LiveVariant

Creates a LiveVariant test and returns every URL needed to run it, plus a freshly generated stats secret. Pass `variants` to test one element, or `slots` to test several at once (hero image AND call-to-action, say). With slots the test optimizes the COMBINATION: one model learns how the elements interact, which two separate tests structurally cannot see. There is no algorithm to pick either way; every test runs the same joint model, sized from its shape. By default, nothing is registered anywhere: the config IS the test, encoded into the URLs, and the test's identity is a hash of it. Pass `publishableKey` on an account-enabled deployment to also register the new test to that key's organization, so it appears under My tests; the config and URLs are still the test, and registration failure is returned as a warning rather than failing the build. Editing a variant later produces a DIFFERENT test with its own empty history, which is usually what you want per campaign but is worth saying out loud to whoever you are building this for. The stats secret is returned once and never again. Only its hash goes into the config, so nobody, including this service, can recover it. Give it to the person who will read the results.

Takes YOUR estimate of how each variant will perform and converts it into the prior the model starts from, so a test does not spend its first visitors rediscovering what you already suspect. You supply the guess; this does the arithmetic and the capping. That capping is the point: a prior is expressed as pseudo-observations, and it is deliberately held weak enough that real data overrides it quickly. The response says exactly how many real visitors per variant it takes to wash your guess out, so you can judge whether you have been too confident. Being wrong here costs a little early traffic, not the test. Priors are outside the identity hash, so the test keeps its id, its URLs and any history it already has. Pass `when` to make the belief hold for ONE segment only ("image B is the one for the blue segment"). Without it the belief is about every visitor, which is a different and much stronger claim.

Fetches a test's results and works out what they mean. Alongside the raw counts it returns the probability that each combination is genuinely best and the expected cost of stopping now and keeping the leader. Use those rather than comparing conversion rates by eye: a variant ahead 2/10 to 1/10 looks twice as good and is very close to a coin flip, and that mistake is the single most common way an A/B test gets called wrong. Multi-slot tests also report per-slot marginals: how each variant did across every combination it appeared in. Needs the stats secret. If you have the manage URL, its #fragment IS the secret and it will be used automatically.

Decodes a test and describes it: slots, variants, context, and whether it can be served by redirect. Also lints it for the mistakes that only show up once a campaign is out, such as an email test whose context comes from geo (which a mail proxy answers about itself). Use this before sending anything, and to answer 'what is this link?'.

Uploads an image to the deployment's asset store and returns its URL, for use as a variant's `image` (email tests) or `url`. The returned URL is deliberately not fetchable on its own: assets are only served with a short-lived signature that the serve endpoints mint per request, so uploading here does not create free static hosting. Use `previewUrl` (valid for an hour) to check what was stored. Storage is content-addressed: the id is the sha256 of the bytes, so uploading the same image twice is harmless and returns the same URL. Raster images only; SVG is refused because it can carry scripts. Not every deployment enables asset hosting, and this tool says so plainly when yours does not.

Returns the constraints to write or generate test variants against, for email or web, plus the rules that decide whether a test can be read at all once it runs. The one that matters most: one idea per slot. To vary two elements, give the test two slots and let it learn the combination, rather than bundling both changes into one variant and never learning which half worked. Ask for this before drafting variants, then produce them yourself against what it returns.