trailblaze

Project Url: block/trailblaze
Introduction: AI-driven mobile testing framework.
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Trailblaze is an AI-powered UI testing framework that lets you author and execute tests using natural language.

trailblaze-with-goose-android.gif

Current Vision

Trailblaze enables adoption of AI powered tests in regular Android on-device instrumentation tests. This allows leveraging existing execution environments and reporting systems, providing a path to gradually adopt AI-driven tests at scale.

Because Trailblaze uses Maestro Command Models for UI interactions it enables a longer term vision of cross-platform ui testing while reusing the same authoring, agent and reporting capabilities.

Core Features

  • AI-Powered Testing: More resilient tests using natural language test steps
  • On-Device Execution: Runs directly on Android devices using standard instrumentation tests (Espresso, UiAutomator)
  • Custom Agent Tools: Extend functionality by providing app-specific TrailblazeTools to the agent
  • Detailed Reporting: Comprehensive test execution reports
  • Maestro Integration: Uses a custom on-device driver for Maestro to leverage intuitive, platform-agnostic UI interactions

Multi-Agent V3 Features (Mobile-Agent-v3 Inspired)

Trailblaze implements cutting-edge features from Mobile-Agent-v3 research:

Feature Description
Exception Handling Automatically handles popups, ads, loading states, and errors
Reflection & Self-Correction Detects stuck states and loops, backtracks when needed
Task Decomposition Breaks complex objectives into manageable subtasks
Cross-App Memory Remembers information across app switches for complex workflows
Enhanced Recording Captures pre/post conditions for more robust replay
Progress Reporting Real-time MCP progress events for IDE integrations

Trail & Blaze Architecture

Trailblaze's unique "blaze once, trail forever" workflow:

  • Blaze Mode: AI explores the app to achieve objectives, discovering the path dynamically
  • Trail Mode: Replay recorded actions deterministically with zero LLM cost
  • Hybrid Mode: Use recordings where available, fall back to AI when needed
┌─────────────────────────────────────────────────────────────┐
│                    First Run: BLAZE                          │
│  AI explores → Records actions → Generates .trail.yaml      │
└──────────────────────────┬──────────────────────────────────┘
                           │
                           ▼
┌─────────────────────────────────────────────────────────────┐
│                   Future Runs: TRAIL                         │
│  Replay recordings → Zero LLM cost → Fast CI/CD execution   │
└─────────────────────────────────────────────────────────────┘

Documentation at block.github.io/trailblaze

See Mobile-Agent-v3 Features Guide for detailed usage examples.

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