Michał Pierzchała
a67c72c211
* fix(ios): pin tap-outcome corroboration probes to the baseline's backend The recorded-failure screens are exactly where the capture plan flips between XCTest and private-AX (the penalty boundary), so #1605's same-backend requirement failed closed right where XCTest tap false negatives actually happen: the baseline was captured via private-AX under penalty, the probe came back via tree, and a landed tap surfaced as XCTEST_RECORDED_FAILURE. In the AppControlBench bsky-16 run this fired four times, each sending the model into a re-observe/retry spiral. The comparison stays same-backend by design (backends are not comparable views of a screen); instead the probe is now CAPTURED the way its baseline was: a new internal preferredBackend option (never CLI-exposed) threads daemon -> runner, and a private-AX-preferred capture takes the exact penalized route — privateAX-first plan, 'deferred' verdict, no degradation warning, no settle budget reset. Live-verified on the deterministic repro (Bluesky drawer-menu press under penalty, seeded bench feed): errored with the backend-mismatch diagnostic before, corroborates as landed after, with no mismatch phase in the request diagnostics. Daemon tests cover pinned and unpinned baselines end to end through the dispatch context; the Swift plan gate is a pure function with an executed in-bundle test (added to the ios.yml regression list). * style: oxfmt * fix: exclude raw baselines from corroboration and prove the pin end to end (review) Raw baselines could not be pinned: the raw diagnostic plan keeps tree-first error propagation by contract and is never rerouted by the penalty or the preferred backend, so preserving 'raw: true' on the probe recreated exactly the backend-mismatch false failure this PR removes. Corroboration now declines raw baselines up front (they are diagnostics, not evidence baselines) with a regression pinning that no probe capture is dispatched at all. The wire is now regression-proven at every hop: a dispatch-level test drives dispatchCommand with the context flag and asserts the emitted RunnerCommand carries preferredBackend (red if handleSnapshotCommand or the interactor stops forwarding); the injected-transport test asserts the interactor's snapshot payload both ways; and a runner unit test decodes the wire JSON, projects it through the extracted snapshotOptions(from:), and composes it with the plan rule — pinned regular plan defers to privateAX-first, RAW plan stays untouched. Executed on-simulator; added to the ios.yml regression list.
agent-device
Let your coding agent verify its changes in the running app.
agent-device lets coding agents inspect, control, and verify apps on iOS, Android, tvOS, Android TV, Amazon Vega OS TV through the Vega Virtual Device (VVD), web, macOS, and Linux. Agents can read token-efficient accessibility snapshots where supported, find elements by ref or selector, run device actions, and save evidence for review. Initial Vega OS support is VVD-only and covers discovery, app lifecycle, and complete TV-remote control; physical Fire TV, capture, and selector backends remain unsupported.
Your coding agent or QA tool reads each result and chooses the next command. agent-device runs the command and saves evidence when asked.
agent-device uses the inspect-act-verify process from Vercel's agent-browser for mobile, TV, and desktop apps. Basic --platform web support runs agent-browser in the same session and replay system.
Quick start
Install the CLI and check setup. It requires Node.js 22.12 or newer; web automation requires Node.js 24 or newer. See Installation for target requirements.
npm install -g agent-device@latest
agent-device doctor
agent-device help workflow
Run agent-device doctor yourself before handing the CLI to an agent. The installed CLI help defines current behavior. agent-device help workflow links to guides for debugging, replay, React Native profiling, and other tasks.
Add a contact in the built-in iOS Contacts app:
# Start a session.
agent-device open Contacts --platform ios
# Inspect the screen. The example below shows the output; refs vary.
agent-device snapshot -i
# @e2 [button] "Add"
# Use the ref and wait for the UI to settle.
agent-device press @e2 --settle
# The diff includes:
# + @e7 [text-field] "First name"
agent-device fill @e7 "Ada" --settle
# The next diff shows changed values and current refs:
# - @e7 [text-field] "First name"
# + @e14 [text-field] "Ada"
# = @e15 [text-field] "Last name"
# Capture evidence and close the session.
agent-device screenshot ./contact-form.png
agent-device close
Use refs only from the latest output. Do not assume an earlier @eN still identifies the same element. After a command with --settle, use the refs in its diff. Take another snapshot only if the diff omits what you need.
Snapshots use the app's accessibility tree. Clear labels, roles, and test IDs make agent runs more reliable. Use screenshots and videos as evidence or when accessibility data is poor. Use refs and selectors for actions and assertions when you can.
What agents can do
- Inspect app state through accessibility snapshots, refs, selectors, and React Native component trees.
- Act on visible UI by tapping or pressing elements, filling fields, scrolling, making gestures, waiting, asserting state, and handling alerts.
- Diagnose failures with screenshots, video, logs, traces, network data, performance samples, crash details, and React profiles.
- Repeat workflows by saving working steps as
.adscripts for local use or CI. Export strict Maestro YAML when needed.
See Commands for the commands and evidence each target supports.
Next steps
- Set up your agent: run the CLI from Cursor, Codex, Claude Code, Windsurf, or another agent terminal. See AI Agent Setup for skills, rules, MCP tools, and setup for each client.
- Try the sample app: clone the repo and run the bundled Expo test app. Quick Start covers a guided run with screenshots, replay, and performance data.
- Build repeatable tests: use Replay & E2E to repeat tests. Use Debugging & Profiling to find bugs.
Articles and videos
Articles
- Build an AI QA agent for Expo apps with EAS Workflows
- Agent Device: iOS & Android automation for AI agents
- Building mobile QA agents with Vercel Eve
- How we optimized Agent Device for mobile app automation
Videos
- Verifying mobile apps with agent-device
- Using agent-device in an AI coding workflow
- Cloud agents that test mobile apps on real devices
Where to run agent-device
| Path | Best for | Start with |
|---|---|---|
| Local | Trying commands and debugging apps on simulators, emulators, physical devices, macOS, and Linux. | Follow the Quick Start. |
| CI/CD | Automated pull request and merge validation with replay scripts and captured artifacts. | Try the EAS workflow template. GitHub Actions template coming soon. |
| Cloud / remote | Linux runners, managed devices, and remote jobs. | Use Agent Device Cloud, set a remote profile with Commands, or contact Callstack for team QA. |
How it works
agent-device keeps device state in sessions. It sends commands to XCTest on iOS and tvOS, ADB and the snapshot helper on Android, Vega CLI/VDA on the Vega Virtual Device, a local helper on macOS, and AT-SPI on Linux.
Node.js apps can use the typed client or public subpaths. agent-device/android-adb provides the Android ADB provider interface, helpers for logcat, the clipboard, the keyboard, and apps, and port reverse management.
FAQ
What is agent-device?
agent-device is a command-line tool that lets coding agents inspect, control, and verify apps and save evidence for review. It supports iOS, Android, TV, web, macOS, and Linux.
Does it work with React Native, Expo, Flutter, and native apps?
Yes. agent-device supports native iOS and Android apps, plus React Native, Expo, and Flutter apps on supported targets. The commands and evidence vary by target.
How is it different from Appium, Detox, or Maestro?
With agent-device, an agent reads app state and chooses each command at run time. Teams use Appium, Detox, and Maestro to write and maintain test suites. agent-device can complement them by saving its runs as .ad scripts or exporting them as strict Maestro YAML.
Can agent-device run in CI?
Yes. Record a run as an .ad script, replay it locally or in CI, and save screenshots, logs, and other artifacts for review. See Replay & E2E or start with the EAS workflow template.
Who uses agent-device?
Teams and developers at Callstack, JPMorgan Chase, Expensify, Shopify, Kindred, Total Wine & More, LegendList, HerLyfe, App & Flow, and others use agent-device.
Documentation
Contributing
See CONTRIBUTING.md.
Made at Callstack
agent-device is open source under the MIT license. Visit agent-device.dev or contact Callstack.