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.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionralph-planExecute 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.
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-plan. Access via /ralph-plan 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.
Submit your Claude Code skill and start earning
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
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
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
2
total installs
2
this week
22.7K
GitHub stars
0
upvotes
Run in your terminal
2
installs
2
this week
22.7K
stars
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.
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.
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.
Ask the user:
Help establish:
Determine:
Work with the user to:
Establish:
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:
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:
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.
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.
User: I want to add a new feature to the playground
Assistant: Let's plan this out. Can you tell me more about:
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...]
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.
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.
Make data-driven prioritization decisions faster
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
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ 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.
mattpocock/skills
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
ralph-plan fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
ralph-plan is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
ralph-plan reduced setup friction for our internal harness; good balance of opinion and flexibility.
Useful defaults in ralph-plan — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Solid pick for teams standardizing on skills: ralph-plan is focused, and the summary matches what you get after install.
We added ralph-plan from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
ralph-plan is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
ralph-plan fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
I recommend ralph-plan for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Registry listing for ralph-plan matched our evaluation — installs cleanly and behaves as described in the markdown.
showing 1-10 of 53