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Cloud Worker용 도구가 미리 설치된 이미지를 만들고 선택해 시작 시간과 세션 작동을 검증합니다. 실패 시 이전 선택으로 복원하고 승인 후 기존 이미지를 삭제합니다.

• 필요한 도구를 미리 설치한 이미지 생성
• 이미지 변경 전후의 시작 시간 비교
• 새 이미지에서 세션 작동 확인

Run installation, integration, and end-to-end tests that follow real user actions in remote environments or Docker. Choose an appropriate isolated environment, inspect failures, record execution details, and clean up resources after testing.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Testing package installation in a clean environment
• Verifying an integration with a real service
• Checking behavior across macOS, Windows, and WSL2

Build or review Java Spring Boot backends using examples for web APIs, separate application layers, and database access. Covers input validation, error handling, caching, background processing, and logging to guide maintainable implementations.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Designing web APIs and separating application layers
• Reviewing database access and transactions
• Adding input validation and centralized error handling

Build or review Java services with Quarkus 3.x using patterns for REST APIs, database access with Panache, and messaging with Apache Camel. Examples cover layered code structure, validation, transactions, and asynchronous processing, where work completes separately from the main flow.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Designing a REST API with separate service and repository layers
• Connecting services through Camel and RabbitMQ
• Reviewing Panache database access and transactions

Develop and refactor Quarkus 3.x LTS services by writing tests first. Covers API responses, event handling, and asynchronous operations, with unit and integration tests plus coverage checks to show how much code is tested.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Adding REST endpoints with tests first
• Reproducing bugs before fixing them
• Testing Apache Camel routes and event handling

Design and review Prisma database code for TypeScript backends. Use examples for schemas, queries, transactions, pagination, migrations, and connection management to identify common pitfalls in bulk operations and serverless deployments.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Designing database models and relationships with Prisma
• Reviewing queries and pagination
• Investigating transaction and bulk update problems

Set up GPU servers on Lambda Labs for machine learning training and inference. Follow workflows for SSH access, persistent storage, Python API operations, and distributed training that spreads work across multiple GPUs or servers.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Set up a GPU server for long training jobs
• Fine-tune a large language model across multiple GPUs
• Keep datasets and checkpoints between sessions

Prepare LLM training datasets with NeMo Curator by removing duplicates, filtering low-quality content, and redacting personal information. The skill also covers image, video, and audio curation, including GPU processing and distributed workflows.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Clean web-scraped text for LLM training
• Remove exact, near, and meaning-based duplicates
• Remove or replace personal information in text

Guides implementation and maintenance of Claude applications using language-specific references and official SDKs, the libraries used to call the API. Covers tool integration, streaming responses, model migration, cost reviews, prompt audits, and evaluation workflows.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Adding Claude API calls to an application
• Building an agent that uses custom tools
• Migrating existing Claude integrations to another model

Migrate code and API calls from Claude Sonnet 4.0, Sonnet 4.5, or Opus 4.1 to Opus 4.5. Update platform-specific model identifiers and address reported prompt behavior issues, such as excessive tool use or unnecessary code complexity.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Updating model identifiers in existing code
• Migrating API settings for a specific platform
• Adjusting prompts that trigger excessive tool use

Publish a folder of static HTML and assets to the configured Paperclip S3/CloudFront host. Validate the folder before upload, obtain a persistent public URL, and update an existing page from its original publishing directory.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Sharing a static report through a persistent URL
• Publishing an HTML prototype or viewer
• Checking a site's structure and URL before publishing

Configure a RuView sensing deployment, including WiFi settings, detection thresholds, processing on devices, and coordinated nodes. It covers device provisioning, server options, firmware variants, and Cognitum Seed integration to adjust how the system operates.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Adjust WiFi channels and transmitter filters
• Tune presence, fall, and vital sensing settings
• Configure coordinated sensing across multiple nodes

Get RuView running with a Docker demo using simulated WiFi signal data, source checks, or live sensing with supported hardware. Choose a starting path based on available equipment and open a working sensing dashboard.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Try the dashboard without sensing hardware
• Explore the API or develop the interface using simulated data
• Check the Rust build and Python verification

Set up RuView sensing nodes by building and flashing ESP32 firmware, configuring WiFi and the receiving address, and checking serial logs. Diagnose missing CSI streams, the WiFi signal measurements sent by sensing nodes.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Setting up a new RuView sensing node
• Reflashing firmware for an 8 MB or 4 MB ESP32-S3
• Configuring WiFi and the receiving server

Set up an ESP32-S3/C6 sensing node for RuView by choosing firmware, checking and flashing binaries, and configuring WiFi and capture settings. Use boot logs to confirm CSI, measurements of the WiFi channel, is being captured.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choosing firmware for an ESP32 board
• Flashing firmware after checksum verification
• Configuring WiFi, channels, and MAC filters

Turn specifications and algorithm outlines into a system architecture. Define components, interfaces, data structures, and deployment plans, then document technology choices, security measures, failure handling, and plans for supporting increased usage.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Turn specifications into a system design
• Define component responsibilities and API interfaces
• Plan for increased traffic and component failures

Build Claude applications using guidance for the official Anthropic SDK. Choose an integration approach, implement streaming and tool use, and follow workflows for model migration, prompt audits, evaluation, and cost optimization.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build a summarization app with Claude API
• Choose how to run an agent with custom tools
• Migrate existing code to a newer Claude model

Guide HyperFrames video projects from setup through layout checks, editable previews, and video output. Covers command-line workflows, environment troubleshooting, and distributed rendering on AWS Lambda, which splits video rendering work across cloud functions.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Setting up a HyperFrames video project
• Checking text overflow and scene display
• Exporting a video after reviewing it in Studio

Guide HyperFrames video projects from setup and component selection through checks, previews, and rendering. Use command-line tools to inspect timelines, diagnose failures, compare frames, and choose local, batch, or cloud rendering for the finished composition.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Set up and preview a HyperFrames video project
• Diagnose build or rendering failures
• Render multiple videos from variable data

Publish updated Chrome binaries to Remotion Lambda’s test region, update layer references and version documentation, and verify rendering with Docker before rolling the update out to all supported regions.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Test a Chrome update before regional rollout
• Update Lambda layer references and Chrome version documentation
• Verify rendering with Docker across platforms

Guide test writing, updates, and reviews in Remotion by checking observable user outcomes. Choose integration, unit, visual, or end-to-end tests that detect broken workflows, and verify that bug fixes address the original regression.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choose a test boundary for a feature
• Review whether existing tests detect broken workflows
• Verify a regression test fails before the fix and passes after it

Create product demos, explainers, and social clips by choosing among AI footage, virtual presenters, code-based video templates, and editing tools. The skill guides scripts, visuals, captions, reusable production workflows, and exports suited to the target platform.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Creating a product demo with screen recordings and captions
• Producing an explainer with an AI presenter
• Generating multiple social clips from one template

Manage files and storage buckets in Tigris through its official CLI. Agents can upload and download objects, generate temporary sharing URLs, take snapshots, and manage access keys and permissions with structured JSON output.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Upload, download, and copy files in Tigris
• Create temporary upload or download links
• Take a bucket snapshot before making changes

Choose tools and workflows for 3D modeling, dimensioned CAD parts, scan processing, rendering, and fabrication. Capability tables and recipes help connect tasks from photographs or initial designs to printable parts, CNC toolpaths, or game assets.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Plan a workflow from dimensioned CAD to 3D printing
• Model and export a game asset
• Reconstruct a 3D model from photographs