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Found 416 Skills
Load PROACTIVELY when task involves application state, data fetching, or form handling. Use when user says "manage state", "add data fetching", "set up Zustand", "handle form validation", or "add React Query". Covers server state (TanStack Query with caching, optimistic updates), client state (Zustand stores), form state (React Hook Form with Zod validation), URL state (search params, routing), and choosing between state solutions.
Expert guidance for Next.js Cache Components and Partial Prerendering (PPR). Use when implementing 'use cache' directive, configuring cache lifetimes with cacheLife(), tagging cached data with cacheTag(), invalidating caches with updateTag()/revalidateTag(), optimizing static vs dynamic content boundaries, managing 'use cache: private' for compliance scenarios, pass-through/interleaving patterns, GET Route Handler caching, debugging cache issues, and reviewing Cache Component implementations.
Implements Syncfusion Angular DataManager for local/remote binding, CRUD, querying, caching, and middleware. Supports JsonAdaptor, ODataAdaptor, ODataV4Adaptor, UrlAdaptor, WebApiAdaptor, WebMethodAdaptor, RemoteSaveAdaptor, GraphQLAdaptor, CustomDataAdaptor, and CustomAdaptor. Covers Query class, filtering, sorting, paging, grouping, persistence, offline mode, caching, and error handling.
Shared references and cross-cutting rules used by all Infrahub skills. Contains GraphQL query syntax, .infrahub.yml configuration format, and common rules for git integration, display label caching, and Python environment setup. DO NOT TRIGGER directly — loaded automatically by other Infrahub skills when they need shared references.
Grafana Tempo distributed tracing backend. Covers TraceQL query language (span selectors, attribute scopes, pipeline operators, structural operators, metrics functions), trace ingestion via OTLP/Jaeger/Zipkin, Tempo architecture (distributor/ingester/compactor/querier/metrics-generator), full configuration reference with YAML, metrics-from-traces (span metrics, service graphs, TraceQL metrics), deployment modes (monolithic/microservices/Helm/Kubernetes), multi-tenancy, performance tuning, caching, and HTTP API. Use when working with distributed traces, writing TraceQL queries, deploying Tempo, configuring trace pipelines, or setting up Grafana-Tempo integrations (traces-to-logs, traces-to-metrics, traces-to-profiles).
Creates scoped key-value stores, reads and writes state entries, lists keys, and performs partial updates across functions. Use when persisting data between invocations, managing user sessions, caching computed values, storing feature flags, sharing state between workers, or building a KV data layer as an alternative to Redis or DynamoDB.
Fast structured generation and serving for LLMs with RadixAttention prefix caching. Use for JSON/regex outputs, constrained decoding, agentic workflows with tool calls, or when you need 5× faster inference than vLLM with prefix sharing. Powers 300,000+ GPUs at xAI, AMD, NVIDIA, and LinkedIn.
Provides guidance for mechanistic interpretability research using TransformerLens to inspect and manipulate transformer internals via HookPoints and activation caching. Use when reverse-engineering model algorithms, studying attention patterns, or performing activation patching experiments.
Reviews URLSession networking code for iOS/macOS. Covers async/await patterns, request building, error handling, caching, and background sessions.
Master modern GraphQL with federation, performance optimization, and enterprise security. Build scalable schemas, implement advanced caching, and design real-time systems. Use PROACTIVELY for GraphQL architecture or performance optimization.
Comprehensive guide for production-ready Python backend development and software architecture at scale. Use when designing APIs, building backend services, creating microservices, structuring Python projects, implementing database patterns, writing async code, or any Python backend/server-side development task. Covers Clean Architecture, Domain-Driven Design, Event-Driven Architecture, FastAPI/Django patterns, database design, caching strategies, observability, security, testing strategies, and deployment patterns for high-scale production systems.
Build type-safe D1 databases with Drizzle ORM for Cloudflare Workers. Includes schema definition, migrations with Drizzle Kit, relations, and D1 batch API patterns. Prevents 12 errors including SQL BEGIN failures. Use when: defining D1 schemas, managing migrations, writing type-safe queries, implementing relations or prepared statements, using batch API for transactions, or troubleshooting D1_ERROR, BEGIN TRANSACTION, foreign keys, migration apply, or schema inference errors. Prevents 12 documented issues: D1 transaction errors (SQL BEGIN not supported), foreign key constraint failures during migrations, module import errors with Wrangler, D1 binding not found, migration apply failures, schema TypeScript inference errors, prepared statement caching issues, transaction rollback patterns, TypeScript strict mode errors, drizzle.config.ts not found, remote vs local database confusion, and wrangler.toml vs wrangler.jsonc mixing. Keywords: drizzle orm, drizzle d1, type-safe sql, drizzle schema, drizzle migrations, drizzle kit, orm cloudflare, d1 orm, drizzle typescript, drizzle relations, drizzle transactions, drizzle query builder, schema definition, prepared statements, drizzle batch, migration management, relational queries, drizzle joins, D1_ERROR, BEGIN TRANSACTION d1, foreign key constraint, migration failed, schema not found, d1 binding error