npm package discovery and stats viewer.

Discover Tips

  • General search

    [free text search, go nuts!]

  • Package details

    pkg:[package-name]

  • User packages

    @[username]

Sponsor

Optimize Toolset

I’ve always been into building performant and accessible sites, but lately I’ve been taking it extremely seriously. So much so that I’ve been building a tool to help me optimize and monitor the sites that I build to make sure that I’m making an attempt to offer the best experience to those who visit them. If you’re into performant, accessible and SEO friendly sites, you might like it too! You can check it out at Optimize Toolset.

About

Hi, 👋, I’m Ryan Hefner  and I built this site for me, and you! The goal of this site was to provide an easy way for me to check the stats on my npm packages, both for prioritizing issues and updates, and to give me a little kick in the pants to keep up on stuff.

As I was building it, I realized that I was actually using the tool to build the tool, and figured I might as well put this out there and hopefully others will find it to be a fast and useful way to search and browse npm packages as I have.

If you’re interested in other things I’m working on, follow me on Twitter or check out the open source projects I’ve been publishing on GitHub.

I am also working on a Twitter bot for this site to tweet the most popular, newest, random packages from npm. Please follow that account now and it will start sending out packages soon–ish.

Open Software & Tools

This site wouldn’t be possible without the immense generosity and tireless efforts from the people who make contributions to the world and share their work via open source initiatives. Thank you 🙏

© 2026 – Pkg Stats / Ryan Hefner

getlewn

v0.1.0

Published

Poll a calibrated panel of synthetic respondents from your code — the official lewn (Lewis) SDK.

Readme

lewn

Poll a calibrated panel of synthetic respondents from your code. Ask any question, get back how a population actually splits — with an honest confidence read and panel composition.

npm install getlewn

Quick start

import { Lewn } from "getlewn";

const lewn = new Lewn({ apiKey: process.env.LEWN_API_KEY! });

const res = await lewn.poll({
  question: "Would you pay $15/mo for an AI calendar assistant?",
  options: ["Yes", "No", "Maybe"],
  audience: { market: "national_us", n: 300 },
});

console.log(res.summary);
// "Among US adults (n=300), Yes leads at 38% (vs No 34%, Maybe 28%). Directional read."
console.log(res.distribution);
// [ { option: "Yes", pct: 38.2, count: 115 }, ... ]
console.log(res.confidence);       // { score: 0.62, label: "Directional", tier: "amber" }
console.log(res.panel_composition); // { n_real: 150, n_synthetic: 150, n_total: 300, ... }

res.summary is a ready-to-print sentence — great for logging or handing straight to a coding agent. Everything else (res.distribution, res.confidence, res.panel_composition) is the structured detail.

Get an API key at https://lewn.ai/developers (Pro and Research plans).

Calibrated vs. free-form

  • Pass 2–6 options → a calibrated multiple-choice read (the trustworthy path; benchmarked against Pew/Gallup).
  • Omit options → an uncalibrated free-form read (directional only, no numeric accuracy claim).

Always check res.confidence.tier before leaning on a number.

API

new Lewn({ apiKey, baseUrl?, timeout? })

  • apiKey — your sk-lew-... key (required).
  • baseUrl — defaults to https://lewn.ai/api/v1.
  • timeout — ms, default 60000.

lewn.poll(params) → Promise<PollResult>

  • question: string (required)
  • options?: string[] — 2–6 for calibrated MC
  • audience?: { market?: string; n?: number } — e.g. market: "national_us" | "atlanta" | "texas"; n is clamped to your plan's per-query max
  • requestId?: string — idempotency key (a retried request bills once)

Errors throw LewnError with .status and .code (UNAUTHORIZED, FORBIDDEN, RATE_LIMITED, TIMEOUT, API_ERROR, …).

Billing

Metered by respondents queried against your plan's monthly pool. res.usage shows respondents_billed, month_used, and month_limit. Per-query size and rate scale with your plan (Pro $70 / Research $200).


Made by lewn · synthetic respondents are estimates, not guarantees.