307 件 ・ 関連度順
概要と使いどころ
Design stable, compatible public APIs using extend-only design principles. Manage API compatibility, wire compatibility, and versioning for NuGet packages and distributed systems.
日本語の概要は準備中です。原文の説明を表示しています。
Use when building, modifying, or reviewing a Stripe App — or when the user describes something that implies one (e.g. "add a panel to the customer page", "customize my Stripe Dashboard", "react to Stripe events from my app", "connect my service to Stripe without sharing API keys"). Covers the full app development workflow (scaffold, preview, upload, versioning), UI extension architecture (sandboxed iframe, Stripe UI toolkit, viewports), extension types (UI extensions, backend-only, extension interfaces, embedded apps), authentication (platform keys, OAuth, restricted API keys), stripe-app.yaml manifest setup (permissions, viewports, CSP), webhook configuration for apps, Secret Store API, `fetchStripeSignature` auth, and marketplace publishing, plus submitting one agentic feedback report after a build. Use when the user mentions Stripe Apps, UI extensions, @stripe/ui-extension-sdk, @stripe/extensibility-sdk, script extensions, stripe-app.yaml, Dashboard extensions, or customizing the Stripe Dashboard.
日本語の概要は準備中です。原文の説明を表示しています。
MongoDB schema design patterns and anti-patterns. Use when designing data models, reviewing schemas, migrating from SQL, or troubleshooting performance issues caused by schema problems. Triggers on "design schema", "embed vs reference", "MongoDB data model", "schema review", "unbounded arrays", "one-to-many", "tree structure", "16MB limit", "schema validation", "JSON Schema", "time series", "schema migration", "polymorphic", "TTL", "data lifecycle", "archive", "index explosion", "unnecessary indexes", "approximation pattern", "document versioning".
日本語の概要は準備中です。原文の説明を表示しています。
Deploy ML models on Kubernetes with KServe (formerly KFServing) and NVIDIA Triton Inference Server. Includes canary deployments, autoscaling, model versioning, A/B testing, and GPU resource management for production model serving.
日本語の概要は準備中です。原文の説明を表示しています。
Configure S3 buckets, policies, and lifecycle rules. Implement versioning, replication, and security. Use when managing object storage on AWS.
日本語の概要は準備中です。原文の説明を表示しています。
Designs REST or GraphQL APIs, creates OpenAPI specifications, and plans API architecture including resource modeling, versioning strategies, pagination patterns, and error handling standards.
日本語の概要は準備中です。原文の説明を表示しています。
Orchestrate end-to-end release pipelines. Use when running pre-release validation, generating changelogs, bumping semantic versions, scoring deployment readiness, or gating releases with secret scanning and GO/NO-GO checks.
日本語の概要は準備中です。原文の説明を表示しています。
Automates release management with changelog generation, semantic versioning, and release readiness checks. Use when preparing releases, generating changelogs, bumping versions, or validating release candidates.
日本語の概要は準備中です。原文の説明を表示しています。
Prompt engineering frameworks for building, testing, versioning, and evaluating prompts: chain-of-thought, few-shot, regression testing, and rubrics. Use when designing production prompts, running A/B tests, or building prompt libraries.
日本語の概要は準備中です。原文の説明を表示しています。
Review REST API designs for quality, consistency, and breaking changes. Lints OpenAPI specs, generates scorecards, and detects breaking changes between versions. Use when designing APIs, reviewing contracts, or managing API versioning.
日本語の概要は準備中です。原文の説明を表示しています。
Expert blueprint for save/load systems using JSON/binary serialization, PERSIST group pattern, versioning, and migration. Covers player progress, settings, game state persistence, and error recovery. Use when implementing save systems OR data persistence. Keywords save, load, JSON, FileAccess, user://, serialization, version migration, PERSIST group.
日本語の概要は準備中です。原文の説明を表示しています。
Expert knowledge for Azure Durable Task development including best practices, decision making, architecture & design patterns, limits & quotas, configuration, integrations & coding patterns, and deployment. Use when choosing Durable storage backends, versioning orchestrations, using fan-out/fan-in, human approvals, or instance APIs, and other Azure Durable Task related development tasks. Not for Azure Functions (use azure-functions), Azure Logic Apps (use azure-logic-apps), Azure App Service (use azure-app-service), Azure Service Fabric (use azure-service-fabric).
日本語の概要は準備中です。原文の説明を表示しています。
Expert knowledge for Azure Application Network development including decision making, and configuration. Use when enabling App Network logs, Azure Monitor metrics, AKS/App Gateway versioning, or upgrade compatibility, and other Azure Application Network related development tasks. Not for Azure Virtual Network (use azure-virtual-network), Azure Virtual Network Manager (use azure-virtual-network-manager), Azure Networking (use azure-networking), Azure Application Gateway (use azure-application-gateway).
日本語の概要は準備中です。原文の説明を表示しています。
Review REST API contracts for HTTP semantics, versioning, backward compatibility, and response consistency. Use when user asks "review API", "check endpoints", "REST review", or before releasing API changes.
日本語の概要は準備中です。原文の説明を表示しています。
Design, change, or review an HTTP/JSON API surface — endpoints, request/response shapes, authentication and authorization, pagination, idempotency, rate limits, versioning, and deprecations. Use when adding or modifying an HTTP endpoint, reviewing an OpenAPI spec or HTTP route diff, or deciding whether an HTTP API change breaks consumers. Do not use as a protocol-compatibility checklist for gRPC/protobuf, GraphQL, WebSockets, or other non-HTTP/JSON interfaces.
日本語の概要は準備中です。原文の説明を表示しています。
Apply REST API conventions — HTTP semantics, status codes, versioning, pagination, and OpenAPI standards for any framework. Use when designing endpoints, choosing HTTP methods, implementing pagination, or writing OpenAPI specs.
日本語の概要は準備中です。原文の説明を表示しています。
Module composition, state management, workspace strategy, provider versioning, and infrastructure-as-code best practices.
日本語の概要は準備中です。原文の説明を表示しています。
API design, versioning, testing, schema validation, and contract testing patterns for REST and GraphQL APIs.
日本語の概要は準備中です。原文の説明を表示しています。
Git history'den otomatik changelog, semantic versioning, release notes, conventional commits
日本語の概要は準備中です。原文の説明を表示しています。
Manage Git branching strategies, commit conventions, and collaboration workflows. Use when choosing between trunk-based development, GitHub Flow, or GitFlow, implementing conventional commits for automated versioning, setting up Git hooks for quality gates, or organizing monorepos with clear ownership.
日本語の概要は準備中です。原文の説明を表示しています。
Strategic guidance for operationalizing machine learning models from experimentation to production. Covers experiment tracking (MLflow, Weights & Biases), model registry and versioning, feature stores (Feast, Tecton), model serving patterns (Seldon, KServe, BentoML), ML pipeline orchestration (Kubeflow, Airflow), and model monitoring (drift detection, observability). Use when designing ML infrastructure, selecting MLOps platforms, implementing continuous training pipelines, or establishing model governance.
日本語の概要は準備中です。原文の説明を表示しています。
API design and implementation across REST, GraphQL, gRPC, and tRPC patterns. Use when building backend services, public APIs, or service-to-service communication. Covers REST frameworks (FastAPI, Axum, Gin, Hono), GraphQL libraries (Strawberry, async-graphql, gqlgen, Pothos), gRPC (Tonic, Connect-Go), tRPC for TypeScript, pagination strategies (cursor-based, offset-based), rate limiting, caching, versioning, and OpenAPI documentation generation. Includes frontend integration patterns for forms, tables, dashboards, and ai-chat skills.
日本語の概要は準備中です。原文の説明を表示しています。
Data pipelines, feature stores, and embedding generation for AI/ML systems. Use when building RAG pipelines, ML feature serving, or data transformations. Covers feature stores (Feast, Tecton), embedding pipelines, chunking strategies, orchestration (Dagster, Prefect, Airflow), dbt transformations, data versioning (LakeFS), and experiment tracking (MLflow, W&B).
日本語の概要は準備中です。原文の説明を表示しています。
Use when you need framework-agnostic OpenAPI 3.x guidance — spec structure, metadata and versioning, paths and operations, reusable schemas, security schemes, examples, documentation quality, contract validation (e.g. Spectral), breaking-change awareness, and handoffs to codegen — without choosing Spring Boot, Quarkus, or Micronaut. This should trigger for requests such as Review an OpenAPI; Improve an OpenAPI; Improve API contract; Improve API schema design. Part of Plinth Toolkit
日本語の概要は準備中です。原文の説明を表示しています。