2.5천건 · 관련도순
Use when working with Azure Devops — azure DevOps comprehensive management. Covers pipelines, boards, repositories, artifacts, test plans, work item tracking, and release management. Use when checking pipeline status, managing work items, investigating build failures, or auditing Azure DevOps project configurations.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when working with Bazel — bazel build system management. Covers BUILD file analysis, target querying, dependency graphs, remote execution, caching configuration, and build performance profiling. Use when managing Bazel workspaces, debugging build failures, querying targets, or optimizing build performance.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when working with Aws Codebuild — aWS CodeBuild project management and build analysis. Covers build project inventory, build history, build phase details, environment configurations, source credentials, report groups, and build metrics. Use when inspecting build projects, debugging build failures, reviewing build environments, or analyzing build performance.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when working with Aws App Runner — aWS App Runner service management and health analysis. Covers service inventory, deployment status, auto-scaling configurations, custom domain associations, VPC connector settings, and observability configurations. Use when inspecting App Runner services, debugging deployment failures, reviewing scaling behavior, or auditing service configurations.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when working with Ansible — ansible automation and configuration management. Covers playbook execution, inventory management, role management, vault secrets, ad-hoc commands, fact gathering, and task debugging. Use when running playbooks, managing inventories, debugging task failures, or auditing Ansible configurations.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when working with Aws Amplify — aWS Amplify application management and deployment analysis. Covers Amplify apps, branches, backend environments, build status, domain associations, and webhook configurations. Use when inspecting Amplify deployments, debugging build failures, reviewing hosting configurations, or auditing Amplify app settings.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when working with Argocd — argoCD GitOps continuous delivery management for Kubernetes. Covers application sync status, deployment health, rollback operations, repository management, cluster registration, RBAC analysis, and application diff review. Use when checking deployment status, investigating sync failures, managing GitOps applications, or auditing ArgoCD configurations.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when working with Argo Workflows — argo Workflows management for Kubernetes-native workflow orchestration. Covers workflow templates, cron workflow scheduling, artifact management, workflow execution, parameter handling, and resource monitoring. Use when checking workflow status, investigating step failures, managing templates, or auditing cron workflows.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when working with Apache Druid Deep — apache Druid deep management — monitor cluster health, datasources, ingestion tasks, segments, query performance, and coordinator/overlord status. Use when debugging ingestion failures, inspecting segment distribution, optimizing query latency, or auditing cluster capacity.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when working with Apache Airflow Deep — apache Airflow deep management covering DAG inventory, task instance monitoring, scheduler health, executor status, pool and variable management, connection auditing, and SLA miss tracking. Use when investigating DAG failures, analyzing task duration trends, monitoring scheduler performance, or auditing Airflow configurations.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when working with Airflow — apache Airflow workflow orchestration management. Covers DAG management, task instance monitoring, executor health, pool status, variable management, connection audit, and scheduler diagnostics. Use when checking DAG run status, investigating task failures, managing Airflow resources, or auditing configurations.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when working with Airbyte — airbyte data integration platform management. Covers connection status monitoring, sync job tracking, source and destination health, schema change detection, workspace management, and connector upgrades. Use when checking sync status, investigating job failures, managing Airbyte connections, or auditing data pipeline configurations.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when working with Aws Step Functions — aWS Step Functions execution analysis, state machine management, error tracking, and performance optimization. Covers execution history, failure investigation, state transition metrics, Express vs Standard comparison, and workflow visualization.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when working with Azure App Insights — application Insights request performance, dependency tracking, availability tests, smart detection, and failure analysis via Azure CLI and Log Analytics queries.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when working with Aws Batch — aWS Batch compute environment management, job queue analysis, scheduling policy review, and array job monitoring. Covers compute resource utilization, job status tracking, failure investigation, Fargate vs EC2 comparison, and queue priority analysis.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when working with Great Expectations — great Expectations data quality framework analysis. Covers expectation suite management, validation result review, data docs generation, checkpoint execution, datasource configuration, and batch analysis. Use when reviewing data quality results, managing expectation suites, investigating validation failures, or auditing data quality configurations.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when working with Aws Ecs — aWS ECS cluster health, service status, task analysis, capacity provider management, and deployment tracking. Covers service stability, task failure investigation, container insights, resource utilization, and scaling analysis.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use after generating code, after accepting AI suggestions, or when reviewing AI-written modules. Also use when code works but feels brittle, when error handling seems thin, when orphaned resources or missing cleanup are suspected, or when the agent claims done but hidden debt may exist. Catches the specific failure patterns AI agents produce that humans would not.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Understand how ideas evolved over time to find old solutions for new problems and avoid repeating past failures
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when doing ANY task involving Supabase. Triggers: Supabase products (Database, Auth, Edge Functions, Realtime, Storage, Vectors, Cron, Queues); client libraries and SSR integrations (supabase-js, @supabase/ssr) in Next.js, React, SvelteKit, Astro, Remix; auth issues (login, logout, sessions, JWT, cookies, getSession, getUser, getClaims, RLS); Supabase CLI or MCP server; schema changes, migrations, declarative schemas, security audits, Postgres extensions (pg_graphql, pg_cron, pg_vector); debugging and troubleshooting errors or unexpected behavior on Supabase projects (HTTP errors, Postgres errors, RLS surprises, permission denied, schema cache issues, timeouts, Edge Function crashes, Realtime drops, Storage failures) and reading or querying logs (Logs Explorer, ClickHouse).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
RED-GREEN-REFACTOR for process documentation - baseline without skill, write addressing failures, iterate closing loopholes
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Deploy and configure web frameworks on Netlify — build settings and SSR/edge adapters plus local platform emulation and env vars. Use when setting up or fixing a framework deploy (Next.js / Astro / Nuxt / SvelteKit / Remix / React Router / TanStack Start / SolidStart / Gatsby / Angular / Vite / Express / Hydrogen / Hugo / Eleventy / Vue / React), adding SSR or edge functions or middleware wired to Netlify context, fixing SPA redirect and catch-all rules, setting a build command or publish directory, or debugging "why isn't my env var updating" and framework build failures.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Optimize MongoDB client connection configuration (pools, timeouts, patterns) for any supported driver language. Use this skill when working/updating/reviewing on functions that instantiate or configure a MongoDB client (eg, when calling `connect()`), configuring connection pools, troubleshooting connection errors (ECONNREFUSED, timeouts, pool exhaustion), optimizing performance issues related to connections. This includes scenarios like building serverless functions with MongoDB, creating API endpoints that use MongoDB, optimizing high-traffic MongoDB applications, creating long-running tasks and concurrency, or debugging connection-related failures.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
AI demos and GPU compute with Gradio Spaces and Hugging Face Spaces ZeroGPU. Use when writing or reviewing code that uses `@spaces.GPU`, configuring `python_version` or `requirements.txt` for a ZeroGPU Space, or handling ZeroGPU-specific code constraints — pickle-based process isolation, `gr.State` semantics across the worker boundary, no `torch.compile` (use AoTI instead), CUDA wheel-only builds (no `nvcc` at build or runtime), large vs xlarge sizing, and dynamic duration callables. Make sure to use this skill whenever the user mentions ZeroGPU, `@spaces.GPU`, or the `spaces` Python package, or hits ZeroGPU-specific code errors like `PicklingError` across the worker boundary, `illegal duration`, or `flash-attn` wheel-build failures — even when the user does not explicitly ask for ZeroGPU coding guidance. Trigger on `import spaces` or `@spaces.GPU` in code.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.