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lean-ux-canvas

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项目 README

来源文件:README.md

抓取于 2026年8月2日

Product Manager Skills

GitHub stars License: CC BY-NC-SA 4.0 PRs Welcome Version Claude Code Plugin Skills

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║   70 battle-tested skills + 6 command workflows                    ║
║   Claude Code • Cursor • Codex  • n8n • OpenClaw • and more ...    ║
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║   v0.83 • July 17, 2026 • CC BY-NC-SA 4.0                          ║
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70 battle-tested PM frameworks, ready for Claude, Codex, ChatGPT, and any agent that can read structured knowledge.


Why This Exists

Generic AI output is a PM's worst enemy. When you tell your agent "write a PRD" without shared context, you get a generic document that no stakeholder trusts and no engineer can act on.

This library gives both you and your AI agent the same professional foundation: the why behind each framework, the failure modes to avoid, and the judgment to apply them correctly. You stop repeating yourself. Your agent stops guessing. The work gets better.

The goal is dual — functional and pedagogic in equal measure. Skills equip agents to do PM work at a professional level, and they teach the human PM the reasoning behind each framework — so you can explain it, adapt it, and pass it on. Neither is a byproduct of the other.


What You Can Get Done

Navigate by what you're actually trying to accomplish:

Framing and strategy

  • problem-framing-canvas — MITRE's Look Inward / Look Outward / Reframe sequence; stops teams from solving the wrong problem
  • positioning-statement — Geoffrey Moore's template for defining who you serve, what you solve, and how you're different
  • product-strategy-session — full strategy arc: positioning → problem framing → solution exploration → roadmap (2-4 weeks)

Stakeholder alignment

  • stakeholder-identification — map every stakeholder before engaging anyone: broad brainstorm → allies/audiences/influencers → R/P/D marking → equity lens → narrow to priority targets
  • stakeholder-mapping — run two complementary grids (Power × Interest for engagement strategy; Impact × Power for whose voice to elevate) and compare to find the gaps
  • stakeholder-engagement-advisor — per-stakeholder engagement planning: diagnoses their profile and context, then delivers tailored message framing, medium, cadence, and a named next action

Customer discovery and research

Prioritization and roadmapping

  • prioritization-advisor — asks 3-5 questions about your context, then recommends RICE, ICE, Kano, or the right alternative
  • epic-breakdown-advisor — splits large epics using Richard Lawrence's 9 patterns
  • roadmap-planning — gather inputs → define epics → prioritize → sequence → communicate (1-2 weeks)

Writing PM deliverables

  • user-story — Mike Cohn format + Gherkin acceptance criteria, with anti-patterns
  • prd-development — structured PRD: problem → personas → solution → metrics → stories (2-4 days)
  • press-release — Amazon Working Backwards: clarify product vision before writing a line of spec

Validation and experimentation

  • pol-probe-advisor — recommends which prototype type to run based on your hypothesis and risk level
  • pol-probe — template for documenting lightweight validation experiments before building

Finance and growth

  • business-health-diagnostic — diagnoses SaaS health across growth, retention, efficiency, and capital using your real metrics
  • organic-growth-advisor — McKinsey Growth Pyramid triage: diagnoses whether your constraint is in new segments, geographies, channels, or products
  • feature-investment-advisor — build / don't build recommendation using revenue impact, cost, ROI, and strategic value

Market and competitive intelligence

Career and leadership transitions

AI product work


Get Started

Choose your setup:

I use...Get thisNotes
Claude Desktop or Claude Webpm-skills-starter-pack.zipUnzip, then upload the individual skill ZIPs to Claude Skills
Claude CodePlugin marketplaceclaude /plugin marketplace add deanpeters/Product-Manager-Skills
Codexpm-skills-codex.zipInstalls .agents/skills and AGENTS.md
Not surepm-skills-starter-pack.zipStart here

All downloads: GitHub Releases

Themed packs for Claude Desktop / Web

Each pack below is a ZIP of upload-ready skill ZIPs — unzip, then upload individuals to Claude Skills:

PackDownloadWhat's inside
Starterpm-skills-starter-pack.zipCore skills across all categories
Discovery02-discovery-pack.zipResearch, interviewing, synthesis
Strategy03-strategy-pack.zipPositioning, roadmapping, prioritization
Delivery04-delivery-pack.zipPRDs, stories, epics
AI PM05-ai-pm-pack.zipContext engineering, orchestration, readiness
Market Intel06-market-intel-pack.zipThe full Market Intelligence Suite: disciplines, investigation chain, frameworks, monitors
All skills99-all-skills-pack.zipAll 70 skills

Install guides


Try It First — Streamlit (beta)

Not ready to wire skills into your agent setup? Run the local playground first and kick the tires in your browser.

pip install -r app/requirements.txt
streamlit run app/main.py

What you can do:

  • Learn — browse setup and integration paths without leaving the app
  • Find My Skill — describe your situation in plain English and get recommended skills
  • Run Skills — run a skill with your own scenario once you know what you want

Multi-provider support: Anthropic, OpenAI, Ollama. API keys via environment variables only (no in-app key entry).

Docs: app/STREAMLIT_INTERFACE.md · app/.env.example

Feedback welcome via GitHub Issues or LinkedIn.


70 Skills, 3 Types

Skills are organized in three tiers that build on each other:

┌────────────────────────────────────────────────────────┐
│  WORKFLOW SKILLS (19)                                  │
│  Complete end-to-end PM processes (days to weeks)      │
│  Example: run a full discovery cycle or write a PRD    │
└────────────────────────────────────────────────────────┘
                       ↓ orchestrates
┌────────────────────────────────────────────────────────┐
│  INTERACTIVE SKILLS (27)                               │
│  Guided discovery — 3-5 questions, then recommendations│
│  Example: "Which prioritization framework fits here?"  │
└────────────────────────────────────────────────────────┘
                       ↓ uses
┌────────────────────────────────────────────────────────┐
│  COMPONENT SKILLS (24)                                 │
│  Templates for specific PM deliverables (30-90 min)    │
│  Example: write a user story with acceptance criteria  │
└────────────────────────────────────────────────────────┘

Interactive skills use an Adaptive Decision Ladder. Instead of dumping a framework at you, an interactive skill asks 3-5 targeted questions about your specific context, then offers numbered recommendations — each with a clear "use this when" rationale. You pick a path. The skill executes it and explains the why as it goes. If you want to just learn the framework without doing the work, you can ask that too — the skill coaches you either way. This is ABC — Always Be Coaching — in practice.

Full catalog: catalog/INDEX.md — all 70 skills with descriptions, or browse skills/ directly.


How a Skill File Works

Every SKILL.md follows the same structure:

SectionWhat it contains
Frontmattername, description, type, intent, best_for, scenarios
PurposeWhat this skill does and when to reach for it
InputWhat you can bring (with example invocations) — inline input is used, not re-asked, and arriving empty-handed is fine: the skill walks you through it
Key ConceptsFrameworks, definitions, anti-patterns — with vocabulary explained
ApplicationStep-by-step instructions an agent (or human) can follow
ExamplesReal-world cases showing both good and bad versions
Common PitfallsNamed failure modes with consequences and corrections
ReferencesRelated skills and external frameworks

The best_for frontmatter field lists 3-5 specific scenarios where the skill is most useful — helpful for quickly scanning whether a skill fits your situation.

Why no $ARGUMENTS templating? Other skill libraries use Claude Code's $ARGUMENTS substitution for input. We deliberately don't: it only expands in Claude Code (it renders as literal syntax in Claude Desktop/Web, Codex, and the Streamlit playground), and it teaches the human reader nothing. Instead, every skill has a plain-language ## Input section that works on every runtime — and makes clear you can show up with full context, partial context, or nothing at all and be guided through the rest. Full rationale in CONTRIBUTING.md.


Works With

Claude Code · Claude Desktop · Claude Web · OpenAI Codex · ChatGPT · Cursor · Windsurf · n8n · LangFlow · CrewAI · Gemini · any agent that reads structured markdown

See docs/Platform Guides for PMs.md for platform-specific setup.


Docs

DocumentPurpose
Using PM Skills 101Beginner-friendly orientation — setup without technical overload
Platform Guides for PMsTool-by-tool setup chooser for every supported platform
Using PM Skills with ClaudeClaude Code + GitHub ZIP upload for Claude Desktop/Web
Using PM Skills with CodexLocal workspace + GitHub-connected Codex on ChatGPT
Using PM Skills with ChatGPTGitHub app, Custom GPT Knowledge, and Project-based usage
Using PM Skills with Slash Commands 101Turn skills into reusable slash commands like /pm-story
Add-a-Skill Utility GuideEnd-to-end guide for generating and validating new skills
Market Intelligence Suite SummaryThe 14-skill competitive/market research suite: disciplines, chain, and which skill to run when
Building PM SkillsHow raw PM content gets distilled into agent-ready skills
START_HERE.md60-second onboarding for local repo users

What's New

v0.83 — July 17, 2026 · The Market Intelligence Suite

v0.82 — July 8, 2026

  • Added incoming-request-advisor (Interactive) — drop in a Slack ping, email, mandate, or escalation and get a structured breakdown that separates the literal ask from the real job-to-be-done, reads sender power and stake, and points you toward a reply. Ships with a copy/paste template so you can run it by hand too
  • New: a browsable download shelf at /dist — no terminal, no Releases tab. Read the plain-language README, scan the CATALOG, and download any skill or pack straight from the repo. Built for PMs who just want the skills
  • Library now at 70 skills

v0.81 — July 4, 2026

  • Every skill now has a required ## Input section: what to bring, what happens to context you supply up front (it's used, not re-asked), and reassurance that arriving empty-handed is fine — the guided flow covers the rest
  • Added argument-hint autocomplete for Claude Code users; deliberately no $ARGUMENTS templating — it breaks on every other runtime and teaches the reader nothing (why)
  • Validator now enforces the convention: skills fail without an Input section or with bare $ARGUMENTS in the body
  • Streamlit playground shows each skill's "What to bring (all optional)" before you start a session
  • Restored agent-orchestration-advisor (Interactive) — the multi-agent workflow design skill was referenced everywhere but only existed on an orphaned commit; recovered from git history and brought up to current standards

v0.80 — June 19, 2026

  • Added stakeholder-identification (Component) — comprehensive stakeholder brainstorm using allies/audiences/influencers, R/P/D marking, equity lens, and bias check; narrows to priority targets
  • Added stakeholder-mapping (Component) — two complementary grids (Power × Interest + Impact × Power); comparing outputs reveals who you're under-engaging relative to how much the product affects them
  • Added stakeholder-engagement-advisor (Interactive) — per-stakeholder engagement planning via Adaptive Decision Ladder: three questions on profile, power/impact, and context deliver tailored message framing, medium, cadence, and a named next action

All three adapted from the MITRE Innovation Toolkit via the companion repo MITRE ITK Skills — worth a bookmark if you work in discovery, facilitation, or cross-functional product strategy.

v0.79 — May 15, 2026

  • Added organic-growth-advisor — McKinsey Growth Pyramid triage for new segments, geographies, channels, or products
  • Added pm-skill-creator — interactive skill for designing repo-compliant skills via guided conversation
  • Fixed missing .claude-plugin/plugin.json that silently blocked Claude Code skill discovery
  • Added configurable input length guard (PM_MAX_INPUT) and path traversal protection to helper scripts

→ Full changelog


Contributing

Found a gap? Have a PM framework worth formalizing? The bar is pedagogic — skills must teach the why, not just the how.

See CONTRIBUTING.md for guidelines, or open an issue to start a conversation.


License

CC BY-NC-SA 4.0 — non-commercial use with share-alike.

Everything in this repository — every skill, template, and doc — is licensed CC BY-NC-SA 4.0. There is no mix of licenses here.

Some skills note in their Provenance sections that they were adapted from product-manager-prompts, Dean's earlier prompt library. That repo has the same author, so there is no license conflict: a license grants permissions to other people, and a copyright holder is free to adapt and relicense their own work. Those Provenance lines are lineage — a breadcrumb back to where an idea started — not a license dependency. No third-party MIT-licensed text is incorporated anywhere in this library.

In plain terms:

  • ✅ Use these skills in your day job — at a for-profit company, with your team, in your agents. That's what they're for.
  • ✅ Adapt and remix them — share what you build under this same license, with credit.
  • ✅ Teach with them — workshops, brown bags, mentoring, sending the ladder down.
  • ❌ Don't sell them — no repackaging the skills themselves into a paid product, course, or service without expressed written permission.
  • 🤔 Not sure your use qualifies? Open an issue and ask. If you're using these in the spirit they were built — to get better at the craft and help others do the same — the answer is almost certainly yes.

The companion prompt library, product-manager-prompts, carries the same CC BY-NC-SA 4.0 license as of its v2.3.0, with its own plain-language permissions (stricter on commercial use) — see its LICENSING.md, which governs that repo.


Questions

商业与运营

中风险

  • 来源需自行核对维护者身份。
  • 未检测到明显脚本安装指令。
  • 可能需要外部 token、网络权限或第三方服务。
  • 未检测到高风险命令。
  • 扫描发现:2 条。

Codex — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/deanpeters/Product-Manager-Skills.git
  3. 将 "skills/lean-ux-canvas" 文件夹复制到 Codex 的 skills 目录中。
  4. 重启 Codex 让新的 skill 生效。

Codex — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Codex 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Codex 让新的 skill 生效。

Claude Code — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/deanpeters/Product-Manager-Skills.git
  3. 将 "skills/lean-ux-canvas" 文件夹复制到 Claude Code 的 skills 目录中。
  4. 重启 Claude Code 让新的 skill 生效。

Claude Code — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Claude Code 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Claude Code 让新的 skill 生效。

Cursor — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/deanpeters/Product-Manager-Skills.git
  3. 将 "skills/lean-ux-canvas" 文件夹复制到 Cursor 的 skills 目录中。
  4. 重启 Cursor 让新的 skill 生效。

Cursor — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Cursor 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Cursor 让新的 skill 生效。

GitHub Copilot — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/deanpeters/Product-Manager-Skills.git
  3. 将 "skills/lean-ux-canvas" 文件夹复制到 GitHub Copilot 的 skills 目录中。
  4. 重启 GitHub Copilot 让新的 skill 生效。

GitHub Copilot — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 GitHub Copilot 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 GitHub Copilot 让新的 skill 生效。

Windsurf — Git Clone 安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 克隆仓库:git clone https://github.com/deanpeters/Product-Manager-Skills.git
  3. 将 "skills/lean-ux-canvas" 文件夹复制到 Windsurf 的 skills 目录中。
  4. 重启 Windsurf 让新的 skill 生效。

Windsurf — 手动复制安装

  1. 安装前请先查看来源仓库和风险报告。
  2. 从源仓库下载 SKILL.md 及相关文件。
  3. 在 Windsurf 的 skills 目录中创建新文件夹。
  4. 将所有 skill 文件复制到新文件夹中。
  5. 重启 Windsurf 让新的 skill 生效。
查看 SKILL.md 原文
name: lean-ux-canvas
argument-hint: "[business problem]"
description: Guide teams through Lean UX Canvas v2. Use when framing a business problem, surfacing assumptions, and defining what to learn next.
intent: >-
  Guide product managers through creating **Jeff Gothelf's Lean UX Canvas (v2)**—a one-page facilitation tool that frames work around a **business problem to solve**, not a **solution to implement**. Use this to align cross-functional teams around core assumptions, craft testable hypotheses, and ensure learning happens every sprint by exposing gaps in understanding (problem, users, value, and why the solution should work).
type: interactive
best_for:
  - "Framing a business problem before solutioning"
  - "Surfacing assumptions in a cross-functional workshop"
  - "Turning a vague initiative into hypotheses and learning goals"
scenarios:
  - "Help me run a Lean UX Canvas workshop for onboarding drop-off"
  - "Use Lean UX Canvas to frame a new AI product idea"
  - "We have a business problem but too many assumptions. Run a Lean UX Canvas session."

Purpose

Guide product managers through creating Jeff Gothelf's Lean UX Canvas (v2)—a one-page facilitation tool that frames work around a business problem to solve, not a solution to implement. Use this to align cross-functional teams around core assumptions, craft testable hypotheses, and ensure learning happens every sprint by exposing gaps in understanding (problem, users, value, and why the solution should work).

This is not a roadmap or feature list—it's an "insurance policy" that turns assumptions into experiments before committing to full development. The canvas shifts conversations from outputs to outcomes and ensures teams build the right thing, not just build things right.

Input

Works best with: The business problem you're framing — or the solution idea you're being handed, which the canvas will reframe as a problem. Also useful: Known users, evidence so far, and what the team already believes (assumptions to surface).

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.

Arriving empty-handed? That works too. The skill opens with Box 1: what business problem are you trying to solve?

Example invocation: Fill a Lean UX canvas: leadership wants 'an AI chatbot' — underlying problem seems to be support ticket volume growing 3x faster than the team.

Key Concepts

What is the Lean UX Canvas?

The Lean UX Canvas (v2) is a structured, one-page template designed to help teams frame their work around a business problem, not a solution. It aligns cross-functional teams on:

  • What problem exists (and why it matters now)
  • What measurable outcomes indicate success
  • Who we're solving for
  • What assumptions we're making
  • What we need to learn first
  • What experiments will test those assumptions

Origin: Created by Jeff Gothelf, author of Lean UX (O'Reilly, 2013). Version 2 was released to improve clarity around business vs. user outcomes.

Key Insight: The canvas acts like an insurance policy—it exposes gaps in understanding before you build, ensuring you don't waste sprints on the wrong thing.


Canvas Structure (8 Boxes)

Layout (3 columns × 3 rows):

┌─────────────────────┬──────────────┬───────────────────────┐
│ 1. Business Problem │              │ 2. Business Outcomes  │
│                     │              │                       │
├─────────────────────┤ 5. Solutions ├───────────────────────┤
│ 3. Users            │  (tall box   │ 4. User Outcomes      │
│                     │   spanning   │    & Benefits         │
├─────────────────────┤   rows 1-2)  ├───────────────────────┤
│ 6. Hypotheses       │──────────────┤ 8. Least Work /       │
│                     │ 7. Learn     │    Experiments        │
│                     │    First     │                       │
└─────────────────────┴──────────────┴───────────────────────┘

The 8 Boxes (fill in this order):

  1. Business Problem — What changed in the world that created a problem worth solving?
  2. Business Outcomes — What measurable behavior change indicates success?
  3. Users — Which persona(s) should you focus on first?
  4. User Outcomes & Benefits — Why would users seek this? What benefit do they gain?
  5. Solutions — What features/initiatives might solve the problem and meet user needs?
  6. Hypotheses — Testable assumptions combining boxes 2-5 (If/Then format)
  7. What's Most Important to Learn First? — The single riskiest assumption right now
  8. What's the Least Work to Learn Next? — Smallest experiment to validate/invalidate that assumption

Why This Works

Problem-First, Not Solution-First: Starts with "what changed in the world?" not "we should build X." This prevents solution-driven thinking.

Assumption-Driven: Makes hypotheses explicit before building. Every discipline surfaces their risks (technical feasibility, user value, business viability).

Experiment-Focused: Tests assumptions before committing resources. Small experiments beat big bets.

Cross-Functional Alignment: Shared canvas creates common language. Everyone sees the same gaps in understanding.


Key Distinctions (Avoid Confusion)

Box 2 (Business Outcomes) vs. Box 4 (User Outcomes):

  • Box 2: Measurable behavior change (retention rate, time on site, average order value)
  • Box 4: Goals, benefits, emotions, empathy (save money, get promoted, spend time with family)

Box 2 is metrics. Box 4 is human.

Solutions (Box 5) Are Hypotheses, Not Commitments: List candidate solutions (features, policies, even business model shifts). You're not committing to build all of them—you're exploring the solution space.

Hypotheses (Box 6) Are Testable: Use the template: "We believe [business outcome] will be achieved if [user] attains [benefit] with [solution]." Each hypothesis focuses on one solution.


Anti-Patterns (What This Is NOT)

  • Not a feature list: Solutions are ideas to test, not a backlog
  • Not a project plan: Canvas frames learning, not delivery timelines
  • Not a replacement for strategy: Canvas executes strategy; it doesn't create it
  • Not a one-time exercise: Re-visit as you learn; update assumptions

When to Use This

✅ Use this when:

  • Starting a new product initiative or feature
  • Reframing an existing project (suspect you're building the wrong thing)
  • Aligning cross-functional teams on assumptions and experiments
  • Planning discovery sprints or MVPs
  • Stakeholders are solution-driven ("we need to build X") and you need to expose assumptions

❌ Don't use this when:

  • Problem and solution are already validated (move to execution)
  • Tactical bug fixes or technical debt (no learning needed)
  • Stakeholders have committed to a solution regardless of evidence (address alignment first)

Facilitation Source of Truth

Use workshop-facilitation as the default interaction protocol for this skill.

It defines:

  • session heads-up + entry mode (Guided, Context dump, Best guess)
  • one-question turns with plain-language prompts
  • progress labels (for example, Context Qx/8 and Scoring Qx/5)
  • interruption handling and pause/resume behavior
  • numbered recommendations at decision points
  • quick-select numbered response options for regular questions (include Other (specify) when useful)

This file defines the domain-specific assessment content. If there is a conflict, follow this file's domain logic.

Application

Use template.md for the full fill-in structure.

This interactive skill walks through 8 adaptive questions (one per canvas box) in sequence. At each step, the agent offers guidance, examples, and options to help you fill the box correctly.


Step 0: Gather Context

Agent asks:

Before we fill out the Lean UX Canvas, let's gather context. Please share:

Business Context:

  • Stakeholder request, product brief, or initiative description
  • Business metrics (revenue, churn, growth targets, KPIs)
  • Strategic goals (OKRs, roadmap priorities)

User Context:

  • Customer research, personas, JTBD insights
  • User feedback, support tickets, churn reasons
  • Competitor analysis, market trends

You can paste:

  • PRD or product brief
  • Stakeholder memo
  • User research summary
  • Just describe the initiative briefly

Question 1: Business Problem (Box 1)

Agent asks:

What problem does the business have that you are trying to solve?

Describe:

  • Current state: How does the business deliver value today?
  • What changed: Market shift, competitive threat, customer behavior change, new delivery channel
  • Why it matters: Why isn't the current situation meeting expectations?

Good examples:

  • "Our checkout conversion rate dropped 15% after mobile traffic surpassed desktop. Our checkout flow wasn't designed for mobile, and competitors have one-tap checkout."
  • "Enterprise customers are churning after 6 months because our onboarding process requires 3+ weeks of manual configuration. Competitors offer self-service onboarding."

Bad examples (too vague):

  • "We need to increase revenue" (no context on what changed)
  • "Users want more features" (no business problem stated)

Agent offers 3 options:

  1. I'll describe the business problem — [Paste or write your description]
  2. Help me identify the business problem — [Agent asks follow-up questions: What changed? What metrics are affected? What are competitors doing?]
  3. I'm not sure what the business problem is — [Agent suggests starting with skills/problem-statement/SKILL.md or skills/problem-framing-canvas/SKILL.md first]

User response: [Selection or description]

Agent validates: Does this describe what changed and why it creates a problem? If not, ask clarifying questions.


Question 2: Business Outcomes (Box 2)

Agent asks:

How will you know you solved the business problem? What will you measure?

Focus on measurable behavior change (leading indicators welcome). Ask yourself: "What will people be doing differently if the solution works?"

Examples of business outcomes:

  • Increase mobile checkout conversion rate from 45% to 60%
  • Reduce enterprise onboarding time from 3 weeks to 3 days
  • Increase average order value from $50 to $75
  • Reduce customer support tickets by 30%
  • Increase free-to-paid conversion rate from 5% to 10%

Important: This is Box 2 (behavior change), not Box 4 (user benefits/empathy). Metrics go here. Emotions go in Box 4.

Agent offers 3 options:

  1. I have specific metrics in mind — [State your business outcomes]
  2. Help me define measurable outcomes — [Agent suggests metrics based on the business problem]
  3. I only have lagging indicators (revenue, profit) — [Agent helps identify leading indicators that predict those outcomes]

User response: [Selection or description]

Agent validates: Are these measurable? Observable? Do they indicate behavior change (not just "increase revenue")?


Question 3: Users (Box 3)

Agent asks:

What types (i.e., personas) of users and customers should you focus on first?

Consider:

  • Who buys it?
  • Who uses it?
  • Who configures it?
  • Who administers it?

Why this matters: Teams tend to shortcut here ("everyone"). The canvas wants a shared vision of the user—and it's not always "the customer."

Examples:

  • "SMB owners (1-10 employees) in professional services (consultants, accountants, lawyers)"
  • "Enterprise IT admins who configure SSO for 500+ employees"
  • "Mobile-first millennials (25-35) who order takeout 3+ times per week"

Agent offers 3 options:

  1. I have personas already — [Reference skills/proto-persona/SKILL.md or paste persona]
  2. Help me identify target users — [Agent asks: Who experiences the business problem most? Who's most likely to adopt? Who's easiest to reach?]
  3. I need to create personas first — [Agent suggests using skills/proto-persona/SKILL.md component skill]

User response: [Selection or description]

Agent validates: Is this specific enough to imagine a real person? Or is it too broad ("all users")?


Question 4: User Outcomes & Benefits (Box 4)

Agent asks:

Why would your users seek out your product or service? What benefit would they gain? What behavior change can we observe that tells us they've achieved their goal?

Focus on goals, benefits, emotions, empathy—not metrics (those go in Box 2).

Examples of user outcomes & benefits:

  • Save 10 hours per week on manual data entry (spend more time with family)
  • Get promoted by delivering projects faster
  • Avoid embarrassment of failed checkout in front of friends
  • Feel confident configuring enterprise software without calling support

Why this matters: This is the empathy box. It's about human motivation, not just behavior change.

Agent offers 3 options:

  1. I know what users want to achieve — [Describe user benefits]
  2. Help me identify user benefits — [Agent prompts: What job are they hiring this product to do? What pain are they avoiding? What gain are they seeking?]
  3. I need to research this first — [Agent suggests skills/jobs-to-be-done/SKILL.md or skills/discovery-interview-prep/SKILL.md]

User response: [Selection or description]

Agent validates: Does this explain why the user cares (not just what they'll do)?


Question 5: Solutions (Box 5)

Agent asks:

What can we make that will solve our business problem and meet the needs of our customers at the same time?

List features, initiatives, policies, systems, or even business model shifts that might work. Encourage a wide solution space: big/small, innovative, "weird," and non-technical solutions.

Examples:

  • One-tap mobile checkout (Apple Pay, Google Pay)
  • Self-service onboarding wizard (no human configuration)
  • AI-powered recommendation engine
  • Concierge onboarding (high-touch, manual—test before automating)
  • Change pricing model (usage-based instead of flat rate)

Important: These are hypotheses, not commitments. You're exploring options, not committing to build everything.

Agent offers 3 options:

  1. I have solution ideas — [List your candidate solutions]
  2. Help me brainstorm solutions — [Agent suggests solutions based on problem, outcomes, and users]
  3. I only have one solution in mind — [Agent challenges: "What else could solve this? What if that solution doesn't work?"]

User response: [Selection or description]

Agent validates: Do you have at least 3 candidate solutions? (More options = better hypotheses later)


Question 6: Hypotheses (Box 6)

Agent asks:

Now let's create testable hypotheses by combining assumptions from Boxes 2-5.

Use this template:

We believe that [business outcome from Box 2] will be achieved if [user from Box 3] attains [benefit from Box 4] with [solution from Box 5].

Rules:

  • Each hypothesis focuses on one solution (from Box 5)
  • Combines assumptions from Boxes 2, 3, 4, and 5
  • Must be testable (you can design an experiment to validate/invalidate it)

Example:

We believe that increasing mobile checkout conversion rate from 45% to 60% will be achieved if mobile-first millennials (25-35) attain faster, friction-free checkout with one-tap Apple Pay integration.

Agent offers:

Based on your inputs, here are suggested hypotheses (one per solution from Box 5):

  1. [Generated hypothesis 1]
  2. [Generated hypothesis 2]
  3. [Generated hypothesis 3]

Options:

  • Accept these hypotheses — [Agent records them]
  • Edit a hypothesis — [Modify wording]
  • Write my own hypotheses — [Use the template]

User response: [Selection or description]

Agent validates: Does each hypothesis clearly state what you believe will happen if the solution works?


Question 7: What's the Most Important Thing We Need to Learn First? (Box 7)

Agent asks:

For each hypothesis from Box 6, identify its riskiest assumptions. Then determine the riskiest one right now.

Types of risk:

  • Value risk: Will users actually use this? Do they care?
  • Usability risk: Can users figure out how to use it?
  • Feasibility risk: Can we technically build this?
  • Viability risk: Will this achieve the business outcome?

Hint: Early on, focus risk on value more than feasibility (most of the time). Don't build something users don't want, even if it's technically feasible.

Agent offers:

Based on your hypotheses, here are the riskiest assumptions:

  1. [Hypothesis 1 risk] — e.g., "Users will trust one-tap checkout without seeing itemized charges"
  2. [Hypothesis 2 risk] — e.g., "Self-service onboarding will reduce setup time to <3 days"
  3. [Hypothesis 3 risk] — e.g., "AI recommendations will increase average order value by 50%"

Which is the riskiest right now?

Options:

  1. Risk 1 — [Select and explain why]
  2. Risk 2 — [Select and explain why]
  3. Risk 3 — [Select and explain why]
  4. I'm not sure which is riskiest — [Agent helps prioritize: Which assumption, if wrong, would kill the initiative?]

User response: [Selection]

Agent records: This is the assumption we'll test first.


Question 8: What's the Least Amount of Work We Need to Do to Learn the Next Most Important Thing? (Box 8)

Agent asks:

Design an experiment to validate or invalidate the riskiest assumption (from Box 7) as fast as you can.

Examples of experiment types:

  • Customer interviews — 5-10 interviews to test value hypothesis
  • Landing page — Fake door test to measure interest
  • Concierge / manual prototype — High-touch, manual version before automating
  • Wizard-of-Oz — Pretend the feature exists (humans behind the scenes)
  • Smoke test — Announce the feature, measure signups

Reminder: Experiment design is an art. The canvas nudges you to do it—expect to iterate on the experiment design separately.

Agent offers:

Based on your riskiest assumption, here are experiment options:

  1. Customer Interviews — Talk to 10 users, ask if they'd use [solution], observe their current workaround
  2. Landing Page Test — Create a landing page describing [solution], measure signup rate
  3. Concierge Test — Manually deliver [benefit] to 5 users, observe if they achieve [outcome]
  4. Wizard-of-Oz Prototype — Fake [solution] with humans behind the scenes, see if users complete the workflow
  5. Design a custom experiment — [Describe your experiment]

Which experiment will you run?

User response: [Select one or describe custom experiment]

Agent validates: Is this the smallest test that can validate/invalidate the assumption? (If it takes >2 weeks, it's too big—break it down.)


Step 9: Review and Export Canvas

Agent summarizes:

Here's your completed Lean UX Canvas (v2):

┌─────────────────────────────────────────────────────────────┐
│ Lean UX Canvas (v2)                                         │
│ Initiative: [Title]                                         │
│ Date: [Today's date]                                        │
│ Iteration: 1                                                │
└─────────────────────────────────────────────────────────────┘

┌─────────────────────┬──────────────┬───────────────────────┐
│ 1. Business Problem │              │ 2. Business Outcomes  │
│ [Your input]        │              │ [Your input]          │
│                     │              │                       │
├─────────────────────┤ 5. Solutions ├───────────────────────┤
│ 3. Users            │              │ 4. User Outcomes      │
│ [Your input]        │ [Your input] │    & Benefits         │
│                     │              │ [Your input]          │
├─────────────────────┤──────────────┼───────────────────────┤
│ 6. Hypotheses       │ 7. Learn     │ 8. Experiments        │
│ [Your input]        │    First     │ [Your input]          │
│                     │ [Your input] │                       │
└─────────────────────┴──────────────┴───────────────────────┘

Next steps:

  1. Run the experiment (Box 8) — Set a timeline (e.g., 2 weeks)
  2. Document learnings — What did you learn? Was the assumption validated or invalidated?
  3. Update the canvas — Revise hypotheses based on learnings, choose next riskiest assumption
  4. Iterate — Repeat Box 7 → Box 8 until confidence is high enough to build

Agent asks:

Would you like me to:

  1. Export this canvas as a Markdown file?
  2. Suggest related skills to use next (e.g., skills/discovery-interview-prep/SKILL.md for customer interviews)?
  3. Refine a specific box (if something feels incomplete)?

Examples

See examples/sample.md for full Lean UX Canvas examples.

Mini example excerpt:

**Box 1:** Mobile checkout conversion is 15% lower than desktop
**Box 2:** Increase mobile conversion from 45% to 60%
**Box 8:** Wizard-of-Oz test with one-tap checkout

Common Pitfalls

1. Starting with Solutions, Not Problems

Failure Mode: Box 1 says "We need to build X" instead of describing what changed.

Consequence: You build the solution someone already decided on, without validating the problem exists.

Fix: Ask: "What changed in the world? Why is this a problem now (vs. 6 months ago)?"


2. Vague Business Outcomes

Failure Mode: Box 2 says "Increase revenue" or "Make users happy."

Consequence: No way to measure success; can't tell if experiments worked.

Fix: Define measurable behavior change. "Increase average order value from $50 to $75" or "Reduce support tickets by 30%."


3. Too-Broad User Segments

Failure Mode: Box 3 says "All users" or "Everyone."

Consequence: Can't design targeted experiments; waste time on personas who won't adopt.

Fix: Pick one persona to start. You can expand later.


4. Confusing Box 2 and Box 4

Failure Mode: Putting emotions in Box 2 and metrics in Box 4 (or vice versa).

Consequence: Misaligned hypotheses; unclear success criteria.

Fix: Box 2 = Behavior change (metrics). Box 4 = Goals, benefits, emotions (empathy).


5. Only One Solution in Box 5

Failure Mode: Listing one feature because stakeholders already decided.

Consequence: No exploration of alternatives; can't test which solution is best.

Fix: Force yourself to list 3+ solutions. Ask: "What else could solve this problem?"


6. Skipping Experiments (Box 8)

Failure Mode: "We'll just build it and see what happens."

Consequence: Waste weeks/months building the wrong thing.

Fix: Design smallest experiment first. If you can't think of one, use skills/pol-probe-advisor/SKILL.md to choose a validation method.


References

Related Skills

External Frameworks

  • Jeff Gothelf — Lean UX: Designing Great Products with Agile Teams (O'Reilly, 2013; 2nd ed. 2016)
  • Jeff Gothelf — Lean UX Canvas v2 (official blog post)
  • Lean UX Canvas PDF — Download v2 PDF

Tools

  • Miro / Mural — Digital whiteboard for collaborative canvas filling
  • Google Slides / PowerPoint — Template available from Jeff Gothelf's site
  • Notion / Coda — Database view for tracking multiple canvases

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