ralph-tui-prd

subsy/ralph-tui · updated Apr 8, 2026

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$npx skills add https://github.com/subsy/ralph-tui --skill ralph-tui-prd
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summary

Generate detailed Product Requirements Documents optimized for AI agent execution via ralph-tui task orchestration.

  • Guides users through adaptive clarifying questions to understand feature scope, goals, and quality requirements
  • Produces structured PRDs with user stories, functional requirements, and explicit quality gates for automated conversion to beads issues or prd.json
  • Emphasizes small, independently completable user stories with verifiable acceptance criteria suitable for singl
skill.md

Ralph TUI PRD Generator

Create detailed Product Requirements Documents optimized for AI agent execution via ralph-tui.


The Job

  1. Receive a feature description from the user
  2. Ask 3-5 essential clarifying questions (with lettered options) - one set at a time
  3. Always ask about quality gates (what commands must pass)
  4. After each answer, ask follow-up questions if needed (adaptive exploration)
  5. Generate a structured PRD when you have enough context
  6. 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 PRD for adding dark mode to the TUI

Assistant: I'll help you create a PRD for dark mode. Let me ask a few questions:

  1. What is the primary goal? A. Reduce eye strain for long sessions B. Match system theme preference C. Provide visual customization D. Other

  2. Should the setting persist? A. Yes, save to config file B. No, session only C. Follow system preference

User: 1A, 2A

Assistant: Great! A couple more questions:

  1. Which components need dark mode support? A. All TUI components B. Only the main execution view C. Main view + settings D. Other

  2. What quality commands must pass for each story? A. pnpm typecheck && pnpm lint B. npm run typecheck && npm run lint C. bun run typecheck D. Other: [specify]

  3. For UI stories, include browser verification? A. Yes, use dev-browser skill B. No, automated tests sufficient

User: 3A, 4A, 5A

Assistant: Perfect, I have enough to generate the PRD.

[PRD]

PRD: Dark Mode for Ralph TUI

Overview

Add dark mode support to ralph-tui to reduce eye strain during long orchestration sessions. The feature will apply to all TUI components and persist the user's preference in the config file.

Goals

  • Provide a comfortable viewing experience in low-light environments
  • Persist theme preference across sessions
  • Apply consistent styling to all TUI components

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

User Stories

US-001: Add theme configuration

Description: As a user, I want to set my preferred theme (light/dark) so that it persists across sessions.

Acceptance Criteria:

  • Add theme field to .ralph-tui.yaml schema
  • Support values: "light", "dark", "system"
  • Default to "light" for backwards compatibility

US-002: Create dark theme color palette

Description: As a user, I want a soft-contrast dark theme that's easy on the eyes.

Acceptance Criteria:

  • Define dark palette with gray tones (not pure black)
  • Ensure sufficient contrast ratios (WCAG AA)
  • Colors work well for all UI states (selected, hover, disabled)

US-003: Apply theme to TUI components

Description: As a user, I want all TUI components to respect my theme preference.

Acceptance Criteria:

  • Header component uses theme colors
  • Task list uses theme colors
  • Detail panels use theme colors
  • Progress bar uses theme colors
  • Dialogs use theme colors

US-004: Add theme toggle in settings

Description: As a user, I want to toggle themes from within the TUI settings.

Acceptance Criteria:

  • Theme option visible in settings view
  • Changes apply immediately without restart
  • Changes persist to config file

Functional Requirements

  • FR-1: Theme setting must be readable from .ralph-tui.yaml
  • FR-2: Theme must apply on TUI startup
  • FR-3: Theme changes in settings must apply immediately
  • FR-4: All text must maintain readability in both themes

Non-Goals

  • System theme auto-detection (future enhancement)
  • Custom color schemes beyond light/dark
  • Per-component theme overrides

Technical Considerations

  • Use existing OpenTUI theming capabilities if available
  • Consider creating a ThemeContext for React components
  • Minimize re-renders when theme changes

Success Metrics

  • All components render correctly in dark mode
  • No accessibility contrast issues
  • Theme persists across sessions

Open Questions

  • Should we detect system theme preference automatically in v2? [/PRD]

Checklist

Before outputting the PRD:

  • Asked clarifying questions with lettered options
  • Asked about quality gates (REQUIRED)
  • Asked follow-up questions when needed
  • Quality Gates section included with project-specific commands
  • User stories are small and independently completable
  • User stories do NOT include quality gate commands (they're in the Quality Gates section)
  • Functional requirements are numbered and unambiguous
  • Non-goals section defines clear boundaries
  • PRD is wrapped in [PRD]...[/PRD] markers
how to use ralph-tui-prd

How to use ralph-tui-prd on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add ralph-tui-prd
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/subsy/ralph-tui --skill ralph-tui-prd

The skills CLI fetches ralph-tui-prd from GitHub repository subsy/ralph-tui and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/ralph-tui-prd

Reload or restart Cursor to activate ralph-tui-prd. Access the skill through slash commands (e.g., /ralph-tui-prd) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.459 reviews
  • Jin Gupta· Dec 24, 2024

    We added ralph-tui-prd from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Alexander Martin· Dec 20, 2024

    Useful defaults in ralph-tui-prd — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Aisha Khan· Dec 16, 2024

    Solid pick for teams standardizing on skills: ralph-tui-prd is focused, and the summary matches what you get after install.

  • Hassan Kapoor· Dec 12, 2024

    Keeps context tight: ralph-tui-prd is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Chaitanya Patil· Dec 4, 2024

    ralph-tui-prd has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Piyush G· Nov 23, 2024

    Solid pick for teams standardizing on skills: ralph-tui-prd is focused, and the summary matches what you get after install.

  • Jin Tandon· Nov 19, 2024

    ralph-tui-prd fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Arjun Nasser· Nov 15, 2024

    Keeps context tight: ralph-tui-prd is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Sophia Martinez· Nov 11, 2024

    I recommend ralph-tui-prd for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Hassan Jain· Nov 7, 2024

    ralph-tui-prd has been reliable in day-to-day use. Documentation quality is above average for community skills.

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