# lean-startup

Guides MVP scoping, leap-of-faith assumption testing, and Build-Measure-Learn experiments directly in AI coding assistants.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 5800 installs · ★ 2508
- Author: wondelai
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/wondelai/skills/tree/HEAD/lean-startup/SKILL.md
- Updated: 2026-09-10
- HTML: https://affpapa.org/en/nevibecode/skills/lean-startup

## What it does

This skill embeds Eric Ries's Lean Startup methodology into agent workflows. It enforces reverse planning for the Build-Measure-Learn loop: define the learning hypothesis first, select actionable metrics, and only then construct the minimum test. Every plan receives a diagnostic score up to 10 points based on validated evidence rather than vanity signals.

The prompt structures MVPs into five models: Concierge, Wizard of Oz, Smoke test, Single feature, and Piecemeal assemblies. Evidence gets evaluated against a five-tier Validation Ladder. Stated preferences and signups rank low, while upfront deposits and sustained active usage are treated as the only reliable commitments before building at scale.

Building full features before reaching Level 4 or 5 evidence is flagged as waterfall thinking. When testing customer motivations or running five-day prototype sprints, the repository documentation points toward `jobs-to-be-done` and `design-sprint` instead.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add wondelai/skills --skill lean-startup -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/lean-startup/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/lean-startup/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add wondelai/skills --skill lean-startup -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/lean-startup/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add wondelai/skills --skill lean-startup -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/lean-startup/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install wondelai/skills lean-startup
```

2. **Manually: put the files in place**
- File: `.github/skills/lean-startup/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add wondelai/skills --skill lean-startup -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/wondelai/skills --path lean-startup
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/lean-startup/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add wondelai/skills --skill lean-startup -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/wondelai/skills/tree/HEAD/lean-startup/SKILL.md

## When to use it
- scope a minimal MVP without overbuilding features
- rank leap-of-faith business assumptions by risk
- evaluate user validation signals on the 5-level ladder
- set up innovation accounting baselines before scaling

## Example prompts
- Help me design a smoke test MVP to validate demand before writing backend code
- Review our onboarding metrics and score them against the Validation Ladder
- Identify the riskiest leap-of-faith assumptions for our SaaS product

## Source text · SKILL.md · MIT

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 6ef349a2204cd861.

BEGIN THIRD-PARTY FILE 6ef349a2204cd861
```text
---
name: lean-startup
description: 'Design MVPs, validated learning experiments, and pivot-or-persevere decisions using Build-Measure-Learn. Use when the user mentions "MVP scope", "validated learning", "pivot or persevere", "vanity metrics", "test assumptions", "innovation accounting", "build-measure-learn", "minimum viable experiment", "should we pivot", "test a business idea cheaply", or "build the smallest version first". Also trigger when deciding what to include in a first version, measuring startup progress, or evaluating whether to change direction on a product bet. Covers innovation accounting and actionable metrics. For 5-day prototype testing, see design-sprint. For customer motivation analysis, see jobs-to-be-done.'
license: MIT
metadata:
  author: wondelai
  version: "1.4.0"
---

# Lean Startup Methodology

A systematic approach to building startups and launching new products that shortens development cycles and rapidly discovers whether a business model is viable.

## Core Principle

**Entrepreneurship is a form of management.** Success doesn't require a perfect plan or brilliant insight—it requires a systematic process for testing assumptions, learning from customers, and iterating rapidly. Most startups fail not because they couldn't build what they planned, but because they built the wrong thing: treat every plan as a set of hypotheses to falsify, and spend effort to eliminate waste and accelerate **validated learning**, not to execute a fixed roadmap.

## Scoring

**Goal: 10/10.** Score a plan, experiment, or metric set by the five Quick Diagnostic rows—**1 point each** when the answer is yes, **2 points** when it is also backed by evidence on the Validation Ladder (Level 3+):

- **9-10:** every leap-of-faith assumption named and ranked by risk, the riskiest tested by a real MVP, actionable metrics defined, and explicit pivot criteria set before building.
- **5-6:** a hypothesis and some MVP exist, but metrics are vanity or pivot criteria are undefined—decisions can't be made from the data.
- **≤3:** waterfall thinking—building the full product first, asking customers what they want, or scaling before product/market fit.

State the current score and the lowest-scoring diagnostic row to fix next.

## The Build-Measure-Learn Loop

The fundamental cycle: **IDEAS → BUILD (product) → MEASURE (data) → LEARN (knowledge) → back to IDEAS.**

**Critical insight:** Plan the loop backward:
1. **What do we want to learn?** (hypothesis to test)
2. **How will we know if we learned it?** (metrics)
3. **What's the minimum we can build?** (MVP)

**Goal:** Minimize total time through the loop.

See [references/build-measure-learn.md](references/build-measure-learn.md) when planning an experiment—reverse-planning sequence, an experiment-design template, per-product-type loop examples, and the build/vanity-metric loop traps.

## Validated Learning
```
END THIRD-PARTY FILE 6ef349a2204cd861

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