speckit-adlc-product-implement

Convert Product Decision Records into a unified PRD.md via a multi-agent DAG workflow.

Updated Apr 21, 2026
One-click install
npx skills add https://github.com/chaimt/GarminShabbatMode --skill speckit-adlc-product-implement
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: speckit-adlc-product-implement
Source: https://github.com/chaimt/GarminShabbatMode/tree/main/.cursor/skills/speckit-adlc-product-implement
Command: npx skills add https://github.com/chaimt/GarminShabbatMode --skill speckit-adlc-product-implement

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Product teams often struggle to synthesize scattered Product Decision Records into a single, actionable Product Requirements Document. This Skill provides a repeatable, DAG-based process to convert PDRs into a comprehensive PRD.

Core Features & Use Cases

  • DAG-driven PRD generation from PDRs
  • Multi-phase workflow (Plan, Execute, Summarize)
  • Traceability: PDRs underpin every section and decision
  • Resumability and stateful progress across sessions
  • Unified PRD output at PRD.md with canonical storage

Quick Start

Provide a complete PRD from the current PDRs using the configured DAG plan.

Frequently Asked Questions about speckit-adlc-product-implement

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate a unified PRD from scattered Product Decision Records?

You can generate a unified PRD from scattered Product Decision Records by using a multi-agent DAG workflow that transforms PDRs organized by feature areas into a cohesive Product Requirements Document with full traceability.

What is the best way to maintain PDR traceability in a generated PRD?

Maintaining PDR traceability in a generated PRD involves using a DAG-driven process that ensures PDRs underpin every section and decision, ultimately storing accepted decisions at a canonical location within the final PRD.md output.

How does a DAG workflow handle conflict resolution when synthesizing a PRD?

A DAG workflow handles conflict resolution during PRD synthesis by managing the process across planning, execution, and summary phases, resolving inconsistencies between scattered PDRs before generating the final unified document.

Can I resume PRD generation across multiple sessions if the process is interrupted?

Yes, you can resume PRD generation across multiple sessions because the DAG workflow supports resumability and stateful progress, managing phase-based state to preserve your work between planning, execution, and summary stages.

Do I need to organize Product Decision Records by feature area before PRD synthesis?

Yes, you need to organize Product Decision Records by feature area before PRD synthesis, as the DAG workflow applies to projects with PDRs structured this way to effectively execute planning, execution, and summary phases.

What are the limitations of using a multi-agent DAG for product requirements generation?

The multi-agent DAG approach requires PDRs to be pre-organized by feature area and depends on phase-based state management, meaning it is not suited for unstructured product notes lacking formal decision records.