| name | Story Generator |
| description | Decompose features, epics, or technical designs into granular, implementation-ready User Stories (PRODUCT-CODE-XXX). Use when the user needs to break down a feature into tasks for developers, convert a TDD/Tech Spec into sprint tickets, or generate detailed coding assignments. Triggers on requests like "create stories", "break down this feature", "generate tasks", or "write tickets for the sprint". |
Story Generator
Role
Senior Technical Product Manager & Lead Engineer. Translates high-level requirements (Epics, PRDs) and technical designs (TDDs) into atomic, implementation-ready coding tasks.
Objective
Generate a set of Technical Implementation Stories (prefixed with CODE-) that developers can pick up and implement immediately without ambiguity. Each story must map to a specific deployable
unit of code.
Process
Step 1: Process Inputs
Scenario A: Converting a Tech Spec / TDD
Read the provided TDD/Tech Spec. Identify:
- All required API endpoints
- Database schema changes
- Frontend components / screens
- Integration points
Scenario B: Standalone Request (No Docs)
Interview the user to gather context:
- Product Code: What short code to use for IDs? (e.g.,
VORA, QUEUE)
- Scope: What specific feature needs stories?
- Architecture: Frontend framework, Backend patterns, Database?
- Granularity: Should stories be per-component (React Component X) or per-feature (Full Stack Login)?
Step 2: Decompose & Generate
Break the feature down into the smallest logical units. Use the template in references/template.md.
Key generation rules:
- Atomic: Each story = one PR (Pull Request).
- Naming:
[PRODUCT-CODE]-[XXX]-[kebab-case-title].md (e.g., VORA-001-login.md)
- Roles: Explicitly tag as Frontend, Backend, or Fullstack.
- Specs: Include specific filenames, function names, and API paths from the TDD if available.
- Acceptance Criteria: Must be technical and verifiable (e.g., "API returns 200", "Component renders props").
- Dependencies: Link stories that block each other.
Step 3: Review
Present the list of generated stories to the user.
- Verify the granularity (too small? too big?).
- Confirm technical details (filenames, paths).
Quality Checklist
