OpenTest.AI

6.9easy start · #10 of 21
in AI Test Case Generators

Free to practise onyes
Free trialnot on record
Well documentedyes
Runs where you worknot on record

Runs on self-hosted.

OpenTest.AI is ranked #10 of 21 in AI test case generators on The Geeks Club. It runs on Self-hosted. There is a free plan.

OpenTest.AI plans and pricing

All plans

Open source · MIT Free free forever MIT licensed · no API key · no cloud call · no account opentest.ai · 1 Oct 2026

Compared on AI test case generators

Free plan: Yes
Requirements input: No
Existing app input: Yes
Acceptance criteria: No
Browser test generation: Yes
API test generation: No
Mobile test generation: No

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The record

Product purpose: OpenTest.AI provides local-first AI quality checks and portable JSON formats for AI-era software testing.
Open skills: The site lists six quality-check skills: jank auto-fix, jank_deep, jank_risk, jank_confidence, jank_diff, and jank_stats.
AI client integrations: The skills work with Claude Code, Cursor, Antigravity, Codex CLI, GitHub Copilot Chat, Aider, Continue.dev, and AGENTS.md-aware tools.
Local operation: The skills are described as pure-local and require no API key, cloud call, or account.
Auto-fix: jank auto-fix finds bugs in recent changes and can work on code, documents, images, and Office files.
Quality scan: jank_deep performs a full scan across 12 quality dimensions including correctness, security, reliability, performance, maintainability, and testing.
Risk analysis: jank_risk traces changes across code blast radius, GenAI smells, user frustration, and business risk.
Confidence analysis: jank_confidence uses statistical test-coverage analysis with t-tests, p-values, and sampling, and estimates the cost and time to close gaps.
Smart diff: jank_diff compares APIs, documents, or local files while ignoring timestamps, dynamic IDs, and generated metadata noise.
Metrics: jank_stats reports cumulative tokens, cost, fixes by category, and estimated developer time and money saved.
Portable formats: OpenTest.AI publishes v1 JSON formats for bugs and test cases designed to move between finders, runners, fixers, and humans.
Bug detection: The open-source project analyzes screenshots, network logs, console logs, and DOM or accessibility trees using 33+ specialized AI testing profiles.
Testing modes: The project supports bug detection, persona feedback, and prioritized test-case generation for pages or flows.
Runner interoperability: The test-case format can be replayed by Playwright, Selenium, Cypress, or a human.
Price from: Free

Where it ranks on The Geeks Club

Best AI Test Case Generators in 2026#10 of 21

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Sources

opentest.ai· checked 1 Oct 2026