Lean Ux Canvas
Visualize user journeys, identify pain points, and brainstorm solutions using a dynamically generated Lean UX Canvas.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add lean-ux-canvas npx -- -y @trustedskills/lean-ux-canvas
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"lean-ux-canvas": {
"command": "npx",
"args": [
"-y",
"@trustedskills/lean-ux-canvas"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
The lean-ux-canvas skill provides a structured framework for product managers to define user problems, desired outcomes, and solution hypotheses. It guides agents through the core components of a Lean UX Canvas to validate ideas before full-scale development.
When to use it
- Brainstorming initial product concepts with an AI agent to ensure alignment on user needs.
- Validating assumptions about target audiences and value propositions during early-stage planning.
- Structuring feedback loops to iterate on features based on real-world user testing results.
- Creating a shared visual roadmap for cross-functional teams to understand the "why" behind a feature.
Key capabilities
- Problem Definition: Clearly articulating the specific user pain points being addressed.
- Desired Outcome: Defining measurable success metrics and goals for the solution.
- Solution Hypothesis: Drafting potential features or workflows to solve the identified problem.
- User Persona Mapping: Identifying who the primary users are and their specific contexts.
Example prompts
- "Help me fill out a Lean UX Canvas for a new mobile fitness tracking app targeting busy professionals."
- "Critique my current solution hypothesis against the user problems I've defined in this canvas."
- "Generate three alternative desired outcomes based on the user personas we just discussed."
Tips & gotchas
Ensure you provide specific context about your target audience before asking the agent to generate hypotheses, as generic inputs lead to vague solutions. This skill is best used iteratively; treat the output as a living document that evolves with new data rather than a final specification.
Tags
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