Loading...
Loading...
Found 7,062 Skills
Apply when choosing which VTEX IO authentication token should back a request from a backend app. Covers `ctx.authToken`, `ctx.storeUserAuthToken`, `ctx.adminUserAuthToken`, `authMethod`, and how requester context should determine the identity used by VTEX clients. Use for deciding which identity talks to VTEX endpoints in storefront-backed requests, Admin actions, or app-level integrations that should avoid hardcoded VTEX credentials.
Apply when reviewing or designing security-sensitive boundaries in VTEX IO apps. Covers public versus private exposure, trust assumptions at route and integration boundaries, sensitive data handling, validating what crosses the app boundary, and avoiding leakage across accounts, workspaces, users, or integrations. Use for route hardening, data exposure review, or evaluating whether a service boundary is too permissive.
Apply when implementing retry logic, rate limit handling, or resilience patterns in VTEX API integrations. Covers VTEX rate limit headers (X-RateLimit-Remaining, X-RateLimit-Reset, Retry-After), 429 status handling, exponential backoff with jitter, circuit breaker patterns, and request queuing. Use for any VTEX marketplace integration that must gracefully handle API throttling and maintain high availability.
Apply when designing or implementing HTTP endpoints exposed by a VTEX IO backend service. Covers route boundaries, handler structure, middleware composition, request validation, and response modeling for service.json routes. Use for webhook endpoints, partner integrations, callback APIs, or reviewing VTEX IO handlers that should expose explicit HTTP contracts.
Cisco AppDynamics integration. Manage data, records, and automate workflows. Use when the user wants to interact with Cisco AppDynamics data.
Vector search indexing and querying workflows using MCP Vector Search, including setup, reindexing, auto-index strategies, and MCP integration.
A comprehensive guide to building React apps with a modern 2026 stack, covering frameworks, build tools, routing, state management, and AI integration.
Use this skill whenever writing, reviewing, debugging, or refactoring TypeScript code that uses the Effect-TS library. Trigger when you see imports from `effect`, `effect/*`, or any `@effect/*` scoped package (schema, platform, sql, opentelemetry, cli, cluster, rpc, vitest). Trigger on Effect-specific constructs: Effect.gen generators, Schema.Struct/Schema.Class definitions, Layer/Context.Tag/Service patterns, Effect.pipe pipelines, Data.TaggedError/Data.Class error types, Ref/Queue/PubSub/Deferred concurrency primitives, Match module, Config providers, Scope/Exit/Cause/Runtime patterns, or any code using Effect's typed error channel (E parameter). Also trigger when the user asks about Effect patterns, migration from Promises/fp-ts/neverthrow to Effect, or how to structure an Effect application. Covers the full ecosystem: core Effect type, Schema validation, error management, concurrency (fibers, queues, semaphores, pools), streams/sinks, services and layers (DI), resource management, scheduling, observability, platform APIs, and AI integration. Do NOT trigger for React's useEffect, Redux side effects, or general English usage of "effect" unless the context clearly involves the Effect-TS library.
Build and deploy applications on inference.sh. Use when getting started, understanding the platform, creating apps, configuring resources, or needing an overview of inference.sh app development. Supports both Python and Node.js. Triggers: inference.sh app, infsh app, inf.yml, inference.py, inference.js, deploy app, app development, build app, create app, GPU app, VRAM, app resources, app secrets, app integrations, multi-function app
Design data pipelines covering ETL vs ELT architectures, data source integration, scheduling, quality checks, and warehouse design. Use this skill when the user needs to move data between systems, build a data warehouse, automate data processing, or improve data reliability — even if they say 'move data from X to Y', 'build an ETL pipeline', 'our data is a mess', or 'set up a data warehouse'.
Generate comprehensive test plans, test cases, regression test suites, automation annotations, and bug reports for QA engineers. Includes Figma MCP integration for design validation. Use when planning QA before execution, documenting test strategies, marking which flows require E2E follow-up, or creating structured bug reports. Do not use for executing tests against a live repository or running verification gates — use qa-execution for that.
Grafana Beyla eBPF auto-instrumentation for application observability without code changes. Covers supported languages/runtimes, requirements, installation, configuration (discovery, eBPF settings, OTLP traces export, Prometheus metrics export), Kubernetes deployment, and integration with Grafana Cloud. Use when setting up zero-code instrumentation, configuring eBPF probes, deploying Beyla to Kubernetes, connecting to Tempo/Prometheus, or troubleshooting instrumentation issues.