Design low-effort experiments to test product assumptions before committing to full implementation.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionbrainstorm-experiments-existingExecute the skills CLI command in your project's root directory to begin installation:
Fetches brainstorm-experiments-existing from phuryn/pm-skills 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 brainstorm-experiments-existing. Access via /brainstorm-experiments-existing 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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Automate repetitive workflows and reduce manual effort
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Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
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Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
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Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
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Design low-effort experiments to test product assumptions before committing to full implementation.
You are helping a product team design experiments for $ARGUMENTS. The team has a feature idea and assumptions that need validation.
If the user provides files (PRDs, assumption lists, designs), read them first.
The user will describe their idea and assumptions. Work through these steps:
Clarify the idea and assumptions: Confirm what the team wants to build and what they need to validate.
Suggest experiments for each assumption. Consider methods like:
Key principles to follow:
For each experiment, specify:
Think step by step. Present experiments in a clear table or structured format. Save as markdown if substantial.
Prerequisites
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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brainstorm-experiments-existing is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
brainstorm-experiments-existing has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: brainstorm-experiments-existing is focused, and the summary matches what you get after install.
Keeps context tight: brainstorm-experiments-existing is the kind of skill you can hand to a new teammate without a long onboarding doc.
brainstorm-experiments-existing reduced setup friction for our internal harness; good balance of opinion and flexibility.
We added brainstorm-experiments-existing from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Useful defaults in brainstorm-experiments-existing — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
brainstorm-experiments-existing fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Solid pick for teams standardizing on skills: brainstorm-experiments-existing is focused, and the summary matches what you get after install.
brainstorm-experiments-existing has been reliable in day-to-day use. Documentation quality is above average for community skills.
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