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Found 306 Skills
SAP HANA Machine Learning Python Client (hana-ml) development skill. Use when: Building ML solutions with SAP HANA's in-database machine learning using Python hana-ml library for PAL/APL algorithms, DataFrame operations, AutoML, model persistence, and visualization. Keywords: hana-ml, SAP HANA, machine learning, PAL, APL, predictive analytics, HANA DataFrame, ConnectionContext, classification, regression, clustering, time series, ARIMA, gradient boosting, AutoML, SHAP, model storage
Process textual and multimedia files with various LLM providers using the llm CLI. Supports both non-interactive and interactive modes with model selection, config persistence, and file input handling.
Initialize Spec-Driven Development context in any project. Detects stack, conventions, and bootstraps the active persistence backend. Trigger: When user wants to initialize SDD in a project, or says "sdd init", "iniciar sdd", "openspec init".
UdonSharp (C# to Udon Assembly) scripting skill for VRChat world development. Use this skill when writing, reviewing, or debugging UdonSharp C# code. Covers compile constraints (List<T>/async/await/try/catch/LINQ blocked), network sync (UdonSynced, RequestSerialization, FieldChangeCallback, NetworkCallable), persistence (PlayerData/PlayerObject), Dynamics (PhysBones, Contacts), Web Loading, and event handling. SDK 3.7.1 - 3.10.2 coverage. Triggers on: UdonSharp, Udon, VRC SDK, UdonBehaviour, UdonSynced, NetworkCallable, VRCPlayerApi, SendCustomEvent, PlayerData, PhysBones, synced variables, VRChat world scripting, C# to Udon.
Apply when working with MasterData v2 entities, schemas, or MasterDataClient in VTEX IO apps, or when anyone designing or implementing a solution must scrutinize whether Master Data is the correct storage. The skill prompts hard questions: native Catalog or other VTEX stores, OMS, or an external database may be better; do not default to MD because it is convenient. Covers JSON Schema, CRUD, triggers, search and scroll, schema lifecycle, purchase-path avoidance, single source of truth, and BFF handoffs. Use for justified custom persistence while avoiding the 60-schema limit.
Install and configure the Workflow Development Kit for resumable, durable AI agent workflows with step-level persistence, stream resumption, and agent orchestration.
Jotai state management patterns — atoms, globalAtom, contextAtom, and persistence.
Design state schemas, implement reducers, configure persistence, and debug state issues for LangGraph applications. Use when users want to (1) design or define state schemas for LangGraph graphs, (2) implement reducer functions for state accumulation, (3) configure persistence with checkpointers (InMemorySaver/MemorySaver, SqliteSaver, PostgresSaver), (4) debug state update issues or unexpected state behavior, (5) migrate state schemas between versions, (6) validate state schema structure, (7) choose between TypedDict and MessagesState patterns, (8) implement custom reducers for lists, dicts, or sets, (9) use the Overwrite type to bypass reducers, (10) set up thread-based persistence for multi-turn conversations, or (11) inspect checkpoints for debugging.
Generate Go GORM models following Pingo modular architecture conventions. Use when creating or updating persistence models in internal/modules/<module>/model/, including table mapping, nullable SQL types, timestamps, and relation fields for identity and monitor modules.
Production-grade Next.js chatbot builder. Covers tool calling with human-in-the-loop (HITL) approval, PostgreSQL session persistence, GDPR consent gating, SQL-first search, per-tool UI rendering, message feedback, and follow-up suggestions. Use when building chat apps, conversational AI interfaces, customer support bots, or any chatbot needing database-backed sessions, tool approval workflows, consent gating, or custom tool output components. Reference implementation: fair-helpdesk project.
Use when deploying a database to Zeabur. Use when user needs MySQL, PostgreSQL, MongoDB, or Redis. Use when user says "I need a database", "add database", "deploy postgres", "set up MySQL", "add Redis", "add MongoDB", or "connect to database". Also use when user mentions data persistence issues like "data lost after restart", "data not saved", "data disappears", "need persistent storage for data", or "how to persist data". Also use when integrating a database with an existing service.
Build, review, or improve Core Data persistence in apps that have not adopted SwiftData. Use when working with NSManagedObject subclasses, NSFetchedResultsController for list-driven UI, NSBatchInsertRequest / NSBatchDeleteRequest / NSBatchUpdateRequest for bulk operations, NSPersistentHistoryChangeRequest for persistent history tracking and multi-target sync, NSStagedMigrationManager for staged schema migrations (iOS 17+), NSCompositeAttributeDescription for composite attributes (iOS 17+), or when integrating Core Data threading with Swift Concurrency. For Core Data + SwiftData coexistence or migration, see the swiftdata skill instead.