Build recommendation systems using collaborative filtering, matrix factorization (SVD), and hybrid approaches in Python, addressing cold start, sparsity, and quality evaluation with metrics like precision@K and recall@K.
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npx claudepluginhub secondsky/claude-skills --plugin recommendation-engineComprehensive ABAP development skill for SAP systems. Use when writing ABAP code, working with internal tables, structures, ABAP SQL, object-oriented programming, RAP (RESTful Application Programming Model), CDS views, EML statements, ABAP Cloud development, string processing, dynamic programming, RTTI/RTTC, field symbols, data references, exception handling, or ABAP unit testing. Covers both classic ABAP and modern ABAP for Cloud Development patterns.
secondskyComprehensive SAP ABAP CDS (Core Data Services) reference for data modeling, view development, and semantic enrichment. Use when creating CDS views or view entities, defining data models with annotations, working with associations and cardinality, implementing input parameters, using built-in functions, writing CASE expressions, implementing access control with DCL, handling CURR/QUAN data types, troubleshooting CDS errors, querying CDS views from ABAP, or displaying data with SALV IDA. Covers ABAP 7.4+ through ABAP Cloud.
secondskyGuides development with SAP AI Core and SAP AI Launchpad for enterprise AI/ML workloads on SAP BTP. Use when: deploying generative AI models (GPT, Llama, Gemini, Mistral), building orchestration workflows with templating/filtering/grounding, implementing RAG with vector databases, managing ML training pipelines with Argo Workflows, configuring content filtering and data masking for PII protection, using the Generative AI Hub for prompt experimentation, or integrating AI capabilities into SAP applications. Covers service plans (Free/Standard/Extended), model providers (Azure OpenAI, AWS Bedrock, GCP Vertex AI, Mistral, IBM), orchestration modules, embeddings, tool calling, and structured outputs.
secondskySAP Analytics Cloud (SAC) Custom Widget development. Use when building custom visualizations, extending SAC with Web Components, or creating Widget Add-Ons. Covers JSON metadata, JavaScript Web Components, lifecycle functions, data binding with feeds, styling/builder panels, property/event/method definitions, third-party library integration, hosting, security, performance, and debugging. Includes Widget Add-On feature (QRC Q4 2023+) and templates for widgets, charts, and KPI cards.
secondskyDevelops and administers SAP Build Work Zone, advanced edition digital workplace solutions. Use when creating workspaces, workpages, and collaborative sites, developing UI Integration Cards in SAP Business Application Studio, building content packages and workspace templates, integrating with Microsoft 365/Teams/SharePoint/Google Drive, configuring chatbots and webhooks, implementing SCIM API user provisioning, setting up OData business records, managing themes and branding, configuring role-based access and SSO, troubleshooting deployment issues, or working with the Administration Console. Keywords: SAP Build Work Zone advanced edition, digital workplace, UI Integration Cards, content packages, workspace templates, SAP Business Application Studio, SAP Conversational AI, SCIM API, OData, Microsoft Teams integration, SSO, theming, Administration Console
secondskyBuild recommendation systems and engines
jeremylongshoreDeploy production recommendation systems with feature stores, caching, A/B testing. Use for personalization APIs, low latency serving, or encountering cache invalidation, experiment tracking, quality monitoring issues.
secondskyUse this agent when implementing AI/ML features, integrating language models, building recommendation systems, or adding intelligent automation to applications. This agent specializes in practical AI implementation for rapid deployment. Examples:\n\n<example>\nContext: Adding AI features to an app\nuser: "We need AI-powered content recommendations"\nassistant: "I'll implement a smart recommendation engine. Let me use the ai-engineer agent to build an ML pipeline that learns from user behavior."\n<commentary>\nRecommendation systems require careful ML implementation and continuous learning capabilities.\n</commentary>\n</example>\n\n<example>\nContext: Integrating language models\nuser: "Add an AI chatbot to help users navigate our app"\nassistant: "I'll integrate a conversational AI assistant. Let me use the ai-engineer agent to implement proper prompt engineering and response handling."\n<commentary>\nLLM integration requires expertise in prompt design, token management, and response streaming.\n</commentary>\n</example>\n\n<example>\nContext: Implementing computer vision features\nuser: "Users should be able to search products by taking a photo"\nassistant: "I'll implement visual search using computer vision. Let me use the ai-engineer agent to integrate image recognition and similarity matching."\n<commentary>\nComputer vision features require efficient processing and accurate model selection.\n</commentary>\n</example>
ananddtyagiSkills for technical roles: software architecture, Python development, data analytics strategy
maxvaegaUse this agent when implementing AI/ML features, integrating language models, building recommendation systems, or adding intelligent automation to applications. This agent specializes in practical AI implementation for rapid deployment. Examples:\n\n<example>\nContext: Adding AI features to an app\nuser: "We need AI-powered content recommendations"\nassistant: "I'll implement a smart recommendation engine. Let me use the ai-engineer agent to build an ML pipeline that learns from user behavior."\n<commentary>\nRecommendation systems require careful ML implementation and continuous learning capabilities.\n</commentary>\n</example>\n\n<example>\nContext: Integrating language models\nuser: "Add an AI chatbot to help users navigate our app"\nassistant: "I'll integrate a conversational AI assistant. Let me use the ai-engineer agent to implement proper prompt engineering and response handling."\n<commentary>\nLLM integration requires expertise in prompt design, token management, and response streaming.\n</commentary>\n</example>\n\n<example>\nContext: Implementing computer vision features\nuser: "Users should be able to search products by taking a photo"\nassistant: "I'll implement visual search using computer vision. Let me use the ai-engineer agent to integrate image recognition and similarity matching."\n<commentary>\nComputer vision features require efficient processing and accurate model selection.\n</commentary>\n</example>
devsforgeUse this agent when evaluating new development tools, frameworks, or services for the studio. This agent specializes in rapid tool assessment, comparative analysis, and making recommendations that align with the 6-day development cycle philosophy. Examples:\n\n<example>\nContext: Considering a new framework or library
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