Features
Autonomous test generation and execution via AI agents
Specialized QA agents for unit, integration, and end-to-end testing
Integration with Claude Code for agentic workflows
Composable skills for testing across SDLC stages
Open-source framework with community contributions
Supports custom agent creation and skill development
Git repository structure for easy forking and deployment
Lightweight CLI-based setup
Built-in test coverage analysis
Parallel test execution orchestration
Live knowledge graph from code, commits, issues, and docs
Feasibility analysis: flags buildable vs risky items
Technical design document generation grounded in service topology
Impact assessment maps services, APIs, and dependencies across repos
Auto-scoping epics into Jira/Linear stories with effort estimates
One-shot production code generation grounded in service patterns
AI code reviews with cross-repo impact analysis
Production issue triage via MCP
Conversational learning from Slack and Jira
Accelerated onboarding via system-level Q&A in coding agents
Create Jira tickets and merge requests from Slack
MCP server for integration with Cursor, Claude Code, Codex
On-prem or cloud deployment
No code storage or model training
