Features
Centralize engineering playbook with versioning
Distribute playbook artifacts to any AI agent (Copilot, Cursor, Claude, etc.)
Pre-commit rule violation detection and automatic rewrite
MCP server support for agent context injection
Drift detection and repair to maintain alignment
RBAC for playbook authorship and distribution
Audit trail for all technical decisions
Self-hosted deployment with air-gap support
Scales across monorepos, microservices, and enterprise codebases
SonarQube integration for code quality reports
Introducing Skills for governing AI coding agent workflows (June 2026)
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
