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Trailblaze

https://github.com/block/trailblaze
Visit block.github.io
Category
Developer Tools
Rank
No. 789Tools index
Listed in
#3 Generate and improve tests
Pricing
Open Source
Type
TOOL
Builder
block
GitHub
310 stars
Latest release
v2026.09.02
Date

About

AI-driven UI testing framework for Android — describe what you want to test in plain language and let the agent drive the app.

What it does

Trailblaze turns an exploratory device session into a readable test artifact. It captures intent alongside concrete UI actions, stores platform-specific recordings in one YAML trail, then replays those recordings deterministically in CI without calling an LLM.

Why it's ranked here

The design connects agent-led exploration to conventional regression testing unusually well. Android, iOS, and web share one authoring model while retaining native accessibility, semantics, and DOM capabilities. Replayable artifacts and detailed traces make the result more accountable than an opaque autonomous test run.

What's good

Recorded intent gives failed selectors useful repair context. Replay remains deterministic by default, while optional self-healing handles small interface drift. Reports combine screenshots, hierarchy snapshots, tool calls, transcripts, video, and performance timelines. Teams can also add typed TypeScript commands for app-specific operations.

Tradeoffs

Agent-driven steps require a configured LLM provider, and useful visual flows need a model with image input and tool calling. GitHub-release installation requires Java 17 or newer. Video reporting needs an optional dependency. Maestro compatibility covers interactions but excludes JavaScript, subflows, and environment variables.

How to use it well

Use it when a coding agent already participates in development and you want exploratory device work to become committed cross-platform regression tests. Build reusable domain commands for repeated flows, then replay recordings in CI. It does not replace a coding agent or provide a hosted SaaS testing platform.

Technical notes+

README.md defines the CLI-first capture and replay workflow, Homebrew and release installation, bundled agent skill, desktop app, and unified trail artifact. docs/architecture.md describes a Kotlin and Gradle multi-module system using coroutines, serialization, Compose Multiplatform, Ktor, platform drivers, and recorded YAML execution. docs/CLI.md documents shell commands plus an MCP server, persistent device sessions, deterministic runs, reports, profiling, and validation. docs/tools.md specifies TypeScript, pure-YAML, and Kotlin-backed extension mechanisms. docs/llms.md exposes library integration through Koog's LLMClient and TrailblazeRunner. docs/maestro.md states that only part of Maestro's command model is implemented.

Observed

License
Apache 2.0
Primary language
Kotlin, including Kotlin Multiplatform modules
Install surface
Homebrew formula or GitHub release installer; release installation requires Java 17 or newer
Interfaces
CLI, MCP server, desktop application, and Kotlin library integration
Platforms
Android, iOS, and web
Test artifact
One YAML trail can hold natural-language intent and platform-specific recordings
Replay model
Recorded trails replay deterministically without an LLM by default
Custom tools
Supports TypeScript scripted tools, pure-YAML composed tools, and Kotlin-backed tools

Read from README.md, docs/CLI.md, docs/llms.md, docs/index.md, docs/tools.md, docs/logging.md, docs/maestro.md, docs/reports.md, docs/support.md, docs/profiling.md, docs/trailmaps.md, docs/architecture.md, docs/configuration.md, docs/adding_a_model.md.

What it can do

  • Generate UI test automation from natural language descriptions

    Plain language test description → Automated UI test script

  • Execute automated UI tests on Android applications

    Test script and target Android app → Test execution results and status

  • Navigate Android app interfaces autonomously

    Test objectives and target app UI → Simulated user interactions and navigation paths

  • Interpret user intent for mobile app testing

    Natural language testing requirements → Structured test plan and actions

  • Drive mobile app interactions without manual scripting

    Testing goals and Android application → Automated touch, swipe, and input actions

Tags

ui-testingandroidai-agentkotlin

Tech Stack

KotlinJavaScriptHTMLTypeScriptShellPython

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Editorially curated, with community endorsements as a secondary signal. Corrections welcome.