Service Blueprint

SAP Cloud Application Programming Model (CAP) development skill using Capire documentation. Use when: building CAP applications, defining CDS models, implementing services, working with SAP HANA/SQLite/PostgreSQL databases, deploying to SAP BTP Cloud Foundry or Kyma, implementing Fiori UIs, handling authorization, multitenancy, or messaging. Covers CDL/CQL/CSN syntax, Node.js and Java runtimes, event handlers, OData services, and CAP plugins.

Use when preparing, submitting, polling, or debugging Seedance 2.0 video generation jobs from product images, storyboard images, UGC scripts, voiceover copy, or promptPlan request JSON. Use for splitting scripts into render segments, uploading references, composing submit flags, submitting jobs through the PostPlus Cloud service, polling predictions, and handing off local render paths.

Apply when implementing localization and translated copy in VTEX IO apps. Covers the `messages` builder, `/messages/*.json`, `context.json`, frontend message usage, and how VTEX apps integrate with `vtex.messages` for runtime translation. Use for storefront, admin, or backend flows that should use VTEX IO message infrastructure instead of hardcoded strings.

Creates complete AEM components with dialog, HTL template, Sling Model, unit tests, and clientlibs. Supports extending Core Components and project components. When a Figma design URL is provided, fetches the design via Figma MCP (get_design_context) and translates it into pixel-perfect HTL, CSS, and JS. Follows Adobe Experience League best practices for AEM Cloud Service and 6.5. Use this skill whenever the user mentions creating, building, generating, or scaffolding an AEM component, or mentions component types like teaser, card, hero, banner, accordion, tabs, carousel, list, navigation, breadcrumb, or any custom AEM component. Also trigger when the user wants to extend a Core Component, create a component dialog, add a Sling Model, or convert a Figma design into an AEM component.

Setup Sentry AI Agent Monitoring in any project. Use when asked to monitor LLM calls, track AI agents, or instrument OpenAI/Anthropic/Vercel AI/LangChain/Google GenAI/Pydantic AI. Detects installed AI SDKs and configures appropriate integrations.

Use this skill when the user asks for financial data ("price of BTC", "P/E ratio of NVDA"), market analysis, stock or crypto research, quant strategies, backtesting ("backtest a momentum strategy"), tracking assets or portfolios, or help turning investing ideas into live playbooks, dashboards, and analytics on Alva. Powered by 250+ financial data sources across crypto, equities, macro, on-chain, and social data, along with cloud-side analytics and backtesting. Also use when the user asks about Alva platform capabilities.