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Found 1,653 Skills
Set up database migrations for Elixir releases. Use when asked to configure release migrations, add migrate command to releases, or set up Ecto for production deployment without Mix.
macOS menu bar app that identifies USB-C cable capabilities and charging diagnostics using IOKit
Vector database selection, embedding storage, approximate nearest neighbor (ANN) algorithms, and vector search optimization. Use when choosing vector stores, designing semantic search, or optimizing similarity search performance.
Senior UX/UI Design Director for mobile app design auditing across all platforms (iOS, Android, cross-platform). Triggers on "UI建议", "审美讲义", "交互建议", design audit, UI review, UX audit, or premium design feedback. Provides three-tier proposals (Safe/Balanced/Avant-Garde), aesthetic formulas, motion physics, and brand consistency checks. Specializes in "Young Luxury" mobile experiences grounded in Apple HIG and Material Design 3.
Migrate Claude Code project sessions when renaming directories. TRIGGERS - directory rename, move project, migrate sessions, project path change, workspace reorganization, rename folder.
Design, refactor, and review Effector state management using modern v23+ patterns. Use when tasks involve createStore/createEvent/createEffect modeling, dataflow with sample/attach/split, scope-safe SSR with fork/allSettled/serialize/hydrate, React integration with useUnit, Solid/Vue integration patterns, fixing scope loss, or replacing anti-patterns such as business logic in watch, imperative calls in effects, and direct getState business reads.
Expert knowledge for Azure AI Anomaly Detector development including troubleshooting, best practices, architecture & design patterns, limits & quotas, configuration, and deployment. Use when using univariate/multivariate APIs, Docker/IoT Edge containers, predictive maintenance flows, or regional limits, and other Azure AI Anomaly Detector related development tasks. Not for Azure AI Metrics Advisor (use azure-metrics-advisor), Azure Monitor (use azure-monitor), Azure Machine Learning (use azure-machine-learning).
Expert knowledge for Azure Service Connector development including troubleshooting, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when wiring apps to Azure DBs, messaging, storage, Key Vault, OpenAI, or managing Service Connector auth and configs, and other Azure Service Connector related development tasks. Not for Azure API Management (use azure-api-management), Azure App Service (use azure-app-service), Azure Functions (use azure-functions), Azure Logic Apps (use azure-logic-apps).
Implements and debugs browser Language Detector API integrations in JavaScript or TypeScript web apps. Use when adding LanguageDetector support checks, availability and model download flows, session creation, detect() calls, input-usage measurement, permissions-policy handling, or compatibility fallbacks for built-in language detection. Don't use for server-side language detection SDKs, cloud translation services, or generic NLP pipelines.
Mutation-driven test vector generation. Finds implementations of a cryptographic algorithm or protocol, runs mutation testing to identify escaped mutants, then generates new test vectors that deliberately exercise the uncovered code paths. Compares before/after mutation kill rates to prove vector effectiveness. Use when generating cryptographic test vectors, measuring Wycheproof coverage gaps, finding escaped mutants via mutation testing, creating cross-implementation test suites, or improving test vector coverage for crypto primitives.
Create and manage Neo4j vector indexes, run vector similarity search (ANN/kNN), store embeddings on nodes or relationships, use SEARCH clause (Neo4j 2026.01+, preferred) or db.index.vector.queryNodes() procedure (deprecated 2026.04, still works on 2025.x), configure HNSW and quantization options, pick similarity function and embedding provider dimensions, and batch-update embeddings. Use when tasks involve CREATE VECTOR INDEX, vector.dimensions, cosine/euclidean search, embedding ingestion pipelines, or semantic nearest-neighbor lookup. Does NOT handle GraphRAG retrieval_query graph traversal — use neo4j-graphrag-skill. Does NOT handle fulltext/keyword indexes (FULLTEXT INDEX, db.index.fulltext) — use neo4j-cypher-skill. Does NOT handle GDS graph embeddings (FastRP, Node2Vec) — use neo4j-gds-skill.
Store and query vector embeddings using Amazon S3 Vectors, a cost-effective long-term vector storage service with its own API namespace (s3vectors). Triggers on: create S3 vector bucket, vector index, store embeddings, semantic search, RAG vector storage, similarity search, vector database, migrate from other vector databases. Do NOT use for: querying tabular data (use querying-data-lake), S3 object storage, or hundreds/thousands of sustained QPS (use OpenSearch).