What problem does it solve?
It helps you reliably execute a multi-phase implementation plan by coordinating specialist subagents and enforcing evidence-based progress, verification, and quality checks.
Core Features & Use Cases
- Phased orchestration: Breaks work into ordered phases and dispatches fresh subagents where context is large or unclear.
- Evidence requirements: Ensures each subagent reports completion with proof (commands run, outputs produced, and files changed) before moving forward.
- Built-in guardrails: Adds verification, anti-pattern checks, and code quality review, and only commits after verification passes with explicit approval.
- Use case: Turn an AI-generated implementation plan into a safely executed workflow for a codebase change, such as updating IoTProject firmware or server logic, without skipping validation.
Quick Start
Ask your AI to run the do plan for your previously created plan and require each phase to include verification evidence before proceeding.