Docs

Introduction

How Projektor can make debugging test failures in CI faster and easier

Getting started

Getting started with Projektor test reports

Code coverage

Viewing code coverage stats and trends

Performance tests

View performance test results with Projektor, both individual test runs and performance graphed over time

Flaky test detection

Flaky test detection with Projektor

Test failure insights

Group failures by root cause, catch tests that got slower, and see a test’s pass/fail history

GitHub PR comments

Quickly access Projektor reports through automatic GitHub pull request comments

Readme badges

Badge for project readme with code coverage stats

Slack notifications

Get notified in Slack when your mainline build goes red, coverage drops, or a test becomes flaky

AI test failure analysis

Get AI-generated hints on why a test failed, using OpenAI or Anthropic Claude

MCP server

Query Projektor test failure data from AI coding assistants via its MCP server

Code quality

View code quality reports in Projektor

Gradle plugin

Gradle plugin for easily publishing test results and code coverage statistics to Projektor

Node script

Node script for publishing Javascript results to Projektor

GitHub Action

GitHub Action for publishing test results, coverage, and attachments to Projektor from GitHub Actions workflows

Jest tests

Configuring Jest tests to write results for Projektor

Object store persistence

Run the Projektor server with an S3-compatible object store instead of Postgres

Server

Configuring and running the Projektor server

API

Programmatically access Projektor data via a REST API

Architecture

How Projektor’s components fit together