Loading...
Loading...
Found 206 Skills
Expert database specialist focusing on schema design, query optimization, indexing strategies, and performance tuning for PostgreSQL, MySQL, and modern databases like Supabase and PlanetScale.
Vector search best practices for Azure DocumentDB using `cosmosSearch` — choosing between DiskANN / HNSW / IVF, creating indexes, tuning `lBuild` / `lSearch` / `maxDegree`, Product Quantization (up to 16,000 dims), half-precision (fp16) indexing, and normalizing embeddings for cosine similarity. Use when building RAG / semantic-search applications, creating a vector index, tuning recall/latency, or reducing vector-index memory footprint.
Provides comprehensive SAP Commerce Cloud (formerly Hybris) development guidance including type system modeling, service layer architecture, data management with ImpEx and FlexibleSearch, OCC API customization, B2C/B2B accelerator patterns, CronJobs, business processes, Solr search, promotions, caching, and Backoffice configuration. Use when the user asks to "create SAP Commerce extensions", "define item types in items.xml", "write ImpEx scripts", "implement service layer components (facades/services/DAOs)", "customize OCC REST APIs", "work with FlexibleSearch queries", "customize B2C or B2B accelerators", "configure Spring beans", "create CronJobs or scheduled tasks", "define business processes or order flows", "configure Solr search or indexing", "set up promotions or coupons", "configure caching", "customize Backoffice", mentions "Hybris development" or "SAP Commerce Cloud platform", or asks about troubleshooting SAP Commerce issues.
MongoDB Atlas cloud database management including clusters, schemas, aggregation pipelines, and Prisma ORM integration. Activate for MongoDB queries, schema design, indexing, and Atlas administration.
Expert knowledge for Azure AI Video Indexer development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when using Video Indexer APIs/widgets, live camera indexing, custom speech/brand models, or Azure OpenAI integrations, and other Azure AI Video Indexer related development tasks. Not for Azure AI services (use microsoft-foundry-tools), Azure AI Vision (use azure-ai-vision).
Identify and eliminate host-device synchronizations in PyTorch code. Detects sync points (.item(), .cpu(), boolean indexing, torch.tensor on CUDA), classifies false vs true dependencies, provides sync-free alternatives. Triggers: sync-free, synchronization, .item(), .cpu(), host-device sync, eliminate syncs, CPU stall, non_blocking, set_sync_debug_mode, cudaStreamSynchronize, cudaEventSynchronize, remove syncs, async GPU.
SQL query optimization for PostgreSQL/MySQL with indexing, EXPLAIN analysis. Use for slow queries, N+1 problems, missing indexes, or encountering sequential scans, OFFSET pagination, temp table spills, inefficient JOINs.
Use this skill when designing database schemas for relational (SQL) or document (NoSQL) databases. Provides normalization guidelines, indexing strategies, migration patterns, and performance optimization techniques. Ensures scalable, maintainable, and performant data models.
Use when generating, updating, or organizing documentation (component/API docs, project indexes, diagrams, tutorials, learning paths) - provides structured workflows and references for docs generation, indexing, diagrams, and teaching.
How to read data from the Sui network. Use when choosing or implementing a data access strategy — queries for on-chain state, indexing pipelines, historical lookups, event subscriptions, cross-chain reads, or off-chain blob storage. Covers the three live Sui APIs (gRPC, GraphQL RPC, deprecated JSON-RPC), the Archival Store, the General-Purpose Indexer, the `sui-indexer-alt` custom indexing framework, and Walrus for off-chain blobs.
Optimize App Store product pages for search visibility and conversion. Covers App Store Optimization ASO strategy, keyword research and keyword field optimization, app title and subtitle keyword placement, App Store description writing for conversion, promotional text rotation strategy, screenshot caption writing and ordering, in-app review prompt timing with RequestReviewAction and AppStore.requestReview, Custom Product Pages for audience segments, in-app events for search indexing, product page A/B testing experiments, localized metadata optimization across markets, and ratings and review management. Use when improving App Store discoverability, optimizing keyword strategy, writing App Store descriptions or promotional text, planning screenshot captions, setting up Custom Product Pages, configuring in-app review prompts, creating in-app events, running product page optimization tests, or developing a ratings management strategy.
bkend.ai database expert skill. Covers table creation, CRUD operations, 7 column types, constraints, filtering (AND/OR, 8 operators), sorting, pagination, relations, joins, indexing, and schema management via MCP and REST API. Triggers: table, column, CRUD, schema, index, filter, query, data model, 테이블, 컬럼, 스키마, 인덱스, 필터, 쿼리, 데이터 모델, テーブル, カラム, スキーマ, インデックス, フィルター, 数据表, 列, 模式, 索引, 过滤, 查询, tabla, columna, esquema, indice, filtro, consulta, tableau, colonne, schema, index, filtre, requete, Tabelle, Spalte, Schema, Index, Filter, Abfrage, tabella, colonna, schema, indice, filtro, query Do NOT use for: authentication (use bkend-auth), file storage (use bkend-storage), platform management (use bkend-quickstart).