rai-story-design

Design lean story specifications with YAML frontmatter and acceptance criteria.

Updated Feb 4, 2026
One-click install
npx skills add https://github.com/fcastrillo/carbtrack-ai --skill rai-story-design
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: rai-story-design
Source: https://github.com/fcastrillo/carbtrack-ai/tree/main/.claude/skills/rai-story-design
Command: npx skills add https://github.com/fcastrillo/carbtrack-ai --skill rai-story-design

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Lean, repeatable story design specs that balance human readability with AI alignment, enabling faster, safer feature planning.

Core Features & Use Cases

  • Systematic frontmatter-driven design: ensures a consistent starting point for every story.
  • AI-aligned specification: emphasizes WHAT, WHY, and measurable acceptance criteria to guide code generation and reviews.
  • Reusable templates: references the lean-feature-spec-v2 format to streamline planning and reduce risk.

Quick Start

Prompt the AI with the lean story design template before /rai-story-plan to ground integration decisions.

Frequently Asked Questions about rai-story-design

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

FAQPage Schema
How do I write story specifications for AI-aligned feature development?

To write story specs for AI code generation, apply a structured template enforcing YAML frontmatter, a design body, runnable examples, risk guidance, and measurable acceptance criteria to ensure AI alignment.

What is a lean story design template and when do I need one?

A lean story design template is a repeatable specification format balancing human readability with AI alignment, needed before planning complex stories with architectural scope or cross-cutting concerns to ground integration decisions.

How do I structure acceptance criteria for AI code generation?

Structure acceptance criteria for AI code generation by defining measurable conditions within a lean specification body, ensuring the WHAT and WHY are explicitly stated to guide code reviews and automated generation.

Can I use this lean story spec format for complex architectural stories?

Yes, you can use this lean story spec format for complex architectural stories, as it is specifically applied before planning to ground integration decisions when architectural scope or cross-cutting concerns exist.

What is the best way to align AI code generation with human-readable feature specs?

The best way to align AI code generation with human-readable feature specs is to drive planning with a frontmatter-driven design doc that explicitly defines the WHAT, WHY, and measurable acceptance criteria.

Why does my AI-generated code deviate from the planned feature design?

AI-generated code deviates from planned feature design when story specs lack structured design bodies, runnable examples, and clear acceptance criteria, failing to provide the necessary AI alignment for code generation.