「production」の検索結果

Provides AWS CloudFormation patterns for CloudWatch monitoring, metrics, alarms, dashboards, logs, and observability. Use when creating CloudWatch metrics, alarms, dashboards, log groups, log subscriptions, anomaly detection, synthesized canaries, Application Signals, and implementing template structure with Parameters, Outputs, Mappings, Conditions, cross-stack references, and CloudWatch best practices for monitoring production infrastructure.

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。

Provides patterns to deploy ECS tasks and services with GitHub Actions CI/CD. Use when building Docker images, pushing to ECR, updating ECS task definitions, deploying ECS services, integrating with CloudFormation stacks, configuring AWS OIDC authentication for GitHub Actions, and implementing production-ready container deployment pipelines. Supports ECS deployments with proper security (OIDC or IAM keys), multi-environment support, blue/green deployments, ECR private repositories with image scanning, and CloudFormation infrastructure updates.

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。

Provides configuration patterns for LangChain4J vector stores in RAG applications. Use when building semantic search, integrating vector databases (PostgreSQL/pgvector, Pinecone, MongoDB, Milvus, Neo4j), implementing embedding storage/retrieval, setting up hybrid search, or optimizing vector database performance for production AI applications.

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。

Provides patterns to configure Spring Boot Actuator for production-grade monitoring, health probes, secured management endpoints, and Micrometer metrics across JVM services. Use when setting up monitoring, health checks, or metrics for Spring Boot applications.

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。

MLflow 3 GenAI agent evaluation. Use when writing mlflow.genai.evaluate() code, creating @scorer functions, using built-in scorers (Guidelines, Correctness, Safety, RetrievalGroundedness), building eval datasets from traces, setting up trace ingestion and production monitoring, aligning judges with MemAlign from domain expert feedback, or running optimize_prompts() with GEPA for automated prompt improvement.

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。

Comprehensive guide to Spark Structured Streaming for production workloads. Use when building streaming pipelines, working with Kafka ingestion, implementing Real-Time Mode (RTM), configuring triggers (processingTime, availableNow), handling stateful operations with watermarks, optimizing checkpoints, performing stream-stream or stream-static joins, writing to multiple sinks, or tuning streaming cost and performance.

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。

Production incident response automation. Reads logs, checks recent deploys, identifies root cause, suggests fixes, drafts incident comms, creates post-mortem templates. Severity classification (SEV1-4), escalation paths, status page updates. Generates incident-report.md with timeline, root cause, impact assessment, remediation steps, and prevention measures.

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。

Wire a System One model (Jev, or an open reproduction like Von) into a product feature — routing, guardrails, scoring, classification. Use when replacing an LLM call that returns a label rather than prose, when adding a typed decision to an agent loop, or when deciding between the hosted Jev API and a local open model. Covers question design, the eval-set-first workflow, threshold calibration, confidence gates, and the traps measured on real data.

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。

Compose a premium, animated landing page section by section in Next.js + Tailwind + Motion (Framer Motion) — built on a real design system, with editorial copy and motion that feels human-crafted, not template-generated. Use when building or rebuilding a landing page, marketing site, or hero/feature/pricing/CTA sections that need to look production-ready and bespoke from day one.

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。

Build, modify, debug, and cloud-validate VeADK Agents from an accepted product intent. Use for VeADK architecture, tools, workflows, memory, knowledge, executable AgentKit projects, local tests, and AgentKit build/deploy/invoke/log repair loops. Do not use for unrelated user requests, other Agent frameworks, standalone cloud administration, or production Runtime operations.

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。

Expedited workflow for urgent production issues

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。

Production-grade SwiftUI with Apple Design Award-quality aesthetics. Use when building visually striking iOS interfaces — screens, components, redesigns. Screenshot-driven visual iteration, Liquid Glass (iOS 26+), bold design direction. For design advice without code, use ios-design-consultant instead.

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。

Create production-quality Android applications following Google's official architecture guidance and NowInAndroid best practices. Use when building Android apps with Kotlin, Jetpack Compose, MVVM architecture, Hilt dependency injection, Room database, or multi-module projects. Triggers on requests to create Android projects, screens, ViewModels, repositories, feature modules, or when asked about Android architecture patterns.

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。

Standardizes release approvals with GitHub-aware checklists and deployment gates. Use before releasing to production to verify all gates pass.

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。

Tạo AI Skill mới từ ý tưởng hoặc quy trình công việc. Kết hợp phỏng vấn thông minh, pattern detection, và quantitative evaluation để tạo skill chất lượng production. Dùng khi user nói "tạo skill", "biến quy trình thành skill", "make a new skill", "tự động hóa công việc này", hoặc mô tả quy trình lặp lại mà họ muốn AI tự làm. Cũng dùng khi user muốn cải thiện, test, hoặc optimize skill hiện có.

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 Flair for NLP annotation, embeddings, text/sequence model prediction, corpus loading, training/fine-tuning, HunFlair biomedical NER/linking, and production troubleshooting.

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 FlashRAG for retrieval-augmented generation research workflows: config/data validation, retrieval and index building, generation/refinement components, RAG pipelines/method reproduction, evaluation, and WebUI setup.

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。

Routes Distil-Whisper inference, PyTorch distillation training, and Flax reproduction workflows.

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 this self-contained Browser Use repo skill for Python agents that automate websites, browser sessions, custom tools, LLM/provider setup, persistent CLI sessions, cloud/sandbox production deployment, MCP, skills, and troubleshooting. Prefer ChatBrowserUse by default and route to focused sub-skills for implementation details.

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 BentoML to author model-serving Services, build and containerize Bentos, run HTTP/gRPC servers and clients, manage models, operate the CLI and BentoCloud, and configure observability or production runtime behavior. Use when tasks mention BentoML, bentoml service.py, bentofile.yaml, Bento build/serve/deploy, BentoCloud, or BentoML model stores.

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 preparing a release, tagging a version, or when user says "release", "tag", "ship it", "push to production" - ensures all release artifacts are verified before tagging to avoid the retag-four-times failure pattern

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。

Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.

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。

Assemble a report-ready walkthrough.md for a SOLVED engagement - populate the Evidence gallery from the poc/ images captured during the engagement, and draft the step-by-step reproduction from state/loot/log (Killchain.md for pentest/bugbounty, state.md's Chain/Status for ctf) without fabricating. Use when asked to "write the walkthrough", "assemble the walkthrough", "close out the box/engagement", or at close-out once an engagement is marked SOLVED.

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。

Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.

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。