rc-catalog-management
Use this skill when managing the Android product catalog through the Play Console and the RevenueCat dashboard. Covers the two sided catalog flow (create in Play Console, import or map in RevenueCat), entitlement and offering maintenance, and why you do not call the Google Play Developer API directly.
What this skill does
# Catalog Management
Manage the Android product catalog across two surfaces: the Google Play Console (source of truth for products) and the RevenueCat dashboard (entitlements, offerings, targeting). You do not call the Google Play Developer `monetization.subscriptions` or `monetization.onetimeproducts` endpoints from your app or backend.
## Phase 1: Understand
Read this phase before you touch anything.
### Why two surfaces
| Surface | Owns | Examples |
|---|---|---|
| Google Play Console | Underlying products, base plans, offers, prices | `premium_monthly`, base plan `p1m`, intro offer |
| RevenueCat dashboard | Entitlements, Offerings, Packages, Targeting | `pro` entitlement, `default` offering, `$rc_monthly` package |
Play Console holds the billable SKU. RevenueCat decides which SKU gets surfaced to which user and under which entitlement key.
### What changes without an app update
When your app calls `awaitOfferings()`, it fetches whatever the RevenueCat dashboard has configured. Offering edits, package swaps, and targeting rules propagate on the next app launch. No binary release is required.
### When to use the REST API
If you need to automate catalog edits from a backend (for example, seeding dozens of offerings across environments), use the RevenueCat REST API for products, entitlements, and offerings. You still do not talk to Google directly. Play Console remains the product source of truth.
## Phase 2: Plan
Before you make a change, decide:
1. **Is this a new product, or a repackaging of an existing one?**
- New product: start in Play Console.
- Repackaging (new offering, new targeting, new entitlement mapping): stay in RevenueCat.
2. **Which entitlement does the product unlock?** If you do not have a matching entitlement, create one first.
3. **Which offering and package identifier?** Decide the package identifier (for example `$rc_monthly`, `$rc_annual`) so your paywall code keeps working.
4. **Does targeting need to change?** If different users should see different offerings, plan the placement name and the targeting rule (OS version, country, custom attribute).
## Phase 3: Execute
The end to end flow for adding a new subscription product.
### Step 1: Add the product in the Play Console
1. Open **Play Console** -> your app -> **Monetize** -> **Products** -> **Subscriptions**.
2. Click **Create subscription**.
3. Set the product ID (for example `premium_monthly`), name, and description.
4. Add a base plan (billing period, renewal type, price).
5. Optionally add offers (intro pricing, free trial).
6. Activate the subscription.
Wait a few minutes for Play to propagate the product.
### Step 2: Import into RevenueCat and attach an entitlement
1. Open the **RevenueCat dashboard** -> your project -> **Products**.
2. Click **Import** to sync from the Play Console. The new product appears in the list.
3. Open the product and attach it to an existing entitlement, or create a new one.
- Entitlement example: `pro`. Every product that unlocks pro features attaches to `pro`.
Your client code checks entitlements by key:
```kotlin
val isPro = customerInfo.entitlements["pro"]?.isActive == true
```
### Step 3: Wire the product into an Offering as a Package
1. In the dashboard, open **Offerings**.
2. Pick the offering you want to edit, or create a new one (for example `default`).
3. Add a **Package**. Choose a package identifier that matches your paywall:
- `$rc_monthly` for monthly
- `$rc_annual` for annual
- Or a custom identifier
4. Attach the Play Console product to the package.
5. Save. Mark the offering as Current if it should be the default.
Your client code stays the same:
```kotlin
val offerings = Purchases.sharedInstance.awaitOfferings()
val monthly = offerings.current?.monthly
```
### Step 4 (optional): Targeting
If different users should see different offerings, use placements.
1. In the dashboard, open **Targeting** -> **Placements**.
2. Create a placement (for example `paywall_upsell`).
3. Add rules (OS version, country, custom attribute) that map users to specific offerings.
Client code:
```kotlin
val offering = offerings.getCurrentOfferingForPlacement("paywall_upsell")
?: offerings.current
```
No app update is required when you change targeting rules later.
## Phase 4: Verify
Check the change landed before you close the task.
| Check | How |
|---|---|
| Product exists in Play | Play Console -> Subscriptions shows the product as Active |
| Product imported to RC | Dashboard -> Products lists the product |
| Entitlement mapping | Dashboard -> Entitlements shows the product under the right entitlement |
| Offering wiring | Dashboard -> Offerings shows the product attached to the expected package |
| Runtime fetch | Launch the app, call `awaitOfferings()`, confirm the package resolves |
| Entitlement unlock | Complete a test purchase, confirm `customerInfo.entitlements["pro"].isActive` is true |
If `awaitOfferings()` returns `null` for a package you expect, the most common causes are: the offering is not marked Current, the product is not attached to the package, or Play has not finished propagating the product.
## Common Mistakes
- Calling `monetization.subscriptions` from your backend. Use RevenueCat instead.
- Creating an offering before importing the product. Import first, then wire.
- Shipping hard coded product IDs in your paywall UI. Use package identifiers so you can swap products without an app release.
- Forgetting to mark an offering as Current. Clients that call `offerings.current` will see the old offering until you flip this.
## References
- [Full chapter](https://www.revenuecat.com/guides/revenuecat-android-sdk/catalog-management)
Related in Backend & APIs
jfrog
IncludedInteract with the JFrog Platform via the JFrog CLI and REST/GraphQL APIs. Use this skill when the user wants to manage Artifactory repositories, upload or download artifacts, manage builds, configure permissions, manage users and groups, work with access tokens, configure JFrog CLI servers, search artifacts, manage properties, set up replication, manage JFrog Projects, run security audits or scans, look up CVE details, query exposures scan results from JFrog Advanced Security, manage release bundles and lifecycle operations, aggregate or export platform data, or perform any JFrog Platform administration task. Also use when the user mentions jf, jfrog, artifactory, xray, distribution, evidence, apptrust, onemodel, graphql, workers, mission control, curation, advanced security, exposures, or any JFrog product name.
cupynumeric-migration-readiness
IncludedPre-migration readiness assessor for porting NumPy to cuPyNumeric. Use BEFORE substantial porting work begins when the user asks whether code will scale on GPU, whether they should migrate to cuPyNumeric, which NumPy patterns transfer cleanly, what must be refactored before porting, or mentions pre-port assessment, scaling analysis, or refactor planning. Inspect the user's source code, look up NumPy usage, cross-reference the cuPyNumeric API support manifest, and distinguish distributed-scaling-friendly patterns from blockers such as unsupported APIs, scalar synchronization, host round-trips, Python/object-heavy control flow, shape/data-dependent branching, and in-place mutation hazards. Produce a verdict of READY, LIGHT REFACTOR, SIGNIFICANT REFACTOR, or NOT RECOMMENDED, with concrete refactor pointers.
alibabacloud-data-agent-skill
IncludedInvoke Alibaba Cloud Apsara Data Agent for Analytics via CLI to perform natural language-driven data analysis on enterprise databases. Data Agent for Analytics is an intelligent data analysis agent developed by Alibaba Cloud Database team for enterprise users. It automatically completes requirement analysis, data understanding, analysis insights, and report generation based on natural language descriptions. This tool supports: discovering data resources (instances/databases/tables) managed in DMS, initiating query or deep analysis sessions, real-time progress tracking, and retrieving analysis conclusions and generated reports. Use this Skill when users need to query databases, analyze data trends, generate data reports, ask questions in natural language, or mention "Data Agent", "data analysis", "database query", "SQL analysis", "data insights".
token-optimizer
IncludedReduce OpenClaw token usage and API costs through smart model routing, heartbeat optimization, budget tracking, and native 2026.2.15 features (session pruning, bootstrap size limits, cache TTL alignment). Use when token costs are high, API rate limits are being hit, or hosting multiple agents at scale. The 4 executable scripts (context_optimizer, model_router, heartbeat_optimizer, token_tracker) are local-only — no network requests, no subprocess calls, no system modifications. Reference files (PROVIDERS.md, config-patches.json) document optional multi-provider strategies that require external API keys and network access if you choose to use them. See SECURITY.md for full breakdown.
resend-cli
IncludedUse this skill when the task is specifically about operating Resend from an AI agent, terminal session, or CI job via the official resend CLI: installing/authenticating the CLI, sending/listing/updating/cancelling emails, batch sends, domains and DNS, webhooks and local listeners, inbound receiving, contacts, topics, segments, broadcasts, templates, API keys, profiles, or debugging Resend CLI/API failures. Trigger on mentions of Resend CLI, `resend`, `resend doctor`, `resend emails send`, `resend domains`, `resend webhooks listen`, `resend emails receiving`, or agent-friendly terminal automation.
alibabacloud-odps-maxframe-coding
IncludedUse this skill for MaxFrame SDK development and documentation navigation on Alibaba Cloud MaxCompute (ODPS). Helps answer MaxFrame API, concept, official example, and supported pandas API questions; create data processing programs; read/write MaxCompute tables; debug jobs (remote or local); and build custom DPE runtime images. Trigger when users mention MaxFrame, MaxCompute with MaxFrame, ODPS table processing, DPE runtime, MaxFrame docs/examples, DataFrame/Tensor operations, or GPU runtime setup. Works for both English and Chinese queries about Alibaba Cloud data processing with MaxFrame.