Agent skill

Idea Validation

by RefoundAI in RefoundAI/lenny-skills

Help users de-risk new product bets by testing core assumptions, building low-fidelity prototypes, and gathering high-signal evidence before investing heavy engineering resources.

MITAuto-check passedFrontend & Design

Install Idea Validation

skills CLI
$ npx skills add RefoundAI/lenny-skills --skill idea-validation -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install RefoundAI/lenny-skills idea-validation --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/RefoundAI/lenny-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/idea-validation .claude/skills/idea-validation && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
idea-validation
GitHub stars
1.4k
Token cost
~1.5k tokens
SKILL.md length
885 words
Files
3 (incl. references)
Skills in repo
76
Repo updated
First seen
Licence
MIT

At a glance

Help users de-risk new product bets by testing core assumptions, building low-fidelity prototypes, and gathering high-signal evidence before investing heavy engineering resources.

  • Works in 4 steps: Clarify the Core Hypothesis - Help the… → Select a Validation Path - Guide the… → Design Low-Fidelity Experiments -… → …
  • Tasks that involve UI design
  • SKILL.md covers How to Help, Core Principles, Templates & Frameworks and Questions to Help Users, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Idea Validation is an agent skill from RefoundAI/lenny-skills. Help users de-risk new product bets by testing core assumptions, building low-fidelity prototypes, and gathering high-signal evidence before investing heavy engineering resources.

Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/artifacts.md` and `references/guest-insights.md`).

It sits in Frontend & Design, covering UI design. The repository describes itself as: 86 product management skills from Lenny's Podcast for Claude Code and AI agents. Hiring, user research, strategy, shipping, and more. The licence is MIT.

When your agent uses it

  • Tasks that involve UI design

Example prompts

  • “/idea-validation”

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Clarify the Core Hypothesis - Help the user define the specific problem, target audience, and the most 'risky' assumptions using the…
  2. Select a Validation Path - Guide the user through choosing between the 'Listening Path', 'Manual Path', or 'Self-Serve Path' based on…
  3. Design Low-Fidelity Experiments - Recommend specific 'Wizard of Oz' or 'Fake Door' tests to simulate the solution without building a…
  4. Evaluate Signal Quality - Help users distinguish between polite interest and real market pull by looking for financial commitment or…

What it can do on your machine

Read from SKILL.md and the folder at commit 13598cc. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Idea Validation loads about 1.5k tokens when it runs, and up to ~21k if it reads all its reference files. Until then it costs about 49 tokens; SKILL.md has 885 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~49
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~21k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from RefoundAI/lenny-skills at commit 13598cc, republished under its MIT licence (© RefoundAI). 885 words, ~1,531 tokens.

Download SKILL.mdSave it as .claude/skills/idea-validation/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
idea-validation
description
Help users de-risk new product bets by testing core assumptions, building low-fidelity prototypes, and gathering high-signal evidence before investing heavy engineering resources.

Idea Validation

Stop building things people don't want by moving from opinion to evidence-based development.

Help the user with idea validation using insights from 31 guests and posts across Lenny's Podcast and Newsletter.

How to Help

  1. Clarify the Core Hypothesis - Help the user define the specific problem, target audience, and the most 'risky' assumptions using the Founding Hypothesis Scorecard.
  2. Select a Validation Path - Guide the user through choosing between the 'Listening Path', 'Manual Path', or 'Self-Serve Path' based on their proximity to the problem.
  3. Design Low-Fidelity Experiments - Recommend specific 'Wizard of Oz' or 'Fake Door' tests to simulate the solution without building a backend.
  4. Evaluate Signal Quality - Help users distinguish between polite interest and real market pull by looking for financial commitment or high-effort usage.

Core Principles

First-Principles De-risking

Bangaly Kaba: "Someone says, 'Hey, you know what? This would be great to build.' And you go pull data to go justify why that would be great to build. Call that identify, justify, execute. First you have to really understand from first principles what is actually going on."

True de-risking starts with understanding the core problem from first principles before looking for data to justify a specific solution.

Maintaining Prototype Momentum

Grant Lee: "We would have an idea in the morning, come up with some sort of functional prototype, recruit a bunch of people that are legitimately good prospective users, but have zero skin in the game, ship fast so people can start playing with it. In the afternoon, we're already running pretty full scale experiment."

Build functional prototypes within hours of conceiving an idea to maintain speed and identify usability flaws before wasting development cycles.

Direct User Feedback Loops

Gustaf Alstromer: "If I drill down what makes companies fail, it's quite simple. It's just like they don't talk to users, which means they don't find product market fit. And if they don't find product market fit, nothing else really matters."

Achieve product-market fit by talking to customers directly and immediately to learn if you are building something people actually want.

Workflow Compression

Oji Udezue: "So the zone of benefit works as a framework because people will not pay for things that don't either really shrink the workflow that they're doing or doesn't give them superpower. So the same amount of time, but twice as much output. But the most important thing is that it has to be noticeable."

A problem is only worth building for if your solution offers a visible and massive compression of the existing customer workflow.

Show full SKILL.md (462 more words)Show less

Templates & Frameworks

  • Four B2B Idea Validation Paths (How to validate your B2B startup idea) - A framework for choosing which validation strategy to use based on your context as a founder. Each path represents a different level of up-front investment and
  • B2B Idea Validation Interview Process (How to validate your B2B startup idea) - A synthesized process for conducting validation interviews based on patterns across multiple successful B2B founders
  • Four Signs Your B2B Idea Has Real Pull (How to validate your B2B startup idea) - A checklist of signals that indicate genuine market demand vs. polite but hollow interest
  • Vanta's Manual Validation Process (How to validate your B2B startup idea) - How Christina Cacioppo validated Vanta's idea by manually creating SOC 2 compliance reports before writing any code
  • Founding Hypothesis Scorecard (Introducing the Foundation Sprint: From the creators of the Design Sprint) - A scorecard with testable questions for each element of the Founding Hypothesis, used to systematically validate or invalidate your product strategy
  • Pre-Product Invoice Test (How to know if you've got product-market fit) - A pre-product PMF validation technique where you literally try to get potential customers to pay you before the product exists.
  • Ugly Baby Validation (1,000,000) - A framework for getting early validation on a new creative project by finding the right motivators
  • DoorDash's paloaltodelivery.com MVP (How the biggest consumer apps got their first 1,000 users) - How DoorDash validated demand with a simple website with PDF menus and printed flyers at Stanford

See references/artifacts.md for the full list with details.

Questions to Help Users

  • "What is the single most risky assumption that must be true for this idea to succeed?"
  • "Are you getting feedback from cold prospects or just people in your network who want to be nice?"
  • "How many steps does your solution remove from the user's current manual workflow?"
  • "If you had to launch a 'fake door' experiment tomorrow with zero backend, what would it look like?"
  • "Has a potential customer offered to pay for this before you have even built it?"
  • "What is the 'must-have' feature that, if missing, would cause the user to walk away immediately?"

Common Mistakes to Flag

  • Confusing Politeness with Validation - Mistaking 'this looks cool' for 'I will pay for this' leads to building products that lack real market pull.
  • Building Before Testing - Investing heavy engineering resources into a full backend before validating the front-end value proposition wastes months of time.
  • Relying on Warm Leads - Feedback from friends or family is biased and rarely provides the 'pure' signal needed to judge an idea's merit.
  • Averaging User Feedback - Failing to segment feedback between skeptics and early adopters can lead to a watered-down product that serves nobody well.

Deep Dive

For all 33 sourced insights from 31 guests, see references/guest-insights.md

  • Customer Interviews
  • Continuous Discovery
  • Product Experiments
  • Defining Icp

© RefoundAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in skills/idea-validation of RefoundAI/lenny-skills.

  • SKILL.md
  • references/artifacts.md
  • references/guest-insights.md

Open the folder on GitHubat commit 13598cc

Compare with similar skills

Idea Validation next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Idea Validation compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Idea Validation this skillRefoundAI/lenny-skills1.4k—~1.5kAutomated safety check: PassMIT
UI StylingOhh-889/skyroc79513 repos~2.5kAutomated safety check: PassMIT
LobeHub Interactive Prototypelobehub/lobehub83k—~1.6kAutomated safety check: PassCustom licence
Make Interfaces Feel Bettersamuelclay/NewsBlur7.6k10 repos~1.5kAutomated safety check: PassMIT
UI UX Pro MaxZxBing0066/pixel-converter18113 repos~2.6kAutomated safety check: NotesBSD-2-Clause
Stitch Prompt Enhancergoogle-labs-code/stitch-skills8.4k6 repos~1.7kAutomated safety check: PassApache-2.0

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Questions about Idea Validation

What does Idea Validation do?

Help users de-risk new product bets by testing core assumptions, building low-fidelity prototypes, and gathering high-signal evidence before investing heavy engineering resources. Idea Validation is an agent skill from RefoundAI/lenny-skills. Help users de-risk new product bets by testing core assumptions, building low-fidelity prototypes, and gathering high-signal evidence before investing heavy engineering resources.

When should I use Idea Validation?

Idea Validation fits situations like: tasks that involve UI design.

How do I install Idea Validation in Claude Code?

Run `npx skills add RefoundAI/lenny-skills --skill idea-validation -a claude-code`. Or copy the skill folder (skills/idea-validation in RefoundAI/lenny-skills) into .claude/skills/idea-validation in your project. Claude Code loads it when a task matches its description.

How do I install Idea Validation in Codex?

Run `npx skills add RefoundAI/lenny-skills --skill idea-validation -a codex`. Or copy the skill folder (skills/idea-validation in RefoundAI/lenny-skills) into .agents/skills/idea-validation in your project. Codex loads it when a task matches its description.

Can I use Idea Validation in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add RefoundAI/lenny-skills --skill idea-validation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/idea-validation, .gemini/skills/idea-validation, .github/skills/idea-validation and .opencode/skills/idea-validation in your project.

What does Idea Validation need to run?

SKILL.md names no scripts, command-line tools or credentials: Idea Validation is instructions for the agent only.

Does Idea Validation access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Idea Validation safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Idea Validation use?

Idea Validation is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Idea Validation use?

About 1.5k tokens (SKILL.md is roughly 6.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 20k tokens, read only when the agent opens those files.

What are the alternatives to Idea Validation?

Skills that share tags, products or a category with Idea Validation: UI Styling (Ohh-889/skyroc, 795 stars), LobeHub Interactive Prototype (lobehub/lobehub, 83k stars), Make Interfaces Feel Better (samuelclay/NewsBlur, 7.6k stars) and UI UX Pro Max (ZxBing0066/pixel-converter, 181 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Idea Validation?

RefoundAI (a GitHub organization) maintains it in RefoundAI/lenny-skills, which has 1,377 GitHub stars. The repository holds 76 skills in this directory. The repository was last updated on July 16, 2026.

Source: RefoundAI/lenny-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.