1.3천건 · 관련도순
Prepare pathology image datasets by detecting tissue in whole slide images and extracting smaller image tiles. Use random, grid, or score-based selection, preview extraction locations, and apply preprocessing filters to review and prepare the resulting tiles.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Plan, configure, and chain repo-native Nemotron customization steps into single-step or multi-step pipelines: curation, translation, SFT/PEFT (AutoModel or Megatron-Bridge), pretraining/CPT, RL alignment (DPO/RLVR/GRPO/RLHF), BYOB/MCQ benchmarks, checkpoint conversion, ModelOpt optimization, env profiles, and evaluation of trained checkpoints or existing/hosted endpoints. Use when a request names a Nemotron step or workflow, or asks to clean, translate, train, fine-tune, align, convert, optimize, evaluate, or compose these into a pipeline. Do NOT use for frontend/dashboard/visualization work, generic ML advice, billing/access, or non-Nemotron coding tasks.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Build DeepStream GStreamer pipelines interactively. Use when the user asks about pipelines for video/image inference, detection, tracking, or streaming — including natural phrases like 'pipeline to infer on image', 'run inference on video', 'detect objects in stream', 'save inference output', 'deepstream pipeline', 'gst-launch pipeline', 'process video with detection', 'build a pipeline', or any request involving GStreamer/DeepStream elements (nvinfer, nvstreammux, nvtracker, etc.).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Reactive streams and event-driven programming in Golang using samber/ro — ReactiveX implementation with 150+ type-safe operators, cold/hot observables, 5 subject types (Publish, Behavior, Replay, Async, Unicast), declarative pipelines via Pipe, 40+ plugins (HTTP, cron, fsnotify, JSON, logging), automatic backpressure, error propagation, and Go context integration. Apply when using or adopting samber/ro, when the codebase imports github.com/samber/ro, or when building asynchronous event-driven pipelines, real-time data processing, streams, or reactive architectures in Go. Not for finite slice transforms (→ See `samber/cc-skills-golang@golang-samber-lo` skill).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Build and troubleshoot Cloudflare Basin analytics workflows with Basin Pipelines, Basin Catalog, and Basin SQL. Use for streaming data into R2 Iceberg tables, managing catalogs, or querying those tables; also use for requests using the former Data Platform, Pipelines, R2 Data Catalog, or R2 SQL names.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Configures CI/CD pipelines using AWS CodePipeline, CodeBuild, CodeDeploy, CodeConnections, and CodeArtifact. Covers CodePipeline V2 (triggers, variables, execution modes, cross-account), buildspec.yml (caching, VPC, Docker), CodeDeploy strategies (blue/green, canary, linear), CodeArtifact (private package registries, auth tokens, cross-account), and source connections (GitHub, GitLab, Bitbucket). Applies when CodePipeline, CodeBuild, CodeDeploy, CodeConnections, CodeArtifact, buildspec.yml, appspec.yml, or CI/CD pipeline orchestration is referenced. Does NOT cover: ECS Fargate services or task definitions (use aws-containers), CDK Pipelines or cdk deploy (use aws-cdk), sam deploy (use aws-serverless), Amplify deployments (use aws-amplify), or GitHub Actions/GitLab CI.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Implement Apify webhooks for Actor run notifications and event-driven pipelines. Use when setting up run completion alerts, building event-driven scraping pipelines, or configuring ad-hoc webhooks for individual runs. Trigger with "apify webhook", "apify events", "actor run notification", "apify run succeeded webhook", "apify ad-hoc webhook".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
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".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
World-class data engineering skill for building scalable data pipelines, ETL/ELT systems, real-time streaming, and data infrastructure. Expertise in Python, SQL, Spark, Airflow, dbt, Kafka, Flink, Kinesis, and modern data stack. Includes data modeling, pipeline orchestration, data quality, streaming quality monitoring, and DataOps. Use when designing data architectures, building batch or streaming data pipelines, optimizing data workflows, or implementing data governance.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Build end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment. Use when creating ML pipelines, implementing MLOps practices, or automating model training and deployment workflows.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Guides Docker, CI/CD pipelines, deployment strategies, infrastructure as code, and observability setup. Use when writing Dockerfiles, configuring GitHub Actions, planning deployments, setting up monitoring, or when asked about containers, pipelines, Terraform, or production infrastructure.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Scalable data processing for ML workloads. Streaming execution across CPU/GPU, supports Parquet/CSV/JSON/images. Integrates with Ray Train, PyTorch, TensorFlow. Scales from single machine to 100s of nodes. Use for batch inference, data preprocessing, multi-modal data loading, or distributed ETL pipelines.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Manages Fabric deployment pipelines for ALM promotion across dev, test, and prod stages, including stage creation, workspace assignment, selective forward or backward deploys, operation polling, stage role assignments, and the pipeline and workspace permissions each action requires. For Git sync use git-integration-operations-cli.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Generate read-only MongoDB queries (find) or aggregation pipelines using natural language, with collection schema context and sample documents. Use this skill whenever the user asks to write, create, or generate MongoDB queries, wants to filter/query/aggregate data in MongoDB, asks "how do I query...", needs help with query syntax, or discusses finding/filtering/grouping MongoDB documents. Also use for translating SQL-like requests to MongoDB syntax. Does NOT handle Atlas Search ($search operator), vector/semantic search ($vectorSearch operator), fuzzy matching, autocomplete indexes, or relevance scoring - use search-and-ai for those. Does NOT analyze or optimize existing queries - use mongodb-query-optimizer for that. Does NOT handle aggregation pipelines that involve write operations. Requires MongoDB MCP server.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Build and troubleshoot Cloudflare Basin analytics workflows with Basin Pipelines, Basin Catalog, and Basin SQL. Use for streaming data into R2 Iceberg tables, managing catalogs, or querying those tables; also use for requests using the former Data Platform, Pipelines, R2 Data Catalog, or R2 SQL names.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Set up Azure Pipelines for CI/CD, configure build and release pipelines, manage Azure DevOps projects, and integrate with Azure services. Use when working with Azure DevOps Services or Server for enterprise DevOps workflows.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
ML engineering skill for productionizing models, building MLOps pipelines, and integrating LLMs. Covers model deployment, feature stores, drift monitoring, RAG systems, and cost optimization.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Design and generate CI/CD pipelines from project stack signals across GitHub Actions, GitLab CI, CircleCI, and Buildkite. Use when bootstrapping CI, migrating pipelines, adding deployment gates, or optimizing build times.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Expert-level toolkit for modular Godot 4.7+ CLI automation and headless build orchestration. Use when you need to: (1) Build complex scene trees or UI layouts programmatically, (2) Automate expert 3D asset pipelines (glTF -> Collision), (3) Optimize procedural geometry headlessly (CSG -> Static Mesh), or (4) Engineer production-grade CI/CD pipelines. Set GODOT_PATH env var for custom engine location. Keywords: Godot CLI, headless, CI, export, builder, 4.7.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Expert-level toolkit for modular Godot 4.7+ CLI automation and headless build orchestration. Use when you need to: (1) Build complex scene trees or UI layouts programmatically, (2) Automate expert 3D asset pipelines (glTF -> Collision), (3) Optimize procedural geometry headlessly (CSG -> Static Mesh), or (4) Engineer production-grade CI/CD pipelines. Set GODOT_PATH env var for custom engine location. Keywords: Godot CLI, headless, CI, export, builder, 4.7.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Expert knowledge for Azure Test Plans development including limits & quotas, security, configuration, and integrations & coding patterns. Use when configuring test failure types, custom fields, retention, permissions, or tcm.exe-based test suite automation, and other Azure Test Plans related development tasks. Not for Azure DevOps (use azure-devops), Azure Pipelines (use azure-pipelines), Azure Boards (use azure-boards), Azure App Testing (use azure-app-testing).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Expert knowledge for Azure Repos development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, and integrations & coding patterns. Use when managing Git/TFVC repos, branch policies/PR checks, TFVC→Git migrations, large files, or security scanning, and other Azure Repos related development tasks. Not for Azure DevOps (use azure-devops), Azure Pipelines (use azure-pipelines), Azure Boards (use azure-boards), Azure Artifacts (use azure-artifacts).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Expert knowledge for Playwright Workspaces development including troubleshooting, best practices, decision making, limits & quotas, security, and configuration. Use when managing Playwright Testing workspaces, tokens/RBAC, quotas, monitoring/metrics, or run/AADSTS7000112 issues, and other Playwright Workspaces related development tasks. Not for Azure App Testing (use azure-app-testing), Azure DevOps (use azure-devops), Azure Pipelines (use azure-pipelines), Azure Test Plans (use azure-test-plans).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Expert knowledge for Azure App Testing development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when running Azure Load Testing, Playwright Workspaces, JMeter/Locust tests, private endpoint/VNet tests, or CI/CD runs, and other Azure App Testing related development tasks. Not for Azure Test Plans (use azure-test-plans), Azure DevOps (use azure-devops), Azure Pipelines (use azure-pipelines), Azure App Service (use azure-app-service).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.