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Argent

An agentic toolkit to control, debug, and profile iOS and Android apps. Made by Software Mansion.

B 76/100 GitHub score ? This grade is derived from GitHub signals, not user votes. Open for the full breakdown.
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01 / Summary

About Argent.

Argent lets an AI coding agent run, inspect, debug, and profile apps on its own, so it can see what happened on screen and keep working in the same session. It reaches iOS Simulators, Android emulators and physical devices, TVs (Apple TV, Android TV, and Fire TV), and Electron or Chromium desktop and web apps. At its core it is a set of agent skills plus an MCP server that connects coding harnesses to those targets.

For interaction, the agent taps, swipes, types, presses hardware buttons, uses a D-pad on TVs, and drives mouse and keyboard on desktop, navigating by coordinates from accessibility trees. Multi-step interaction sequences run in a single call, and Argent reports back after every interaction. Paths can be recorded once and replayed deterministically as a reproduction or smoke test, and visual regression diffs a baseline against a live capture with OCR and font awareness.

For debugging, it attaches a debugger, reads console logs, evaluates JavaScript expressions, explores the native view hierarchy and the React component tree, and reads network requests and payloads at both the JavaScript fetch layer and the native network layer. For performance, it records React and native iOS profiles together through Hermes, React DevTools, Xcode Instruments, and Perfetto, traces slow React commits down to native stack frames, and detects UI hangs, render cascades, and memory leaks. React Native apps can be built, launched, and iterated on without extra setup.

  • Device control: tap, swipe, gesture, type, and hardware buttons on simulators, emulators, and physical devices
  • TV and desktop targets: D-pad control on Apple TV, Android TV, and Fire TV, and mouse and keyboard on Electron or Chromium apps
  • Batched interactions: multi-step sequences in one call, with on-screen feedback after each step
  • Recorded flows: record a path once and replay it deterministically as a repro or smoke test
  • Visual regression: OCR- and font-aware diffs between a baseline and a live capture
  • Runtime debugging: debugger attach, console logs, JavaScript evaluation, and native and React component trees
  • Network inspection: requests and payloads at both the JavaScript fetch layer and the native layer
  • Profiling: Hermes, React DevTools, Xcode Instruments, and Perfetto profiles for renders, CPU hotspots, and hangs
  • Issue detection: UI hangs, render cascades, and memory leaks, with re-queryable profiling sessions
  • Skills and MCP server: agent skills and an MCP server that connect coding harnesses to devices

02 / Discussion CREDIBILITY-GATED

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04 / Build

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