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

@littlerobots/llm-vibecheck

v0.3.0

Published

A utility to compare LLM outputs

Downloads

21

Readme

README

When working with LLM outputs, it's often valuable to compare results when modifying prompts. While LLM benchmark frameworks exist, a simple "vibe check" can help a lot. This package provides a mini framework to produce a comparison of outputs by producing a csv file.

How to use

  • Make sure you have a set of input files. The format will depend on your Processor and Preprocessor implementation.
  • Create a Processor. The processor receives an arbitrary config object and outputs an object with the results. You'd typically call the code that invokes the LLM from this Processor, but you could also invoke webservice for example. The results end up as columns in the report. The output is also cached on disk for future runs.
  • (Optional) create Preprocessor that takes an input file and processes it to a suitable input for your Processor. Preprocessing happens once per file and the outputs are cached on disk.
  • (Optional) create an Evaluator that takes the input and output and runs whatever evaluation that you want. The result of the Evaluator is added as columns to the report.

Create the cli

import {
  runEvaluation,
  type Processor,
  type Preprocessor,
  type Evaluator,
} from "@littlerobots/llm-vibecheck";

// setup your processor, preprocessor and evaluator

await runEvaluation(processor, preprocessor, evaluator);

Create prompt config

A basic config will look like this:

{
  "prompts": [{ "name": "Base prompt" }]
}

The config object will be passed to the Processor and Evaluator as is. No properties are required, but if you add a name property it will be used in the report to name the prompt results.

Run the cli

When you run the cli without any arguments the output will be similar to this:

Options:
  -i, --input   Directory with input files                   [string] [required]
  -c, --config  Prompt config json file                      [string] [required]
  -o, --output  Output file                                  [string] [required]
      --cache   Directory used for caching inputs and outputs
            [string] [default: "/Users/you/myproject/.cache"]
      --help    Show help                                              [boolean]

Missing required arguments: input, config, output

Pass in the --input, --config and --output arguments to create the report.

Caching

Preprocessed inputs and prompt outputs are cached by default. This speeds up processing and saves cost running the same LLM prompts over and over again. Prompt output is cached based on the prompt configuration, e.g. if you change the prompt configuration this will be considered a new config. Likewise if you change your Processor implementation, but not the config you'll want to remove the outputs from the cache directory to re-run the prompt.

License

Copyright 2024 Hugo Visser

   Licensed under the Apache License, Version 2.0 (the "License");
   you may not use this file except in compliance with the License.
   You may obtain a copy of the License at

       http://www.apache.org/licenses/LICENSE-2.0

   Unless required by applicable law or agreed to in writing, software
   distributed under the License is distributed on an "AS IS" BASIS,
   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
   See the License for the specific language governing permissions and
   limitations under the License.