sdd:plan

Refine draft task specifications into implementation-ready plans via multi-agent workflow.

Updated Feb 27, 2026
One-click install
npx skills add https://github.com/Aouei/pygame_multi --skill sdd-plan-aouei
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sdd:plan
Source: https://github.com/Aouei/pygame_multi/tree/main/.agents/skills/sdd-plan
Command: npx skills add https://github.com/Aouei/pygame_multi --skill sdd-plan-aouei

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill transforms a draft task specification into a fully planned, implementation-ready task by refining, parallelizing, and verifying each step through a multi-agent workflow.

Core Features & Use Cases

  • Parallel Analysis: Conducts research, codebase analysis, and business analysis concurrently.
  • Architecture Synthesis & Decomposition: Combines findings into an architectural overview and breaks down the task into actionable steps with risk assessments.
  • Verification & Promotion: Includes LLM-as-Judge validation at each stage and promotes the refined task to the 'todo' directory.
  • Use Case: You have a high-level idea for a new feature. Use this Skill to automatically flesh out the technical details, identify dependencies, break it into sub-tasks, and prepare it for development.

Quick Start

Refine the draft task located at '.specs/tasks/draft/add-validation.feature.md' into a fully planned implementation-ready task.

Frequently Asked Questions about sdd:plan

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

FAQPage Schema
How do I refine a draft task specification into an implementation-ready plan?▼

To refine a draft task specification, this Skill orchestrates a multi-agent workflow that performs parallel analysis, architecture synthesis, and decomposition to produce an implementation-ready plan. It validates each stage using LLM-as-Judge quality gates before promoting the task.

What is parallel analysis in task planning and decomposition?▼

Parallel analysis in task planning is the concurrent evaluation of research, codebase, and business impacts for a draft specification. This Skill uses this parallelized analysis to gather comprehensive context before synthesizing an architectural overview and breaking down the task.

How does LLM-as-Judge verification work for workflow orchestration?▼

LLM-as-Judge verification for workflow orchestration acts as an automated quality gate to validate task refinement phases. This Skill applies LLM-as-Judge checks at each stage, ensuring the decomposed and parallelized steps meet target quality standards before promotion.

Can I configure iteration limits and skip stages for task refinement?▼

Yes, you can configure iteration limits and skip stages for task refinement via command-line arguments. This Skill supports customizing target quality thresholds, human-in-the-loop checkpoints, included or skipped stages, and incremental refinement modes to control the workflow.

When do I need multi-agent workflow orchestration for task planning?▼

You need multi-agent workflow orchestration for task planning when a high-level feature idea requires automated fleshing out of technical details, dependency identification, and sub-task breakdown. It transforms draft specifications into actionable steps with risk assessments.