648 件 ・ 関連度順
概要と使いどころ
Documentation conventions for NeMo-RL. Covers docs/index.md updates and docstring format. Do NOT use for: bug fixes, test fixes, dependency bumps, refactoring, CI/CD changes, performance tuning, or any task that does not involve writing or updating documentation.
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。
GitHub Actions CI/CD pipeline configuration for Golang projects — workflow files for test, lint, SAST, coverage and vulnerability-scan jobs, Dependabot and Renovate config files, GoReleaser release pipelines, Docker build/push, repository security settings, and AI-driven PR review. Use when setting up or improving Go project CI, writing or fixing `.github/workflows/*.yml`, adding a linter or security scanner as a pipeline job, wiring automated dependency-update bots, or adding quality gates. Covers wiring tools into a pipeline, not the analysis they perform: do NOT use for choosing or interpreting security findings (→ See `samber/cc-skills-golang@golang-security` skill) or for choosing, upgrading, or auditing dependency versions (→ See `samber/cc-skills-golang@golang-dependency-management` skill).
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Deploy to Cloudflare (Workers, R2, D1), Docker, GCP (Cloud Run, GKE), Kubernetes (kubectl, Helm). Use for serverless, containers, CI/CD, GitOps, security audit.
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 deploying an existing web application or API to an already-running Azure Kubernetes Service cluster. Detects the framework, generates a Dockerfile and Kubernetes manifests, validates against AKS Deployment Safeguards, and deploys with verification. WHEN: deploy app to AKS, deploy to existing AKS cluster, containerize app for Kubernetes, generate K8s manifests for Azure, set up CI/CD for AKS, my AKS deployment is failing safeguard checks, I have a Django/Express/Spring Boot app to run on AKS. DO NOT USE FOR: creating or provisioning an AKS cluster (use azure-kubernetes), assessing migration to AKS Automatic (use azure-kubernetes-automatic-readiness), or deploying to non-AKS targets like Web Apps, Container Apps, or Functions.
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Build, deploy, evaluate, optimize, fine-tune, and manage Microsoft Foundry agents, models, and resources end to end. USE FOR: foundry, azd ai agent, azd provision/deploy, hosted agent scaffold/develop/run/deploy/troubleshoot, prompt agent create, create agent, update agent, add tool to agent, invoke agent, agent.yaml, agent insights, pull agent insights, evaluate agent, batch eval, continuous eval, continuous monitoring, agent CI/CD, optimize prompt, improve prompt, prompt optimizer, optimize agent instructions, Agent Optimizer scaffold, dataset curation from traces, deploy model, model fine-tuning (SFT/DPO/RFT), Foundry project, RBAC, role assignment, permissions, quota, capacity, region, deployment failure, AI Services, create Foundry resource, knowledge index, customize deployment, onboard, availability, training-data, grader, distillation, large file upload. DO NOT USE FOR: Azure Functions, App Service, general Azure deploy (use azure-deploy), general Azure prep (use azure-prepare).
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。
Run Playwright tests at scale using Azure Playwright Workspaces (formerly Microsoft Playwright Testing). Use when scaling browser tests across cloud-hosted browsers, integrating with CI/CD pipelines, or publishing test results to the Azure portal.
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 measuring or improving agent quality and performance — set up evaluators, online monitoring, CI/CD quality gates, observability, or cost optimization. Triggers on: "evaluate my agent", "add evaluator", "measure quality", "quality gate", "run evals", "agent too slow", "why is it slow", "reduce latency", "set up observability", "CloudWatch dashboard", "how much does my agent cost", "cost optimization", "logs not showing up", "logs missing", "spans not found", "eval failing", "eval error", "dev traces", "local traces", "agentcore dev traces", "traces to CloudWatch". Not for debugging errors or crashes — use agents-debug. Slow but correct routes here; broken routes to debug.
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。
Sets up CloudWatch observability for the first time - Omni (CloudWatch Application Observability) and classic CloudWatch. Omni: creating a Space or Domain; access grants (who has access, at what level) and access profiles bounding async alerts, integrations, or agents; instrumenting an app or AI agent with the plain ADOT SDK so traces reach Omni (Python/Node/Java/.NET on EC2/ECS/EKS/Lambda), incl. no-image-rebuild and .NET CoreCLR vars; ingesting Azure telemetry via the CloudWatch agent on an Azure VM or AKS; connecting Slack to a Space; whether GitHub or a custom MCP tool server (HTTP/stdio; API key, bearer, OAuth2) can be connected. CloudWatch: onboarding a service to Application Signals - ADOT auto-instrumentation, the amazon-cloudwatch-observability add-on, monitored service, reporting telemetry, ServiceEvents, CI/CD git/deployment metadata, Terraform/manifest edits. For using what is set up - queries, dashboards, alarms, Omni alerts, X-Ray, synthetics, Dynamic Instrumentation - use aws-observability.
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。
Builds, configures, debugs, and optimizes AWS observability - operator-symptom questions and detecting Omni vs classic CloudWatch. CloudWatch on an already-reporting service: Log Insights, metric/composite/anomaly alarms, custom metrics/EMF, dashboards, X-Ray/ADOT tracing, canaries, CloudTrail, Dynamic Instrumentation (live breakpoints/snapshots), the Application Signals service map, and fleet health views. CloudWatch Omni on an existing Space: SQL over logs and traces, PromQL over metrics, Omni dashboards, Omni alerts, context graph for root cause, programmatic/IaC access (API/SDK/CLI/CloudFormation), driving Omni from a coding agent or skills, and evaluating AI agent quality from traces - on-demand and online scoring of live traffic, readback, custom evaluators. For first-time setup - creating an Omni Space, granting access, ingestion, or ADOT instrumentation for Application Signals (ServiceEvents, CI/CD metadata) or Omni - use setting-up-cloudwatch-observability. Not for app logging or threat detection.
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 CI/CD pipeline for AppFolio property management integrations. Trigger: "appfolio CI".
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。
Audit and harden Anima and Figma tokens for design-to-code pipelines. Use when protecting API credentials, restricting Figma access scope, or hardening CI/CD design automation pipelines. Trigger with: "anima security", "anima token safety", "figma token security".
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 automated Figma-to-React pipeline with the Anima SDK. Use when automating design handoff, building CI/CD design-to-code workflows, or creating a design system code generator from Figma components. Trigger with: "anima design pipeline", "figma to react pipeline", "automated design handoff", "anima component generator".
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 readiness checklist for Anima design-to-code pipelines. Use when deploying automated design-to-code services, preparing CI/CD Figma-to-code automation, or validating output quality before production. Trigger with: "anima production", "anima go-live", "anima prod checklist".
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 CI/CD pipeline for automated Figma-to-code generation with Anima. Use when automating design-to-code in GitHub Actions, setting up PR-based component generation, or integrating Anima into design handoff workflows. Trigger with: "anima CI", "anima GitHub Actions", "anima automated generation".
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 and orchestrate Vertex AI ADK agents using A2A protocol. Manages AgentCard discovery, task submission, Code Execution Sandbox, and Memory Bank. Use when asked to "deploy ADK agent" or "orchestrate agents". Trigger with phrases like 'deploy', 'infrastructure', or 'CI/CD'.
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。
Helps understand and write EAS workflow YAML files for Expo projects. Use this skill when the user asks about CI/CD or workflows in an Expo or EAS context, mentions .eas/workflows/, or wants help with EAS build pipelines or deployment automation.
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。
CI/CD pipeline patterns for GitHub Actions, GitLab CI, testing strategies, and deployment automation
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。
CI/CD pipeline design with GitHub Actions, Docker, Kubernetes, Helm, and GitOps 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。
Deploy to Cloudflare (Workers, R2, D1), Docker, GCP (Cloud Run, GKE), Kubernetes (kubectl, Helm). Use for serverless, containers, CI/CD, GitOps, security audit.
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。
Automate GitHub repositories, issues, pull requests, branches, CI/CD, and permissions via Rube MCP (Composio). Manage code workflows, review PRs, search code, and handle deployments programmatically.
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。
Playwright E2E 测试模式、页面对象模型（POM）、配置、CI/CD 集成、产物管理以及不稳定测试（flaky test）策略。
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。
部署工作流、CI/CD流水线模式、Docker容器化、健康检查、回滚策略以及Web应用程序的生产就绪检查清单。
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。
Playwright E2E 测试模式、页面对象模型、配置、CI/CD 集成、工件管理和不稳定测试策略。
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。
Playwright E2E 测试模式、页面对象模型 (Page Object Model)、配置、CI/CD 集成、产物管理以及不稳定测试 (Flaky Test) 策略。
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。