Kilotest

An ensemble testing and reporting service for front-end web quality

Features

This application uses an ensemble of 12 rule engines to test web pages for front-end quality (i.e. accessibility, usability, and standards conformity).

The testing paradigm employed by Kilotest is discussed in these papers:

• How to run a thousand accessibility tests
• Testaro: Efficient Ensemble Testing for Web Accessibility
• Accessibility Metatesting: Comparing Nine Testing Tools

Kilotest acts as a web server for human users, an MCP server for AI platforms, and an API for programmatic access.

Testing for Kilotest is performed by one or more workers (testing agents) that obtain jobs from Kilotest, perform them, and send reports of the results back to Kilotest. Those agents are instances of the Testaro package. Thus, the pages that Kilotest tests need not be on the public Internet. They need only be reachable by the Testaro workers that do the testing for Kilotest. So, one or more Testaro workers running inside a private intranet can test internal pages, as well as any external ones reachable from inside the intranet.

An active production instance of Kilotest may require multiple Testaro workers to handle the load, because testing one web page typically takes about 3 minutes and workers test only one page at a time.

Getting started locally with 1 worker

Installation

In the steps below, hosts T and K may be the same host or two different hosts. Host T can be a Debian stable, Ubuntu LTS, Windows, or macOS host. Host K can be any server host that can run the latest LTS version of Node.js. If hosts T and K differ, then they must be open to https traffic and host K must permit https requests from host T.

1. Clone the Testaro project into a new directory on host T.
2. In that directory, install the Testaro dependencies: npm install.
3. Update the Testaro dependencies and rebuild: npm run deps.
4. Clone the Kilotest repository into a new directory on host K.
5. In that directory, install the Kilotest dependencies: npm install.
6. Copy the env.testaro file from the kilotest directory to .env in the testaro directory and replace the __placeholder__ values in .env with actual values.
7. Copy the env.example file in the kilotest directory to a new .env file in the same directory and replace the __placeholder__ values in .env with actual values. TESTARO_WORKERS is a JSON object mapping each Testaro worker's ID to an object with its secret and its name; the ID and secret for a worker must match the NETWATCH_URL_WORKER_ID and NETWATCH_URL_AUTH values in that worker's .env. A worker authenticates each request with an HTTP Basic Authorization header (id:secret, base64-encoded); as of this writing that header is not yet sent by the published Testaro package, so this scheme requires a matching update to Testaro's netWatch.js request code (only to send the header; no change to Testaro's handling of jobs or reports is needed). The ID is a credential and is never published; the name is written by Kilotest into a job's and report's sources.worker property, which Testaro does not read or alter, so it is a distinct property from sources.agent (Testaro's own, untrusted, self-reported label, which Kilotest ignores). Choose a name that is safe to appear in every report Kilotest serves. ALLOW_INTERNAL_TARGETS controls whether this deployment can be induced to test pages at private, loopback, or link-local addresses; see SERVICE.md before changing it from its default.

Usage

1. In the testaro directory, make Testaro start listening for jobs: node call netWatch true nn true, where nn is the number of seconds to wait between checks for new jobs. Note that Kilotest promises nearly immediate review and, on approval, immediate execution of “orders” for tests and retests, with typical total elapsed time about 2 minutes. That promise implies a promise to keep nn small. A reasonable value is between 10 and 20.
2. In the kilotest directory, start the Kilotest service: node index.

Contributing

Contributions are welcome! You can use GitHub issues to initiate discussions and propose changes. If you want to contribute code, please fork the repository and create a pull request.

Making Kilotest a service

See the SERVICE.md file for instructions on how to make Kilotest a service.

Using Kilotest as an AI tool

Kilotest is not only a web application but also an API and an MCP server. AI platforms and models can use Kilotest via those interfaces.

The URL for models using the MCP server is https://kilotest.com/mcp. The MCP server is listed at these services:

• Smithery
• Glama

There is additional documentation at:

• QAI: a tutorial for allowing AI assistants to use Kilotest
• AI-TOOLS.md: how Kilotest implements the MCP protocol
• Summary of Kilotest capabilities
• llms.txt: basic documentation for LLMs
• llms-full.txt: comprehensive documentation for LLMs
• lhm.plugin.json: documentation for registration with the LobeHub MCP Market