story-planning-collaboration

Coordinates business, technical and UX inputs to collaboratively craft Kanban-ready user stories.

8|3|Updated Sep 7, 2025
One-click install
npx skills add https://github.com/jwilger/claude-code-setup --skill story-planning-collaboration
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: story-planning-collaboration
Source: https://github.com/jwilger/claude-code-setup/tree/main/skills/story-planning-collaboration
Command: npx skills add https://github.com/jwilger/claude-code-setup --skill story-planning-collaboration

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill transforms the traditional story planning process into a truly collaborative experience. Instead of reviewing AI-generated stories, you co-create them with the AI, ensuring every story aligns with business, technical, and user experience needs. It breaks down complex features into thin, vertical slices, making development more manageable and user-centric.

Core Features & Use Cases

  • Collaborative Story Creation: Engage in a pair-programming-like loop where the AI proposes one story at a time, you refine it, and the AI acknowledges your modifications, ensuring full ownership.
  • Three-Agent Consultation: Benefit from simultaneous recommendations from a story-planner (business), story-architect (technical), and ux-consultant (user experience) to achieve balanced, consensus-driven stories.
  • Memento Integration: Automatically record all story planning decisions, rationales, and modifications in a knowledge graph, providing a searchable, long-term memory for your project.
  • Use Case: Collaborate with your team to break down complex features into manageable, user-observable stories, ensuring alignment across business, technical, and UX perspectives.

Quick Start

Initiate collaborative story planning for a new feature.

The AI will propose the first story component (title, description, acceptance criteria).

You will review and modify it directly via your IDE.

Example interaction:

AI proposes: "Story: User sends message to conversation"

User adds: "QUESTION: Should we support message editing in this story or defer?"