revenuecat-experiments
Use when the user asks to create, prepare, or set up a RevenueCat experiment (A/B test), to prepare its variant offerings or paywalls, or to start, pause, resume, or stop an experiment via the RevenueCat MCP experiment tools
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/revenuecat/ai-toolkit --skill revenuecat-experiments- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads revenuecat-experiments automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Setting up and managing experiments
A RevenueCat experiment compares two to four offerings: offering_a (the control) against offering_b–offering_d (the treatments). Enrolled customers are served their variant's offering instead of the project's current offering. Setting up an experiment means preparing one offering per variant, then creating the experiment as a draft.
Refer to the MCP tool schemas for the exact parameters of each tool; the create-experiment schema also lists the available experiment types with their recommended primary and secondary metrics.
Preparing the variants
Keep the variants identical except for the one aspect under test, otherwise results cannot be attributed to the change. For example, when measuring the impact of a lower subscription price, both variants should share the same paywall design and packages, differing only in the price of the products.
Control. When the control variant is "what production does today", pass the current offering (is_current in list-offerings) directly as offering_a_id — do not duplicate it. Duplicate only when control itself needs changes relative to production.
Treatments. First check with list-offerings whether an offering already exists that matches what the treatment should serve, and reuse it instead of duplicating. Otherwise, start each treatment from a duplicate of the offering closest to it (usually the control offering). duplicate-offering copies the packages (attaching the same existing products) and, if the source offering has a paywall, also copies it as a new unpublished draft; it returns the new offering, including its new paywall_id. Pass source_paywall_version: published so the treatment copies the paywall customers see in production rather than unfinished draft edits; this fails when the source paywall was never published, so use the default (draft) only then. Then apply the one change under test:
- Paywall change (copy, layout, CTA, pricing display, ...): this requires the app to use RevenueCat Paywalls — a paywall is an optional property of an offering. If the control offering has none (
paywall_idisnull), the app renders its own paywall in code, so the paywall change has to be made in the app rather than through RevenueCat; tell the user. Otherwise, loadrevenuecat-paywall-designand edit the duplicated paywall withedit-paywall-ai. Request only the minimum changes required to measure the desired effect, and verify the result by looking at the resulting paywall. - Price, trial, or introductory-offer change: these live on store products, so the treatment offering needs different products. Check with
list-productswhether suitable products already exist; create only the missing ones and their store counterparts (see therevenuecat-store-stateskill). Then swap them into the duplicated offering's packages: detach the copied products withdetach-products-from-package, then attach the new ones withattach-products-to-package. - Brand-new paywall: duplicate the offering with
include_paywall: false, then loadrevenuecat-paywall-designand callcreate-paywall-aiwith the new offering'soffering_idso the generated draft is attached to it directly. A paywall and an offering pair 1:1 —attach-offering-to-paywallfails if either side is already paired; undo a wrong pairing withdetach-offering-from-paywall(unpublish the paywall first if it is published).
Publish treatment paywalls. A duplicated or newly created paywall is an unpublished draft, and a variant only serves the published version. If new paywalls were created in previous steps, publish each treatment paywall with publish-paywall before the experiment starts. This is the exception to the rule against proactive publishing, and it is safe: the treatment offering is not the current offering, so no customer sees the paywall until the experiment starts enrolling.
Creating the experiment
Create a draft with create-experiment: display name, enrollment_percentage, the variant offering IDs, experiment_type, a primary_metric (plus secondary_metrics) matching the hypothesis, enrollment_mode (only_new unless the user explicitly wants to include existing customers), and any targeting and notes. Creating never starts the experiment. Adjust a draft with update-experiment.
Before starting, verify each variant: treatment paywalls are published, packages contain the intended products, and any new products are available on the stores.
Lifecycle
start-experimentbegins enrolling real customers — only run it with the user's explicit confirmation.pause-experimentstops enrollment but keeps serving enrolled customers their variant and keeps collecting data.resume-experimentcontinues enrollment.stop-experimentis terminal: enrolled customers fall back to the default offering and the experiment can never be restarted.
To interpret results once the experiment is running, use the revenuecat-experiment-analysis skill.
FAQ
What does the revenuecat-experiments skill do?
Use when the user asks to create, prepare, or set up a RevenueCat experiment (A/B test), to prepare its variant offerings or paywalls, or to start, pause, resume, or stop an experiment via the RevenueCat MCP experiment tools
How do I install revenuecat-experiments?
Run npx skills add https://github.com/revenuecat/ai-toolkit --skill revenuecat-experiments in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/revenuecat-experiments/ (personal) or .claude/skills/revenuecat-experiments/ (project).
Which AI agents can use revenuecat-experiments?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is revenuecat-experiments safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains revenuecat-experiments?
It is published by revenuecat in revenuecat/ai-toolkit. It has 327 recorded installs.
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Display a RevenueCat paywall inside an app using the RevenueCatUI SDK. Use when the user asks to add a paywall, show a RevenueCat paywall, present PaywallView, integrate RevenueCatUI, gate a premium screen with a paywall, launch PaywallActivity, call presentPaywall or presentPaywallIfNeeded, or show the dashboard configured paywall UI on iOS, Android, Kotlin Multiplatform, Flutter, or React Native. To create, edit, evaluate, or audit the dashboard paywall itself, use revenuecat-paywall-design.
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Diagnose and resolve RevenueCat integration issues — inspects dashboard configuration through the RevenueCat MCP, walks the SDK debug logs, and covers code-side gotchas. Use when the user says offerings are empty, products not loading, entitlement not active after purchase, paywall won't load, transactions not appearing, customer info shows no entitlements, sandbox purchase not working, an SDK-gated RevenueCat feature not working, or RevenueCat is broken on iOS, Android, Kotlin Multiplatform, Flutter, or React Native. Also use when asked to check or validate the store / product setup.
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