Generate detailed Product Requirements Documents optimized for AI agent execution via ralph-tui task orchestration.
Works with
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
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionralph-tui-prdExecute the skills CLI command in your project's root directory to begin installation:
Fetches ralph-tui-prd from subsy/ralph-tui and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate ralph-tui-prd. Access via /ralph-tui-prd in your agent's command palette.
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 environment. Always review source, verify the publisher, and test in isolation before production.
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Create detailed Product Requirements Documents optimized for AI agent execution via ralph-tui.
[PRD]...[/PRD] markers for TUI parsingImportant: Do NOT start implementing. Just create the PRD.
Ask questions one set at a time. Each answer should inform your next questions. Focus on:
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.
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
After each response, decide whether to:
Typically 2-4 rounds of questions are needed.
Generate the PRD with these sections:
Brief description of the feature and the problem it solves.
Specific, measurable objectives (bullet list).
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.
Each story needs:
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:
Numbered list of specific functionalities:
Be explicit and unambiguous.
What this feature will NOT include. Critical for managing scope.
How will success be measured?
Remaining questions or areas needing clarification.
The PRD will be executed by AI coding agents via ralph-tui. Therefore:
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
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:
What is the primary goal? A. Reduce eye strain for long sessions B. Match system theme preference C. Provide visual customization D. Other
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:
Which components need dark mode support? A. All TUI components B. Only the main execution view C. Main view + settings D. Other
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]
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]
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.
These commands must pass for every user story:
pnpm typecheck - Type checkingpnpm lint - LintingFor UI stories, also include:
Description: As a user, I want to set my preferred theme (light/dark) so that it persists across sessions.
Acceptance Criteria:
theme field to .ralph-tui.yaml schemaDescription: As a user, I want a soft-contrast dark theme that's easy on the eyes.
Acceptance Criteria:
Description: As a user, I want all TUI components to respect my theme preference.
Acceptance Criteria:
Description: As a user, I want to toggle themes from within the TUI settings.
Acceptance Criteria:
.ralph-tui.yamlBefore outputting the PRD:
[PRD]...[/PRD] markersPrerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ 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.
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We added ralph-tui-prd from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Useful defaults in ralph-tui-prd — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Solid pick for teams standardizing on skills: ralph-tui-prd is focused, and the summary matches what you get after install.
Keeps context tight: ralph-tui-prd is the kind of skill you can hand to a new teammate without a long onboarding doc.
ralph-tui-prd has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: ralph-tui-prd is focused, and the summary matches what you get after install.
ralph-tui-prd fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Keeps context tight: ralph-tui-prd is the kind of skill you can hand to a new teammate without a long onboarding doc.
I recommend ralph-tui-prd for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
ralph-tui-prd has been reliable in day-to-day use. Documentation quality is above average for community skills.
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