Proto Persona
This is for when you need to align a team around who you're building for but don't have months to run user research. It walks you through creating a hypothesis-driven persona from whatever you have: support tickets, stakeholder interviews, analytics, market data. The structure is opinionated about keeping it behavioral rather than just demographic, with sections for pains, goals, quotes, and decision-making context. It's explicit about what this isn't: not validated research, not permanent, not a substitute for talking to real users. Good for early-stage products or new features where you need a shared reference point that's better than design-by-committee but honest about being assumptions that need testing.
- skills.sh installs
- 2.4K
- GitHub stars
- 7.9K
- last updated
- Aug 21, 2026
Install
$ npx -y skills add deanpeters/product-manager-skills --skill proto-persona --agent claude-codeInstalls into .claude/skills of the current project.
Files
Purpose
Create an initial, assumption-based persona profile that synthesizes available user research, market data, and stakeholder knowledge into a working hypothesis about your target user. Use this to align teams early in product development, guide initial design decisions, and identify gaps in understanding that require validation through research.
This is not a validated persona—it's a "proto" (prototype) persona that evolves as you learn more. Think of it as a structured placeholder that prevents design-by-committee while acknowledging you don't have all the answers yet.
Input
Works best with: The target user or segment you need a working profile for. Also useful: Whatever signal exists — support themes, sales anecdotes, analytics, prior research — plus the decision the persona will guide.
Anything supplied with the invocation itself — text after the skill name, a pasted context dump, or an appended ARGUMENTS: line — counts as answers already given. Use it and skip whatever it covers; don't re-ask.
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- Repository
- github.com/deanpeters/product-manager-skills
- Category
- Data Science & ML
- First seen
- Apr 16, 2026
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