ql-plan

Convert a PRD into a machine-readable quantum.json DAG.

24|Updated Feb 16, 2026
One-click install
npx skills add https://github.com/andyzengmath/quantum-loop --skill ql-plan
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ql-plan
Source: https://github.com/andyzengmath/quantum-loop/tree/main/skills/ql-plan
Command: npx skills add https://github.com/andyzengmath/quantum-loop --skill ql-plan

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Converts a Product Requirements Document (PRD) into a machine-readable quantum.json DAG that guides autonomous development execution.

Core Features & Use Cases

  • Builds a dependency-aware plan by translating PRDs into granular 2-5 minute tasks organized in a DAG.
  • Generates execution metadata and wiring notes so that planners, executors, and verifiers stay synchronized across the plan lifecycle.
  • Supports validation, wiring, and DAG verification to prevent scope creep or misalignment across the planning and execution phases.

Quick Start

Invoke the ql-plan skill after creating a spec to generate quantum.json, define granular tasks, and wire dependencies for execution.

Frequently Asked Questions about ql-plan

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

FAQPage Schema
How do I convert a PRD into a dependency-aware execution plan?

To convert a PRD into a dependency-aware execution plan, you translate structured specs into granular 2-5 minute tasks organized within a machine-readable DAG. This ensures proper wiring and dependency tracking across planning, executing, and verifying phases for autonomous software execution.

What is a dependency DAG and how does it help automate software execution?

A dependency DAG is a directed acyclic graph that organizes granular 2-5 minute tasks by their execution dependencies. It drives autonomous software execution by generating machine-readable metadata that keeps planners, executors, and verifiers synchronized throughout the plan lifecycle.

Do I need a structured spec to generate a machine-readable DAG?

Yes, you need a structured spec like a Product Requirements Document to generate a machine-readable DAG. The spec-to-plan conversion requires structured input to accurately define granular tasks, dependency wiring, and execution metadata for autonomous development.

Can I validate task dependencies and prevent scope creep during automated planning?

Yes, you can validate task dependencies and prevent scope creep during automated planning by applying DAG verification checks. This mechanism ensures proper wiring between stories and alignment across planning, executing, and verifying phases to prevent misalignment.

Why should I break down project specs into 2-5 minute tasks for automation?

Breaking down project specs into 2-5 minute tasks for automation ensures granular control and precise dependency wiring within the DAG. This fine-grained approach generates accurate execution metadata required to synchronize planners, executors, and verifiers for end-to-end automation.