'spa' 검색 결과

Support routine Google Workspace administration by reviewing pending IT requests, checking suspicious logins and audit logs, and configuring Drive sharing policies. The guidance also covers permission checks and previews before bulk operations.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing pending IT requests at the start of the day
• Checking suspicious logins and audit logs
• Configuring organizational Drive sharing policies

Save agent memory and outputs in Cua Volume, shared storage that persists beyond a Space, the working environment. Hand files to the user, read shared references, and check synchronization, version history, and conflicting edits.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Keep outputs after a working environment ends
• Save agent memory for later work
• Deliver files to the user

Translate selected FastGPT interface text files from Simplified Chinese into every supported target locale. Check product terminology and interface context, preserve JSON structure and placeholders, and validate the translated files for consistency.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Translating a selected interface text file into all supported locales
• Updating several translation files together
• Translating every namespace from completed Chinese source text

Design systems that collect, transform, and store data. Choose between scheduled and continuous processing, generate workflow configurations, validate data quality, and analyze performance using guidance for tools including Python, SQL, Spark, Airflow, dbt, and Kafka.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Designing data ingestion and transformation pipelines
• Choosing scheduled or real-time data processing
• Checking data freshness, completeness, and uniqueness

Manage coding agents and their workspaces in Paseo through its tools or command line. This reference covers project registration, workspace scripts, agent settings, recurring tasks, and reminders that return to the current conversation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Creating separate workspaces for development tasks
• Starting and stopping configured workspace scripts
• Launching agents and adjusting their runtime settings

Design AI agent analytics workflows across distributed tables and documents. Combine Knowledge Catalog for metadata, meaning information about data and its usage rules, with managed Spark processing to produce architecture diagrams, deployment guidance, and validation plans.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Design analytics across data stored in multiple clouds
• Define metadata and governance with Knowledge Catalog
• Plan Data Agent Kit use in VS Code or Antigravity

Build, publish, and manage apps on 妙搭（Spark/Miaoda） through local development or cloud AI sessions. Create page designs, manage data and permissions, inspect logs and usage, and configure automated triggers.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build and publish a business app
• Create landing pages and interactive prototypes
• Inspect production logs and usage

Track machine learning experiments with Trackio by recording training measurements, viewing live dashboards, and flagging diagnostic events. Retrieve metrics and alerts through command-line queries, with JSON output for automated monitoring and experiment review.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Recording training loss and accuracy
• Flagging loss spikes or stalled training
• Monitoring cloud training through a Space dashboard

Manage separate workspaces for legal matters across multiple clients. Create matter records, list and switch active matters, archive closed work, or return to practice-level context while keeping each matter's information separate by default.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Creating a workspace for a new client matter
• Listing matters and switching the active workspace
• Archiving a closed matter while preserving its records

Configure and troubleshoot Apache Beam runners, the engines that execute data processing pipelines. Covers local testing, Dataflow, Flink, and Spark, with Java and Python examples, runner validation tests, and guidance on logs and execution settings.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Test a Beam pipeline locally
• Configure pipeline execution on Dataflow
• Review Flink or Spark execution settings

Manage Git user settings and authentication for a specific workspace. Set configuration values, register HTTPS access tokens, and import SSH keys, with options to list or remove credentials without exposing stored tokens or private keys in listings.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Setting Git user information for a workspace
• Registering an HTTPS access token
• Importing an SSH key for Git authentication

Find reusable skills in OpenSpace's local registry and explore its cloud library when needed. Review matching skills, choose where to import them locally, and decide whether to follow them or delegate the task.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Finding a skill for a specific task
• Checking which skills are available locally
• Exploring cloud skills when local results are insufficient

Generate and edit transparent PNG ornaments, game sprites, emblems, and interface graphics with built-in Codex image generation. Includes transparency checks, saved prompts, and optional integration into an existing project with verified asset copies.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Create transparent PNG decorations for game interfaces
• Generate standalone sprites and emblems
• Check PNG transparency and gaps within artwork

Improve interface layouts by reviewing spacing, alignment, content density, and visual hierarchy, the cues that show what matters most. Refine repetitive card grids and crowded sections into compositions with consistent spacing and responsive structure.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Adjusting spacing in a crowded interface
• Making important content easier to spot
• Varying repetitive card-based layouts

Understand SenseNova Team Harness, a workspace you host yourself for collaboration between people and local AI agents. Learn its core concepts, startup requirements, and workflow for assigning tasks, sharing input files, and reviewing versioned deliverables.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Assess whether SenseNova Team Harness fits a team
• Learn how shared spaces, tasks, and deliverables relate
• Get started with a self-hosted workspace

Search GitHub, Stack Overflow, Hacker News, and HuggingFace for code examples, projects, technical answers, discussions, models, datasets, and Spaces. Filter supported searches and receive structured JSON results containing titles, links, and snippets.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Find code examples and open-source projects
• Search technical answers and GitHub Issues
• Explore developer news and discussions

Map a single-page application's backend API from its public JavaScript files, including routes loaded later. Compare unauthenticated responses with a protected endpoint to investigate missing authentication and access control using minimal evidence.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Discovering backend API routes in public JavaScript
• Checking API authentication behind an SSO login
• Investigating routes in lazily loaded JavaScript files

Audit backlinks using Google Search Console reports and supplied exports. Review linking domains, link text, potentially spammy patterns, and links to key pages to identify internal linking opportunities and prioritize link building.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Review linking domains and link text
• Check for potentially spammy backlinks
• Find internal linking opportunities for revenue pages

Comprehensive geospatial science skill covering remote sensing, GIS, spatial analysis, machine learning for earth observation, and 30+ scientific domains. Supports satellite imagery processing (Sentinel, Landsat, MODIS, SAR, hyperspectral), vector and raster data operations, spatial statistics, point cloud processing, network analysis, and 7 programming languages (Python, R, Julia, JavaScript, C++, Java, Go) with 500+ code examples. Use for remote sensing workflows, GIS analysis, spatial ML, Earth observation data processing, terrain analysis, hydrological modeling, marine spatial analysis, atmospheric science, and any geospatial computation task.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use whenever the agent creates, writes, moves, or renames a file in a team/delegate (shared) workspace, OR when the user asks to organize, clean up, restructure, audit, or find files in any workspace or the Vault, OR when starting a multi-file task or named project. Enforces a purpose-based folder convention (flat mode: notes/, data/, outputs/, scripts/, archive/; project mode: projects/<slug>/{docs,assets,source,reports,research}/), per-agent namespacing under shared/<agent_key>/, and pre-write discovery via memory_search, vault_search, knowledge_graph_search to surface related files and avoid duplicates. Trigger before any write_file or exec at workspace root, when starting a project, generating reports/assets/exports, delegating, or when the user says "messy", "where did I save", "tổ chức lại", "dọn workspace", "tạo report", "find related", "search vault". Do NOT trigger for read-only ops, edits inside an existing project tree (cloned repo), or short-lived files deleted in the same turn.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Coordinate the AWS DevOps Agent across multiple AgentSpaces from one Claude Code session — route questions to the right space (prod vs staging vs knowledge), query several spaces in parallel and synthesize, or compare findings across accounts. Use whenever the user has more than one AgentSpace configured, mentions multiple AWS accounts, or asks something like "check both prod and staging", "compare across accounts", or "ask the knowledge space".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Execute arbitrary Python or PySpark code on Fabric Spark compute without creating a notebook artifact; ephemeral Livy sessions with full Delta table access. Automatically invoke when the user asks to "run PySpark in Fabric", "create a Livy session", "execute Python on Fabric compute", "run Spark without a notebook", "submit code to Fabric", "ephemeral Spark execution", "run ETL in Fabric".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Convert PyTorch AT_DISPATCH macros to AT_DISPATCH_V2 format in ATen C++ code. Use when porting AT_DISPATCH_ALL_TYPES_AND*, AT_DISPATCH_FLOATING_TYPES*, or other dispatch macros to the new v2 API. For ATen kernel files, CUDA kernels, and native operator implementations.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Apache Spark is a distributed engine for batch, SQL and streaming data processing, used from Python through PySpark. Use when a user asks to process big data, run distributed computations, build ETL pipelines, analyse data at scale, read Parquet from S3, or stream from Kafka with PySpark.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.