-version <version> | Embedded/OTA user counts, most popular updates, cumulative metrics for a channel + runtime |
All of these support --json --non-interactive for programmatic parsing.
Discovering IDs
Before querying insights for an update group, you need its group ID. Use eas update:list with either --branch <name> (updates on that branch) or --all (updates across all branches). Always pass --json --non-interactive when running non-interactively; without a branch/--all flag the command will otherwise prompt for a branch selection:
# Latest group id across all branches
eas update:list --all --json --non-interactive | jq -r '.currentPage[0].group'
# Latest group id on a specific branch
eas update:list --branch production --json --non-interactive | jq -r '.currentPage[0].group'
The JSON response has a currentPage array with one entry per update group (both platforms of the same publish are collapsed into one entry):
{
"currentPage": [
{
"branch": "production",
"message": "\"Fix checkout crash\" (1 week ago by someone)",
"runtimeVersion": "1.0.6",
"group": "03d5dfcf-736c-475a-8730-af039c3f4d06",
"platforms": "android, ios",
"isRollBackToEmbedded": false
}
]
}
Entries also carry codeSigningKey and rolloutPercentage, but only when those features are in use for the group (undefined values are omitted from the JSON output).
When called with --branch <name>, the response also includes name (the branch name) and id (the branch ID) at the top level.
eas update:insights <groupId>
Shows launches, failed launches, crash rate, unique users, launch asset count, and average payload size for a single update group, broken down per platform (iOS, Android), plus a daily breakdown of launches and failures.
Basic use
eas update:insights 03d5dfcf-736c-475a-8730-af039c3f4d06
Flags
| Flag | Description |
|---|---|
--days <N> | Look back N days. Default: 7. Mutually exclusive with --start/--end. |
--start <iso-date> / --end <iso-date> | Explicit time range, e.g. --start 2026-04-01 --end 2026-04-15. |
--platform <ios|android> | Filter to a single platform. Omit to see all platforms in the group. |
--json | Machine-readable output. Implies --non-interactive. |
--non-interactive | Required when scripting. |
JSON output shape
Top level: groupId, timespan (start, end, daysBack), and platforms[] with one entry per platform the group was published to. Each platform entry has updateId, totals (uniqueUsers, installs, failedInstalls, crashRatePercent), payload (launchAssetCount, averageUpdatePayloadBytes), and a daily[] time series of { date, installs, failedInstalls }.
For the complete schema and field reference, see references/update-insights-schema.md.
Fields that matter for health assessment:
platforms[].totals.crashRatePercent, computed asfailedInstalls / (installs + failedInstalls) * 100. Zero when there are no installs.platforms[].totals.installsanduniqueUsersgive the adoption signal.platforms[].dailyis a time series, useful for spotting a sudden spike in failures.
Errors
Could not find any updates with group ID: "<id>"— group doesn't exist or you lack access.Update group "<id>" has no ios update (available platforms: android)—--platform ioswas used but the group wasn't published for iOS.EAS Update insights is not supported by this version of eas-cli. Please upgrade ...— the server deprecated a field the CLI relies on. Runnpm install -g eas-cli@latest.
eas update:view <groupId> --insights
Extends the standard update:view output with the same per-platform insights, inline.
# Human-readable
eas update:view 03d5dfcf-... --insights
eas update:view 03d5dfcf-... --insights --days 30
# JSON: wrapped as { updates: [...], insights: {...} }
eas update:view 03d5dfcf-... --json --insights
Without --insights, update:view behaves exactly as before — no JSON shape change for existing consumers. The --days / --start / --end flags only apply when --insights is set; passing them alone errors.
eas channel:insights --channel <name> --runtime-version <version>
Shows, per channel, how many users are on the embedded build vs over-the-air updates and which updates are pulling the most traffic. Must be run from an Expo project directory.
Basic use
eas channel:insights --channel production --runtime-version 1.0.6
Flags
| Flag | Description |
|---|---|
--channel <name> | Required. The channel name (e.g. production, staging). |
--runtime-version <version> | Required. Match exactly what was published. Check runtimeVersion values in update:list. |
--days <N> | Look back N days. Default: 7. |
--start / --end | Explicit time range, like update:insights. |
--json / --non-interactive | Machine-readable output. |
JSON output shape
Top level: channel, runtimeVersion, timespan, embeddedUpdateTotalUniqueUsers, otaTotalUniqueUsers, mostPopularUpdates[] (each with rank, groupId, message, platform, totalUniqueUsers), cumulativeMetricsAtLastTimestamp[], plus chart-shaped uniqueUsersOverTime and cumulativeMetricsOverTime objects with labels and datasets.
For the complete schema and field reference, see references/channel-insights-schema.md.
Fields that matter:
embeddedUpdateTotalUniqueUsersis the count of users running the embedded (binary-bundled) build.mostPopularUpdates[]is updates ranked bytotalUniqueUsers. Caveat: this is the top-N the server returns;otaTotalUniqueUsersis a sum of that list and may undercount total OTA reach if more than top-N updates are active.uniqueUsersOverTimeandcumulativeMetricsOverTimeare daily data series for charting.
Errors
Could not find channel with the name <name>— typo or wrong account.- "No update launches recorded" in the table / empty
mostPopularUpdatesin JSON — no OTA update has been launched for that channel + runtime yet. Usually means the channel is still serving the embedded build only.
Common workflows
Verify the update I just published is healthy
# 1. Grab the latest publish on production
GROUP_ID=$(eas update:list --branch production --json --non-interactive \
| jq -r '.currentPage[0].group')
# 2. Give it some adoption time (minutes to hours), then check crash rate
eas update:insights "$GROUP_ID" --json --non-interactive \
| jq '.platforms[] | {platform, installs: .totals.installs, crashRate: .totals.crashRatePercent}'
Compare the crashRate across platforms and against previous releases; sudden spikes or asymmetric behaviour (iOS spiking while Android is flat, or vice versa) is the signal to investigate.
Compare adoption between two channels
for channel in production staging; do
echo "--- $channel ---"
eas channel:insights --channel "$channel" --runtime-version 1.0.6 --json --non-interactive \
| jq '{
channel,
embedded: .embeddedUpdateTotalUniqueUsers,
ota: .otaTotalUniqueUsers,
topUpdate: .mostPopularUpdates[0]
}'
done
Detect a rollout regression in the last 24 hours
eas update:insights "$GROUP_ID" --days 1 --json --non-interactive \
| jq '.platforms[] | select(.totals.crashRatePercent > 1)'
Summarize group metrics for release notes
eas update:view "$GROUP_ID" --insights --days 30
Human-readable group details plus 30 days of launches/failures per platform — suitable for pasting into a changelog or incident review.
Output tips
- Pipe JSON through
jq; payloads are structured for easy filtering. --jsonimplies--non-interactive, but passing both is explicit and scripting-friendly.- Dates in
daily[].dateare UTC ISO timestamps; the human-readable table renders them asYYYY-MM-DD(UTC). - The CLI table labels say "Launches" / "Crashes" while JSON uses
installs/failedInstalls. Same field, different display name.
Limitations
- Unique users across platforms may double-count users who run the same publish on both iOS and Android. The same caveat applies to
otaTotalUniqueUsersin channel insights, which is a sum overmostPopularUpdates. - Fresh publishes may show zeros for a short period while the metrics pipeline catches up.
- Installs are downloads, not launches: the
installs/ "Launches" field counts users who downloaded the manifest and launch asset. A confirmed run only registers on the user's next update check (typically up to 24h later, depending on the app's update policy). So metrics lag the real-world state slightly. - Crashes are self-reported:
failedInstalls/ "Crashes" counts updates that errored during install/launch and were reported on the next update check. Crashes that don't trigger an update request (e.g. process kill before recovery) won't appear.
Submitting Feedback
If you encounter errors, misleading or outdated information in this skill, report it so Expo can improve:
npx --yes submit-expo-feedback@latest --category skills --subject "eas-update-insights" "<actionable feedback>"
Only submit when you have something specific and actionable to report. Include as much relevant context as possible. If an AI agent repeatedly failed or the user had to take over an Expo task, load the expo-skill-feedback skill and follow its eval-candidate flow instead of reusing the command above.
Frequently asked questions about EAS Update Insights
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