measuring-product-market-fit

measuring-product-market-fit is a skill for Claude Code, Codex from liqiongyu/lenny_skills_plus. It costs 38 tokens per session (2,499 once invoked), scanned A, original, Apache-2.0.

A product-planning guide for measuring product-market fit, meaning whether a product meets a strong and lasting customer need. It combines customer surveys, continued usage over time, and customer recommendations.

In plain words
What is it for?
Running and interpreting the Sean Ellis “Very Disappointed” survey, examining retention by customer group, checking reference-customer signals, detecting changes in fit, and deciding whether to scale growth.
Why use it?
It helps teams judge product-market fit using several types of evidence instead of relying on one survey or a single growth number.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Running and interpreting the Sean Ellis “Very Disappointed” survey, examining retention by customer group, checking reference-customer signals, detecting changes in fit, and deciding whether to scale growth.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/liqiongyu/lenny_skills_plus/measuring-product-market-fit
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add liqiongyu/lenny_skills_plus --skill measuring-product-market-fit
Clone the repo
git clone --depth 1 https://github.com/liqiongyu/lenny_skills_plus

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for measuring-product-market-fit

README.md
[![agentmods](https://agentmods.dev/badge/skills/liqiongyu/lenny_skills_plus/measuring-product-market-fit/github.svg)](https://agentmods.dev/skills/liqiongyu/lenny_skills_plus/measuring-product-market-fit)
Your own site
<a href="https://agentmods.dev/skills/liqiongyu/lenny_skills_plus/measuring-product-market-fit"><img src="https://agentmods.dev/badge/skills/liqiongyu/lenny_skills_plus/measuring-product-market-fit/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for measuring-product-market-fit

Your own site · 80×15
<a href="https://agentmods.dev/skills/liqiongyu/lenny_skills_plus/measuring-product-market-fit"><img src="https://agentmods.dev/badge/skills/liqiongyu/lenny_skills_plus/measuring-product-market-fit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 38 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,499 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00038 $0.02499
Opus 5 $0.00019 $0.01249
Sonnet 5 $0.00008 $0.00500
Haiku 4.5 $0.00004 $0.00250

Measured 12d ago against content hash 7d98c9e66ecb, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

measuring-product-market-fit scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/measuring-product-market-fit/SKILL.md · 158 lines

How it starts

The opening of the file, as written. The whole thing — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Measuring Product-Market Fit

Scope

Covers

  • Measuring PMF using a triangulated signal set (survey + behavior + customer evidence)
  • Running and interpreting the Sean Ellis "Very Disappointed" survey (overall + by segment)
  • Reading retention curves / cohort retention as PMF evidence (and knowing when they mislead)
  • Using reference-customer / advocacy signals as an additional PMF proxy
  • Detecting PMF drift (market shifts, rising expectations, competitive resets) and setting a re-measurement cadence
  • Special handling for marketplaces (measure PMF per side; focus on the "hard side" first)

When to use

  • "Do we have PMF? For which segment?"
  • "Run a Sean Ellis PMF survey and tell me what it means."
  • "Build a PMF scorecard with retention + survey + references."
  • "Our market shifted—did we lose PMF?"
  • "We want a go/no-go signal for scaling growth spend or launching publicly."

When NOT to use

  • You haven’t defined the problem/ICP yet (use problem-definition).
  • You only need a survey instrument, not a full PMF measurement system (use designing-surveys).
  • You’re deciding whether/how to pivot (use startup-pivoting) rather than measuring PMF signals.
  • You need a product vision/strategy doc as the primary output (use defining-product-vision / ai-product-strategy).
  • You already have PMF and need to optimize retention or engagement (use retention-engagement); this skill measures PMF, not post-PMF growth levers.
  • You need to brainstorm or validate new startup ideas (use startup-ideation); this skill assumes a product already exists with real users.
  • You want to define or refine a north-star metric for an established product (use writing-north-star-metrics); this skill uses metrics as PMF evidence, not as a metric-design exercise.

Inputs

Minimum required

  • Product + category + current stage (pre-PMF / early PMF / growth / mature)
  • Business model: B2B / B2C / marketplace (and, for marketplaces, which side you’re focusing on)
  • Your current best guess at the target segment/ICP (and any meaningful segments)
  • Definition of active user and the core value moment (the action that indicates value received)
  • What data you can access: survey channels, product analytics, retention cohorts, revenue, qualitative feedback, reference customers/testimonials
  • Time horizon and constraints (deadline, privacy/PII constraints, internal-only vs shareable)

Read the full file on GitHub · 158 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 158 lines · 38 tokens per session scan A 7d98c9e66ecb

Subscribe to this mod's changes

measuring-product-market-fit is a skill published in the GitHub repository liqiongyu/lenny_skills_plus (52 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 38 tokens to every session and 2,499 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

cangjie-skill

A process for turning a book, course, podcast, interview, long video, or other long material into reusable instructions for an AI agent. It extracts methods and principles, checks them, and packages them as skills.

kangarooking/cangjie-skill · 143 tokens

plan

Use when a request needs shaping before any code is written — a rough or vague prompt to sharpen, an ambiguous idea to design, or a clear-enough task to decompose. One chain-starter that amplifies the prompt, designs the approach, and decomposes it into a batched task file, skipping whichever phases the request…

jeremylongshore/tons-of-skills-marketplace · 144 tokens

loop-library

Compatibility alias for Loopy. Use only when an existing installation or older instruction explicitly invokes loop-library; use Loopy for new installations and requests. Provides the same discovery, recommendation, audit, repair, adaptation, guided crafting, bounded execution, run debrief, project loop saving, and…

Forward-Future/loopy · 65 tokens

naval-almanack

A reference guide for applying ideas from The Almanack of Naval Ravikant, a book about wealth, work, happiness, judgment, and long-term thinking. It routes questions to the relevant topic guidance and notes when professional help is needed.

kangarooking/cangjie-skill · 255 tokens

decision-heuristics

A set of heuristics for making difficult personal decisions such as changing jobs, buying a home, moving, forming a partnership, or getting married. It is intended for major choices, not everyday decisions.

kangarooking/cangjie-skill · 136 tokens

hourly-rate-time

A time-management method based on assigning a high personal value to each hour. It treats time as a limited resource and uses that value to decide which tasks to do, outsource, or skip.

kangarooking/cangjie-skill · 146 tokens