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Nova AI QA Engineer

An AI QA engineer that proves the bug before filing it

Productivity
SaaS
Developer Tools
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Hunted byİBRAHİM GAZALOĞLUİBRAHİM GAZALOĞLU

Give it an OpenAPI URL or your Gherkin feature files. The AI designs the tests a careful tester would run — boundary values, business-rule violations, hostile inputs — and runs them against your API and your UI: it compiles scenarios into real API calls, drives a browser it has never seen, and reviews what your app accepted. Deterministic oracles decide what counts as a bug, every finding is reproduced 3x, and issues open and close themselves. No API key: your local Claude Code CLI just works.

Top comment

Hi Product Hunt 👋 novaqa is an AI QA engineer. Give it an OpenAPI URL or your feature files and it works the way a new tester would on their first week: designs the tests, runs them against your API and your UI, works out which results actually matter, and files the bugs. Concretely, here's what the AI does: It reads your feature files and designs the nasty version of every scenario. A scenario mentioning "a product priced 79.99, stock 5" becomes -79.99, 0, 1e18, "79.99" as a string, stock -1, an empty name, a 10,000-character name, injection-shaped strings, missing required fields, and the business rules the domain implies. It decides how many cases each scenario deserves — a checkout flow earns more than a health check. With no feature files it works from each request's JSON Schema; on read-only endpoints it designs hostile path and query parameters instead. It runs the same scenarios everywhere — no glue code. Normally a .feature file is dead weight until someone writes step bindings. novaqa hands the scenario text to the model and gets back concrete actions: ordered HTTP calls against your API, or clicks and form-fills against your UI — it reads the page's interactive elements and drives a browser it has never seen, no selectors written by hand. Drop a .feature in and it runs, on both sides of your stack. It reviews what your app accepted. A 2xx is the easiest place for a bug to hide — the wrong price echoed back, a field silently dropped, a total that doesn't add up. In the browser it also catches console errors, uncaught exceptions, and visual regressions against committed baselines. Response bodies are redacted before anything leaves for a model. It writes the analyst summary — recurring root-cause themes, highest risk first, at the top of the report. And it runs with no API key. Three providers: ANTHROPIC_API_KEY, GEMINI_API_KEY, or — the one I'd point you at — your local Claude Code CLI. If claude is on your PATH, novaqa finds it and uses it: full AI on your own subscription, no key to provision, no per-run cost, nothing routed through me. With none of the three it degrades to the deterministic engine and says so on the status line. It never fails a run over a missing key. Why I'm comfortable putting AI on the front page: the model proposes, it never decides. Every AI-proposed request is matched against your OpenAPI spec before it's sent, and browser actions come from a closed vocabulary the runner executes — the model can't invent one. A prompt-injected feature file can't steer traffic at anything you didn't declare. Verdicts come from deterministic oracles — 5xx, schema violation, invalid input accepted, a failed assertion on the page — never from the model. Everything is re-run three times before you see it, in the browser as well as against the API. Anything that doesn't hold up is marked unconfirmed instead of filed. A bug's identity excludes the AI's wording, so the model rephrasing a case tomorrow can't re-file something you already have — and an issue only closes if the run actually re-tried it. "We didn't look" never reads as "it's fixed." Read-only by default. It won't write to your API until you allow it, and it refuses any writing mode against environment: "production" with no override flag. Point it at a test environment and set safety.mode: "safe-write" — that's where the AI earns its keep, because that's where it can send the inputs it designed. Two honest notes. It's source-available, not open source — Functional Source License, free for everything except building a competing product, converting to Apache-2.0 two years after each release. I switched while the project had zero users, because doing it later, once people depend on you, is what burns trust. And there's a runnable example ecosystem in the repo: two deliberately broken services and a storefront, one docker compose up, so you can see what it finds without pointing it at anything you care about. I'd genuinely like to know what it finds in your app — and where it's wrong.

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About Nova AI QA Engineer on Product Hunt

An AI QA engineer that proves the bug before filing it

Nova AI QA Engineer was submitted on Product Hunt and earned 5 upvotes and 1 comments, placing #32 on the daily leaderboard. Give it an OpenAPI URL or your Gherkin feature files. The AI designs the tests a careful tester would run — boundary values, business-rule violations, hostile inputs — and runs them against your API and your UI: it compiles scenarios into real API calls, drives a browser it has never seen, and reviews what your app accepted. Deterministic oracles decide what counts as a bug, every finding is reproduced 3x, and issues open and close themselves. No API key: your local Claude Code CLI just works.

Nova AI QA Engineer was featured in Productivity (658.2k followers), SaaS (43.6k followers) and Developer Tools (517.4k followers) on Product Hunt. Together, these topics include over 284.1k products, making this a competitive space to launch in.

Who hunted Nova AI QA Engineer?

Nova AI QA Engineer was hunted by İBRAHİM GAZALOĞLU. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.

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