npx skills add https://github.com/subsy/ralph-tui --skill ralph-tui-prdSKILL.md
Ralph TUI PRD Generator
Create detailed Product Requirements Documents optimized for AI agent execution via ralph-tui.
The Job
- Receive a feature description from the user
- Ask 3-5 essential clarifying questions (with lettered options) - one set at a time
- Always ask about quality gates (what commands must pass)
- After each answer, ask follow-up questions if needed (adaptive exploration)
- Generate a structured PRD when you have enough context
- Output the PRD wrapped in
[PRD]...[/PRD]markers for TUI parsing
Important: Do NOT start implementing. Just create the PRD.
Step 1: Clarifying Questions (Iterative)
Ask questions one set at a time. Each answer should inform your next questions. Focus on:
- Problem/Goal: What problem does this solve?
- Core Functionality: What are the key actions?
- Scope/Boundaries: What should it NOT do?
- Success Criteria: How do we know it's done?
- Integration: How does it fit with existing features?
- Quality Gates: What commands must pass for each story? (REQUIRED)
Format Questions Like This:
1. What is the primary goal of this feature?
A. Improve user onboarding experience
B. Increase user retention
C. Reduce support burden
D. Other: [please specify]
2. Who is the target user?
A. New users only
B. Existing users only
C. All users
D. Admin users only
This lets users respond with "1A, 2C" for quick iteration.
Quality Gates Question (REQUIRED)
Always ask about quality gates - these are project-specific:
What quality commands must pass for each user story?
A. pnpm typecheck && pnpm lint
B. npm run typecheck && npm run lint
C. bun run typecheck && bun run lint
D. Other: [specify your commands]
For UI stories, should we include browser verification?
A. Yes, use dev-browser skill to verify visually
B. No, automated tests are sufficient
Adaptive Questioning
After each response, decide whether to:
- Ask follow-up questions (if answers reveal complexity)
- Ask about a new aspect (if current area is clear)
- Generate the PRD (if you have enough context)
Typically 2-4 rounds of questions are needed.
Step 2: PRD Structure
Generate the PRD with these sections:
1. Introduction/Overview
Brief description of the feature and the problem it solves.
2. Goals
Specific, measurable objectives (bullet list).
3. Quality Gates
CRITICAL: List the commands that must pass for every user story.
## Quality Gates
These commands must pass for every user story:
- `pnpm typecheck` - Type checking
- `pnpm lint` - Linting
For UI stories, also include:
- Verify in browser using dev-browser skill
This section is extracted by conversion tools (ralph-tui-create-json, ralph-tui-create-beads) and appended to each story's acceptance criteria.
4. User Stories
Each story needs:
- Title: Short descriptive name
- Description: "As a [user], I want [feature] so that [benefit]"
- Acceptance Criteria: Verifiable checklist of what "done" means
Each story should be small enough to implement in one focused AI agent session.
Format:
### US-001: [Title]
**Description:** As a [user], I want [feature] so that [benefit].
**Acceptance Criteria:**
- [ ] Specific verifiable criterion
- [ ] Another criterion
Note: Do NOT include quality gate commands in individual story criteria - they are defined once in the Quality Gates section and applied automatically during conversion.
Important:
- Acceptance criteria must be verifiable, not vague
- "Works correctly" is bad
- "Button shows confirmation dialog before deleting" is good
- Each story should be independently completable
5. Functional Requirements
Numbered list of specific functionalities:
- "FR-1: The system must allow users to..."
- "FR-2: When a user clicks X, the system must..."
Be explicit and unambiguous.
6. Non-Goals (Out of Scope)
What this feature will NOT include. Critical for managing scope.
7. Technical Considerations (Optional)
- Known constraints or dependencies
- Integration points with existing systems
- Performance requirements
8. Success Metrics
How will success be measured?
9. Open Questions
Remaining questions or areas needing clarification.
Writing for AI Agents
The PRD will be executed by AI coding agents via ralph-tui. Therefore:
- Be explicit and unambiguous
- User stories should be small (completable in one session)
- Acceptance criteria must be machine-verifiable where possible
- Include specific file paths if you know them
- Reference existing code patterns in the project
Output Format
CRITICAL: Wrap the final PRD in markers for TUI parsing:
[PRD]
# PRD: Feature Name
## Overview
...
## Quality Gates
...
## User Stories
...
[/PRD]
File naming: The TUI will save to ./tasks/prd-[feature-name].md
Example Conversation Flow
User: Create a PR
...