Enables pipeline-driven task management for AI coding agents, with stage-gated workflows, dependency tracking, artifact versioning, and multi-agent collaboration.
Implements a structured development workflow for LLM-based coding with feature clarification, PRD generation, phased development, and task tracking. Guides LLMs through organized feature development from requirements gathering to completion with document storage and progress monitoring.
Enables spec-driven development workflows with AI assistants, providing tools for managing specification lifecycles, task dependencies, code navigation, testing, and automated reviews through a unified CLI and MCP interface.
Orchestrates complete agile development workflows from product requirements to QA testing through role-based stages (PO → Architect → SM → Dev → Review → QA). Manages workflow state, generates role-specific prompts, and saves artifacts while integrating with multiple AI engines for comprehensive project delivery.
Enables AI coding assistants to drive spec-driven development through slash-command workflows for planning, exploring, implementing, updating, and finalizing changes, with local daemon and project registry support.