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OpenTest.AI
What it is
OpenTest.AI is a self-hosted project offering local AI quality checks and portable JSON formats for software testing. Its six skills address recent-change fixes, quality scanning, risk, confidence, smart comparisons, and metrics. The skills are described as running locally without an API key, cloud call, or account, and work with clients such as Claude Code, Cursor, Codex CLI, GitHub Copilot Chat, Aider, and Continue.dev.
The jank_deep skill scans 12 quality dimensions, including correctness, security, reliability, performance, maintainability, and testing. jank_risk traces code impact, GenAI smells, user frustration, and business risk; jank_confidence applies statistical test-coverage analysis and estimates the time and cost of closing gaps. The project also analyzes screenshots, network and console logs, and DOM or accessibility trees using 33+ specialized AI testing profiles. It supports bug detection, persona feedback, and prioritized test-case generation for pages or flows. Its v1 JSON formats are designed to pass between tools and people, and generated test cases can be replayed by Playwright, Selenium, Cypress, or a human. The MIT-licensed plan is free forever.
For and against
For
- Local operation requires no API key or account
- Six quality-check skills cover different review needs
- Analyzes screenshots, logs, and accessibility trees
- Test cases work with Playwright, Selenium, or Cypress
Against
- No mobile test generation is listed
- No API test generation is listed
- Self-hosted deployment is required
The verdict
OpenTest.AI brings a range of local quality checks and portable testing formats together in a free MIT-licensed project. Its listed capabilities focus on software changes, pages, and flows rather than mobile or API test generation.
Who it suits
It suits developers seeking local quality checks alongside AI coding clients, or teams that want portable test cases. Its described testing modes cover pages and flows, but not mobile test generation.
Plans and prices
Open source · MIT
MIT licensed · no API key · no cloud call · no account
Read 1 Oct 2026 · opentest.ai
On the record
- Additional services
- The site says jank.ai also offers cloud browser testing, URL monitoring dashboards, autonomous hunt-and-fix loops, and human-eye reviews.opentest.ai · read 1 Oct 2026
- AI client integrations
- The skills work with Claude Code, Cursor, Antigravity, Codex CLI, GitHub Copilot Chat, Aider, Continue.dev, and AGENTS.md-aware tools.opentest.ai · read 1 Oct 2026
- Auto-fix
- jank auto-fix finds bugs in recent changes and can work on code, documents, images, and Office files.opentest.ai · read 1 Oct 2026
- Bug detection
- The open-source project analyzes screenshots, network logs, console logs, and DOM or accessibility trees using 33+ specialized AI testing profiles.opentest.ai · read 1 Oct 2026
- 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.opentest.ai · read 1 Oct 2026
- Local operation
- The skills are described as pure-local and require no API key, cloud call, or account.opentest.ai · read 1 Oct 2026
- Metrics
- jank_stats reports cumulative tokens, cost, fixes by category, and estimated developer time and money saved.opentest.ai · read 1 Oct 2026
- Open skills
- The site lists six quality-check skills: jank auto-fix, jank_deep, jank_risk, jank_confidence, jank_diff, and jank_stats.opentest.ai · read 1 Oct 2026
- Portable formats
- OpenTest.AI publishes v1 JSON formats for bugs and test cases designed to move between finders, runners, fixers, and humans.opentest.ai · read 1 Oct 2026
- Product purpose
- OpenTest.AI provides local-first AI quality checks and portable JSON formats for AI-era software testing.opentest.ai · read 1 Oct 2026
- Quality scan
- jank_deep performs a full scan across 12 quality dimensions including correctness, security, reliability, performance, maintainability, and testing.opentest.ai · read 1 Oct 2026
- Risk analysis
- jank_risk traces changes across code blast radius, GenAI smells, user frustration, and business risk.opentest.ai · read 1 Oct 2026
- Runner interoperability
- The test-case format can be replayed by Playwright, Selenium, Cypress, or a human.opentest.ai · read 1 Oct 2026
- Smart diff
- jank_diff compares APIs, documents, or local files while ignoring timestamps, dynamic IDs, and generated metadata noise.opentest.ai · read 1 Oct 2026
- Testing modes
- The project supports bug detection, persona feedback, and prioritized test-case generation for pages or flows.opentest.ai · read 1 Oct 2026
