Features
Natural language test authoring
Self-healing tests that adapt to UI and API changes
Continuous test execution on any cadence (every minute, on push, on schedule)
Multi-surface testing: web UI, mobile, API endpoints, CLI, async workflows
CI/CD integrations with GitHub Actions and GitLab CI
First-class support for AI coding agents (Claude Code, Cursor, Codex)
Reproducible debugging artifacts: scripts, logs, screenshots, videos
Instant failure alerts via Slack, email, or PagerDuty
Dashboard to monitor test runs, pass rates, and auto-repaired tests
Prevent PR merges when tests fail via CI integration
Git + S3 context storage for durable AI agent memory (June 2026 update)
Manual test triggers for ad-hoc runs
Role-based agent assignment (PM, architect, engineer, QA)
Structured output generation (requirements, design, code)
Data Interpreter for data analysis tasks
SELA module for self-evolving agents
Multi-agent collaboration and workflow orchestration
Meta-programming support for custom agent behaviors
Modular and extensible architecture
Built-in demo projects and case studies
MIT License fully open-source
Flow orchestration for complex agent pipelines
Integration with GitHub Actions and CI/CD
Community-driven with GitHub and Discord
