Agent skill

Measuring Pmf

by RefoundAI in RefoundAI/lenny-skills

Help users objectively assess where their product stands on the PMF spectrum by triangulating qualitative feedback, quantitative retention benchmarks, and organic growth signals.

MITAuto-check passedProduct & Project Management

Install Measuring Pmf

skills CLI
$ npx skills add RefoundAI/lenny-skills --skill measuring-pmf -a claude-code

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

GitHub CLI
$ gh skill install RefoundAI/lenny-skills measuring-pmf --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/measuring-pmf .claude/skills/measuring-pmf && 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
measuring-pmf
GitHub stars
1.4k
Token cost
~1.9k tokens
SKILL.md length
1,112 words
Files
3 (incl. references)
Skills in repo
76
Repo updated
First seen
Licence
MIT

At a glance

Help users objectively assess where their product stands on the PMF spectrum by triangulating qualitative feedback, quantitative retention benchmarks, and organic growth signals.

  • Works in 4 steps: Diagnose the current stage - Determine… → Apply quantitative benchmarks - Evaluate… → Analyze market pull - Identify signals… → …
  • Tasks that involve Product strategy
  • 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

Measuring Pmf is an agent skill from RefoundAI/lenny-skills. Help users objectively assess where their product stands on the PMF spectrum by triangulating qualitative feedback, quantitative retention benchmarks, and organic growth signals.

Its SKILL.md is about 1.9k 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 Product & Project Management, covering Product strategy. 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 Product strategy

Example prompts

  • “/measuring-pmf”

Workflow steps

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

  1. Diagnose the current stage - Determine where the user is on the journey from pre-product validation to scalable growth.
  2. Apply quantitative benchmarks - Evaluate cohort retention and Sean Ellis scores against industry standards.
  3. Analyze market pull - Identify signals of organic demand versus founder-led momentum.
  4. Iterate based on feedback - Help prioritize roadmap changes that specifically drive toward retention for the most passionate users.

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

Measuring Pmf loads about 1.9k tokens when it runs, and up to ~41k if it reads all its reference files. Until then it costs about 48 tokens; SKILL.md has 1,112 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~48
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~41k

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). 1,112 words, ~1,919 tokens.

Download SKILL.mdSave it as .claude/skills/measuring-pmf/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
measuring-pmf
description
Help users objectively assess where their product stands on the PMF spectrum by triangulating qualitative feedback, quantitative retention benchmarks, and organic growth signals.

Measuring Product-Market Fit

Transition from pushing your product to feeling the market pull it out of you.

Help the user with measuring product-market fit using insights from 16 guests and posts across Lenny's Podcast and Newsletter.

How to Help

  1. Diagnose the current stage - Determine where the user is on the journey from pre-product validation to scalable growth.
  2. Apply quantitative benchmarks - Evaluate cohort retention and Sean Ellis scores against industry standards.
  3. Analyze market pull - Identify signals of organic demand versus founder-led momentum.
  4. Iterate based on feedback - Help prioritize roadmap changes that specifically drive toward retention for the most passionate users.

Core Principles

Standardize Quantitative Validation

Jag Duggal: "We rarely scale a project, a product we've launched, until we know the Sean Ellis score and we know that it's hit a threshold that we find really compelling."

Use an objective threshold like the Sean Ellis score to validate fit before scaling. Set a strict target of at least 40 percent of users feeling very disappointed if the product disappeared.

Look for Urgent Feedback

Raaz Herzberg: "We really felt the type of questions change, right? Silly. The call sounded like, again, "How are you pricing this, or when can we start doing a POV?" I think naturally, as human beings, you have a bias to look for affirmation, versus a bias for what you don't want to hear."

True fit is revealed when customer feedback shifts from polite interest to urgent, practical questions about pricing and implementation. Treat generic interest as a negative signal.

Listen Selectively

Rahul Vohra: "You have to deliberately not act on the feedback of many of your early users, and this is at the same time as listening to people intensely and building what people want."

Ignore feedback from most users to focus exclusively on the segment that would be very disappointed without your product. Double down on what that specific cohort loves.

Prioritize Retention Above All

From "How to kickstart and scale a consumer business—Step 5: RETAIN: Iterate until enough people stick around": "Do whatever is required to get to product-market fit. Including changing out people, rewriting your product, moving into a different market, telling customers no when you don’t want to, telling customers yes when you don’t want to, raising that fourth round of highly dilutive venture capital—whatever is required."

Iterating toward fit requires an obsessive focus on retention signals. Be prepared to rewrite the product or switch markets if your cohort retention curves do not eventually flatten.

Differentiate Organic Pull

Grant Lee: "And then we'd look at signups, and you'd get that initial spike in signups, and then they sort of flatten out. We were still getting new users every day, but it was clear we didn't have strong word of mouth. There wasn't strong organic virality."

Measure the delta between temporary launch spikes and your long-term organic baseline. True fit is characterized by sustained word-of-mouth growth rather than marketing-driven peaks.

Acknowledge Macro Shifts

Adam Grenier: "Start by assuming you no longer have product market fit, because you had product market fit in a different market. It's a different market now, so you have to start over."

Assume previous product-market fit is lost when entering a significantly changed macroeconomic environment. Shifts in the market can fundamentally alter your customer base and their needs.

Sequence Your Optimization

Todd Jackson: "We've published dozens of articles on the First Round Review, and we have found a very consistent set of patterns, demand satisfaction, and efficiency. But the interesting thing is that you don't go for all three of them from the very beginning."

Finding fit is a sequential journey that starts with demand, moves to satisfaction, and finally focuses on efficiency. Do not try to optimize for efficiency until you have proven satisfaction.

Show full SKILL.md (484 more words)Show less

Templates & Frameworks

  • PMF Signal Hierarchy (Pre-Product and Post-Product) (How to know if you've got product-market fit) - A structured taxonomy of product-market fit signals organized into pre-product (2 signals) and post-product (7 signals), sorted from most concrete/measurable to
  • PMF Signal Checklist (A guide for finding product-market fit in B2B) - A list of signals that indicate you're approaching or have achieved product-market fit, compiled from founder interviews.
  • PMF Survey (100+ Users) (What to ask your users about Product-Market Fit) - A three-question survey template for assessing product-market fit when you have 100+ active users
  • PMF Level Benchmarks Dashboard (Todd Jackson) - Quantitative benchmarks for each of the four PMF levels across key metrics
  • Cohort Retention Curve Analysis for PMF (How to know if you've got product-market fit) - A method for determining product-market fit by plotting cohort retention over time and checking if the curve flattens rather than declining to zero.
  • PMF is a Spectrum, Not Binary (A guide for finding product-market fit in B2B) - The mental model that product-market fit is never a yes/no state but a continuous process of finding fit with larger market segments.
  • Five PMF Journey Archetypes (How to kickstart and scale a consumer business—Step 5: RETAIN: Iterate until enough people stick around) - Five patterns (plus one sad one) that describe how consumer companies typically find product-market fit over time
  • 5-Step B2B Product-Market Fit Progression (A guide for finding product-market fit in B2B) - A progressive framework for moving toward product-market fit in B2B, derived from interviews with 20+ successful founders. Each step represents a deeper level o

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

Questions to Help Users

  • "What percentage of your users would be very disappointed if your product stopped existing today?"
  • "Are your cohort retention curves flattening above zero percent, or do they continue to drop over time?"
  • "Is your growth currently being pushed by marketing spend or pulled by organic word-of-mouth?"
  • "When you talk to customers, are they asking polite questions or urgent questions about pricing and implementation?"
  • "How much of your current growth comes from personal relationships versus customers with no connection to the founders?"
  • "Can you identify a specific segment of users who use the product significantly more than others?"

Common Mistakes to Flag

  • Confusing support with demand - Founders often mistake personal encouragement from their network or investor confidence for actual market pull.
  • Scaling before retention flattens - Increasing headcount or marketing spend before you have a stable cohort of retained users leads to high burn and eventual failure.
  • Solving for every user - Trying to satisfy the feedback of every trial user dilutes the product for the core segment that actually finds value.
  • Ignoring the two-year timeline - Startups often give up too early, failing to realize that reaching product-market fit typically requires at least two years of iteration.

Deep Dive

For all 50 sourced insights from 16 guests, see references/guest-insights.md

  • Defining Product Strategy
  • Product Vision
  • Positioning
  • Pricing Strategy

© 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/measuring-pmf of RefoundAI/lenny-skills.

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

Open the folder on GitHubat commit 13598cc

Compare with similar skills

Measuring Pmf 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.

Measuring Pmf compared with similar skills
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Organic Growth Path Advisordeanpeters/Product-Manager-Skills7.2k2 repos~5.2kAutomated safety check: PassCustom licence
Product Strategistalirezarezvani/claude-skills28k2 repos~1.8kAutomated safety check: PassMIT
PlaidBuildGreatProducts/plaid217—~1.6kAutomated safety check: PassMIT

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Questions about Measuring Pmf

What does Measuring Pmf do?

Help users objectively assess where their product stands on the PMF spectrum by triangulating qualitative feedback, quantitative retention benchmarks, and organic growth signals. Measuring Pmf is an agent skill from RefoundAI/lenny-skills. Help users objectively assess where their product stands on the PMF spectrum by triangulating qualitative feedback, quantitative retention benchmarks, and organic growth signals.

When should I use Measuring Pmf?

Measuring Pmf fits situations like: tasks that involve Product strategy.

How do I install Measuring Pmf in Claude Code?

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

How do I install Measuring Pmf in Codex?

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

Can I use Measuring Pmf 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 measuring-pmf -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/measuring-pmf, .gemini/skills/measuring-pmf, .github/skills/measuring-pmf and .opencode/skills/measuring-pmf in your project.

What does Measuring Pmf need to run?

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

Does Measuring Pmf 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 Measuring Pmf 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 Measuring Pmf use?

Measuring Pmf 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 Measuring Pmf use?

About 1.9k tokens (SKILL.md is roughly 7.7k 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 39k tokens, read only when the agent opens those files.

What are the alternatives to Measuring Pmf?

Skills that share tags, products or a category with Measuring Pmf: Game Changing Features (openstatusHQ/data-table-filters, 2.3k stars), Company Research Brief (deanpeters/Product-Manager-Skills, 7.2k stars), Organic Growth Path Advisor (deanpeters/Product-Manager-Skills, 7.2k stars) and Product Strategist (alirezarezvani/claude-skills, 28k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Measuring Pmf?

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.