'preferences' 검색 결과

Build a shared animation foundation for React and Next.js with motion/react. Define reusable timing and spring settings, respect reduced-motion preferences, adapt to device performance, and align initial animation states with server-rendered content.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Standardize animation settings across components
• Define reusable spring animation presets
• Respect users' reduced-motion preferences

gstack의 확인 질문을 돌아보고 대화로 질문별 확인 방침과 조정 기능의 사용 여부를 설정하며, 직접 밝힌 선호와 행동에서 파악한 경향을 각각 확인합니다.

• 이전에 받은 확인 질문을 살펴봅니다
• 질문별 확인 방침을 설정합니다
• 밝힌 선호와 행동 경향을 비교합니다

대화에서 얻은 사실, 일상 사건, 사용자 선호를 파일로 저장합니다. 프로젝트와 지속적인 책임 등으로 분류하고, 세션이 바뀌어도 검색하고 참조할 수 있습니다.

• 여러 대화에 걸쳐 사실 기억하기
• 일상 사건과 대화 기록하기
• 인물과 프로젝트 지식 정리하기

기존 화면이나 합의된 UI 안에 목적과 사용 빈도에 맞는 애니메이션을 구현합니다. 반복 조작으로 인한 중단과 동작 줄이기 설정도 처리합니다.

• 모달과 드로어의 열기·닫기 애니메이션
• 버튼과 토글 조작에 대한 피드백
• 반복 조작으로 중단되는 애니메이션 조정

GSAP 기본 API로 웹 요소와 SVG의 이동, 회전, 페이드 효과를 구현합니다. 속도 변화와 시간차를 조절하고 화면 너비와 동작 줄이기 설정에 대응합니다.

• 웹 페이지에 이동과 페이드 효과를 넣을 때
• 여러 요소를 시간차로 움직일 때
• 화면 너비에 따라 동작을 바꿀 때

Build AI agents that retain conversation history, user preferences, and useful interaction patterns with AgentDB. The skill covers persistent storage, meaning memories survive between sessions, plus retrieval, context management, and ReasoningBank integration.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Add conversation history to a chat system
• Remember user preferences across sessions
• Reuse patterns from successful interactions

Build AI agents that retain conversation history, user preferences, and useful interaction patterns with AgentDB. The skill covers persistent storage, meaning memories survive between sessions, plus retrieval, context management, and ReasoningBank integration.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Add conversation history to a chat system
• Remember user preferences across sessions
• Reuse patterns from successful interactions

Review fixed pixel values in fonts, widths, and spacing, then suggest relative units that adapt to available space and browser font preferences. Check rendered layouts at different screen widths and during interactions before proposing changes.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Adapting text to browser font size preferences
• Replacing fixed widths with flexible layouts
• Reviewing spacing units within components

Review website animations against users’ reduced motion preferences, a setting that requests less movement. Check flashing content, scrolling effects, alternative transitions, pause controls, and advance warnings, and identify changes needed in rendered pages and interactive states.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Checking support for reduced motion settings
• Reviewing flashing content frequency
• Finding alternatives to scrolling effects

Create and review GSAP code that animates webpage elements and SVG graphics. Covers movement, fades, easing that controls speed changes, staggered effects, playback controls, and adaptations for screen size and reduced-motion preferences.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Adding entrance animations to webpage elements
• Animating multiple items with staggered starts
• Adjusting motion for desktop and mobile screens

Inspect a codebase and create concise project instructions for Claude Code. Review existing guidance, separate team rules from personal preferences, and propose reusable skills or hooks that run commands automatically.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Set up project instructions for Claude Code
• Review and improve an existing CLAUDE.md
• Separate personal preferences from team rules

Use Hindsight to recall past context, save reusable facts, and reason across accumulated memories. Supports continuity between conversations by preserving preferences, project decisions, and lessons learned, while helping explain the reasoning behind earlier choices.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Resuming earlier work with relevant context
• Saving lasting preferences and project decisions
• Reviewing the reasons behind past decisions

Save facts, decisions, preferences, and task outcomes to Hindsight long-term memory. The skill turns what was learned into short notes with context and reasons, choosing either a Bot’s own memory store or a shared store.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Saving a completed task’s outcome and reasoning
• Remembering a user’s stated preferences
• Recording decisions for future work

Find context from past coding sessions in Hindsight long-term memory. Reuse memories already loaded for the session, search for missing details, and reason over accumulated records when answering questions about decisions, project context, or preferences.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Revisit the reasons behind past implementation decisions
• Recover project context discussed in earlier sessions
• Check previously discussed preferences

Search AI and machine learning jobs through AI Dev Jobs MCP, a connection agents use to access job data. Inspect employers and requirements, match roles to skills and preferences, and review available salary and market statistics.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Finding remote machine learning jobs
• Discovering companies hiring for AI roles
• Matching jobs to skills and work preferences

Design agent memory that preserves facts, preferences, and conversation history across sessions. Plan storage, retrieval, and retention separately for each organization or user, with checks for unauthorized access, outdated information, conflicting records, and retrieval quality.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Designing memory that remembers preferences across sessions
• Separating conversation history by organization and user
• Investigating retrieval of outdated or conflicting records

Give an agent rules for consulting long-term memory before work and saving decisions, corrections, and failures afterwards. It helps carry preferences and project conventions across sessions while preserving dated history and making conflicting memories visible.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Carry preferences and project conventions across sessions
• Record user corrections for future tasks
• Preserve the history of changed decisions

Build and review interfaces against WCAG 2.2 accessibility guidelines. Covers keyboard navigation, screen readers that read interface content aloud, accessible forms, mobile support, and display preferences, helping identify and fix barriers to using a website or app.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Audit an interface for accessibility issues
• Add keyboard navigation and focus management
• Improve screen reader support for forms

Choose a model training method and configuration from paired response preferences or individual positive and negative ratings. Covers DPO, ORPO, KTO, and SimPO, including pair construction, repeated training rounds, and troubleshooting learning settings.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choose a training method for paired response preferences
• Select a method for individual positive and negative ratings
• Review learning settings when DPO training loses general capability

Create a landing page from an interview about the product, audience, and brand preferences. Use Stitch to generate and refine designs, then package approved HTML with design documentation and a deployment checklist.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Create a product landing page without a visual direction
• Turn brand preferences into colors and typography
• Compare page designs and refine them through feedback

Retrieve earlier decisions, preferences, and saved resources from OpenViking across sessions. Store durable information, import documents or repositories, and manage deletion, with guidance on how project memory is shared between directories and repository clones.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Recall decisions from earlier sessions
• Save preferences and lasting decisions
• Import files, URLs, or Git repositories for later use

Generate an .editorconfig file tailored to a project's file types and formatting preferences. Set indentation, line endings, character encoding, and whitespace rules, with a clear explanation of each choice to support consistent formatting across editors.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Standardize formatting across team members' editors
• Set indentation rules for different file types
• Define line ending and whitespace settings

Guide language model training with TRL, from learning to follow instructions to matching human preferences. Covers method selection, training data, reward models that score responses, evaluation, and adjustments for memory limits or unstable training.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Train a model on instruction and response examples
• Align responses using preferred and rejected answer pairs
• Build a training pipeline using human feedback

Plan and configure large language model training with OpenRLHF to better match human preferences. Covers training method selection, distributed GPU setup, inference acceleration with vLLM, and troubleshooting memory or training stability issues.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choosing a method for training models on human preferences
• Setting up PPO training with a reward model
• Configuring GRPO training without a critic model