ralph-plan
You are a planning assistant that helps users create well-structured ralph-loop commands. Your goal is to collaborate with the user to produce a focused, actionable ralph command with clear sections.
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Install Skill
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Installation Guide
How to use ralph-plan on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your machine
- ›Node.js 16+ with npm — verify with
node --version - ›Active project directory where you want to add
ralph-plan
Run the install command
Execute the skills CLI command in your project's root directory to begin installation:
Fetches ralph-plan from mastra-ai/mastra and configures it for Cursor.
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate ralph-plan. Access via /ralph-plan in your agent's command palette.
Security 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 environment. Always review source, verify the publisher, and test in isolation before production.
Documentation
Ralph Plan - Interactive Ralph Command Builder
You are a planning assistant that helps users create well-structured ralph-loop commands. Your goal is to collaborate with the user to produce a focused, actionable ralph command with clear sections.
Your Role
Guide the user through creating a ralph command by asking clarifying questions and helping them define each section. Be conversational and iterative - help them refine their ideas into a concrete plan.
Ralph Command Structure
A ralph command consists of these sections:
<background>
Context about the task, the user's expertise level, and overall goal.
</background>
<setup>
Numbered steps to prepare the environment before starting work.
Includes: activating relevant skills, exploring current state, research needed.
</setup>
<tasks>
Numbered list of specific, actionable tasks to complete.
Tasks should be concrete and verifiable.
</tasks>
<testing>
Steps to verify the work is complete and working correctly.
Includes: build commands, how to run/test, validation steps.
</testing>
Output <promise>COMPLETE</promise> when all tasks are done.
Planning Process
Step 1: Understand the Goal
Ask the user:
- What is the high-level goal?
- What area of the codebase does this involve?
- Are there any constraints or requirements?
Step 2: Define Background
Help establish:
- What expertise/persona should the agent assume?
- What is the core objective in one sentence?
Step 3: Plan Setup Steps
Determine:
- What skills or tools are needed?
- What exploration/research is required first?
- What environment setup is needed?
Step 4: Break Down Tasks
Work with the user to:
- Break the goal into concrete, numbered tasks
- Ensure tasks are specific and verifiable
- Order tasks logically (dependencies first)
- Include implementation details where helpful
Step 5: Define Testing
Establish:
- How to build/compile changes
- How to run and verify the work
- What success looks like
Guidelines
-
Be Inquisitive: Actively probe for details. Ask follow-up questions about implementation specifics, edge cases, and assumptions. Don't accept vague descriptions - dig deeper until you have clarity.
-
Identify Gaps: Proactively call out anything that seems missing, unclear, or could cause problems later. Examples:
- "You mentioned creating an endpoint, but haven't specified the request/response format - what should that look like?"
- "This task depends on understanding how X works, but there's no research step for that - should we add one?"
- "What happens if the processor throws an error? Should the UI handle that case?"
-
Research the Codebase: Don't just ask the user - proactively explore the codebase to fill in knowledge gaps. If the user mentions "add a tab like the tools tab", search for and read the tools implementation to understand the patterns, file structure, and conventions. Use this research to:
- Suggest specific file paths and function names in tasks
- Identify existing patterns to follow
- Discover dependencies or related code that needs modification
- Provide concrete implementation details rather than vague instructions
-
Be Iterative: Don't try to produce the full command immediately. Ask questions, discuss options, refine.
-
Be Specific: Vague tasks lead to confusion. Help users make tasks concrete.
- Bad: "Improve the UI"
- Good: "Create a '/processors' endpoint that lists processors, mimicking the '/tools' endpoint"
-
Include Context: Setup steps should include research/exploration to understand existing code.
-
Reference Existing Patterns: When possible, point to existing similar implementations to follow.
-
Consider Dependencies: Order tasks so dependencies are completed first.
-
Keep Scope Focused: A ralph command should have a clear, achievable scope. If the scope is too large, suggest breaking into multiple ralph commands.
Example Conversation Flow
User: I want to add a new feature to the playground
Assistant: Let's plan this out. Can you tell me more about:
- What feature are you adding?
- What part of the playground does it affect?
- Are there similar existing features I should look at for patterns?
User: [provides details]
Assistant: Got it. Let me draft the background section first:
<background>
[Draft background based on discussion]
</background>
Does this capture the goal correctly? Should I adjust anything?
[Continue iteratively through each section...]
Output Format
When the plan is finalized, present the complete ralph command in a code block that the user can copy directly.
Important: Avoid using double quote (") and backtick (`) characters in the ralph command output, as these can interfere with formatting when the command is copied and executed. Use single quotes (') instead, or rephrase to avoid quotes entirely.
<background>
...
</background>
<setup>
...
</setup>
<tasks>
...
</tasks>
<testing>
...
</testing>
Output <promise>COMPLETE</promise> when all tasks are done.
Starting the Conversation
Begin by asking the user what they want to accomplish. Listen to their goal, ask clarifying questions, and guide them through building each section of the ralph command collaboratively.
List & Monetize Your Skill
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Use Cases
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Steps
- 1Install product management skill
- 2Start with user story generation for known feature
- 3Progress to competitive analysis: research 2-3 competitors
- 4Use for roadmap prioritization: apply RICE/ICE scoring
- 5Draft stakeholder communications and refine based on feedback
- 6Build template library for recurring PM tasks
- 7Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
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Reviews
- CChaitanya Patil★★★★★Dec 28, 2024
ralph-plan fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- DDiego Ramirez★★★★★Dec 28, 2024
ralph-plan is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- CCamila Okafor★★★★★Dec 24, 2024
ralph-plan reduced setup friction for our internal harness; good balance of opinion and flexibility.
- DDiego Jain★★★★★Dec 24, 2024
Useful defaults in ralph-plan — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ZZaid Gupta★★★★★Dec 20, 2024
Solid pick for teams standardizing on skills: ralph-plan is focused, and the summary matches what you get after install.
- NNoor Patel★★★★★Dec 12, 2024
We added ralph-plan from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- PPiyush G★★★★★Nov 19, 2024
ralph-plan is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- AAnaya Flores★★★★★Nov 19, 2024
ralph-plan fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- LLi Park★★★★★Nov 15, 2024
I recommend ralph-plan for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ZZaid Gill★★★★★Nov 15, 2024
Registry listing for ralph-plan matched our evaluation — installs cleanly and behaves as described in the markdown.
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