'scaffold' 검색 결과

기존 TypeScript 프로젝트에 업무 규칙을 묶어 관리하는 애그리거트의 코드 틀을 만듭니다. 엔티티, 저장용 인터페이스, 이벤트와 테스트의 기초를 마련합니다.

• 기존 업무 영역에 애그리거트 추가
• 업무 규칙이 있는 개념 모델링
• 엔티티와 테스트 코드 틀 생성

저장소가 AI 에이전트 실행 프레임워크를 도입할 준비가 되었는지 다섯 지표로 평가합니다. 파일 변경 없이 예상 실행 비용과 기본 틀의 준비 상태도 확인합니다.

• 에이전트 실행 프레임워크 도입 전 평가합니다
• 다섯 지표로 준비 상태를 비교합니다
• 예상 실행 비용과 기본 틀을 확인합니다

Set up a new Remotion Element for development in the documentation’s Remotion Studio. It follows the design and contribution guides, creates the starting structure, and offers to launch Docs Studio for a preview.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Starting development of a new Remotion Element
• Preparing an Element with the official guides
• Previewing a scaffolded Element in Docs Studio

Create a new app that extends a running Twenty instance. Guide project naming and instance selection, then use the scaffolder to install dependencies, authenticate, initialize Git, and complete the initial sync and installation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Start a new Twenty app project
• Scaffold a CRM extension or integration
• Create an app connected to an existing Twenty instance

Create and update prompt-based agents in Azure AI Foundry from a local JSON manifest, a file listing agent definitions. The skill prepares synchronization scripts, pushes instructions to the service, and verifies registered agents.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Registering multiple agents from JSON definitions
• Synchronizing changes to agent instructions
• Preparing a manifest and synchronization script

Generate page and component folder structures with a command, keeping related files together by feature. Create tabbed page shells, starter tests, and README files, and register page routes within the supplied frontend structure.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Starting a page with a consistent folder structure
• Creating a page shell with multiple tabs
• Adding components within a feature

Check the Compound Engineering environment and repository settings, identify configuration issues, and report optional tools. Confirm where generated documents will be stored, make approved configuration fixes, or scaffold a Compound Pack with pack:<id>.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Checking the Compound Engineering environment
• Fixing outdated or invalid repository settings
• Confirming where generated documents are stored

Structure a student's legal case memo with IRAC: issue, rule, application, and conclusion. Identify research gaps and relevant facts while leaving the student's analysis and conclusions to them, with support adjusted to the supervisor's teaching mode.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Structuring a legal case analysis memo
• Listing gaps before starting legal research
• Organizing facts to address in the analysis

Answer a short series of questions about your workflow to choose a Claude Code agent, command, skill, hook, or rule, then generate a template with the structure and file location for that component.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choosing how to implement a Claude Code workflow
• Creating a template for a reusable team procedure
• Planning automatic checks or persistent behavior rules

Generate drug-like molecule candidates with GenMol NIM through NVIDIA's hosted API or local Docker deployment. Expand molecular scaffolds, modify existing candidates, rank results by drug-likeness or lipophilicity, and save the ranked molecules to a file.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Generate new molecule candidates from scratch
• Add structures around a molecular scaffold
• Modify fragments of a lead molecule

Scaffold production-ready AI agents on Google's Agent Development Kit (ADK): ReAct-style single agents, multi-agent orchestration (Sequential/Parallel/Loop), tool wiring, evaluation, and optional Vertex AI Agent Engine deployment. Use when building, scaffolding, or deploying ADK agents on Google Cloud, or when wiring ADK tools and orchestration patterns. Trigger with "build an ADK agent", "scaffold an agent on ADK", or "deploy to Agent Engine".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Scaffold a graded problem set with sections, problems, worked solutions, and short "why this matters" explainers across analytical, empirical, and coding types. Use when user says "make a problem set on X", "scaffold exercises for this lecture", "create practice problems", "generate homework with a solution key", "build a graded assignment on topic Y". Emits a clean student set plus a separate solution key — NOT for grading submissions or auto-checking student answers.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Designs and analyzes pooled prime-editor (PE) screens for installing precise genetic variants without bystander confounding. Covers pegRNA design with PRIDICT and PRIDICT2 for predicting per-pegRNA editing efficiency, pegRNA architecture (spacer + scaffold + PBS + RTT), PE2/PE3/PE3b/PEmax variants, MOSAIC in situ saturation mutagenesis, the PRIME pooled-screen methodology (Ren 2023; ~3,699 ClinVar variant screens), chromatin context as a major locus-level determinant of PE efficiency, scaffold-incorporation and indel byproduct quantification with CRISPResso2, and the cross-modal validation strategy of PE + base-editor screens for variant function. Use when designing a pegRNA library for variant installation, choosing between BE and PE for a specific edit, predicting pegRNA efficiency before library synthesis, analyzing PE screen output, distinguishing intended-edit from scaffold-incorporation, or scaling PE screens to thousands of variants.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Performs 3D shape-based similarity searching using ROCS (OpenEye), USRCAT (ultra-fast), Open3DAlign (RDKit), ESPSim (electrostatic), and ShaEP with explicit handling of Tanimoto-Combo (shape + color), shape vs ECFP4 complementarity, conformer-ensemble searching, alignment optimization, and scaffold hopping. Use when searching for shape-mimicking compounds with different scaffolds, identifying bioisosteric replacements, prospective scaffold hopping, or expanding hit series beyond 2D similarity.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Generate scaffolds supporting student self-regulation across planning, monitoring, and evaluation phases. Use when students struggle to manage their own learning during extended or independent tasks.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Track performance across sessions and reduce scaffolding as competence grows. Makes fading visible — the learner knows when scaffolds are removed and why. Use for sustained learning engagement where independence is the goal.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Generate argument structure scaffolds using Toulmin, PEEL, or CER frameworks for a specific claim or question. Use when teaching argumentative or analytical writing across any subject.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Create a writing scaffold teaching the genre conventions specific to an academic discipline. Use when students write lab reports, historical essays, or other discipline-specific text types.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Modify a classroom task with language scaffolds that preserve cognitive demand for EAL learners. Use when adapting existing tasks for students at different English proficiency levels.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Scaffold end-to-end testing infrastructure. Use when the user says "e2e scaffold" or "set up e2e testing"

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Seed a fresh (greenfield) repository with the PRD-Driven Context Engineering scaffold — PRD.md, SoT/ knowledge files, EPIC templates, domain-profile config, and agent MEMORY starters. Invoked as /prd-ce:init when the plugin is installed. The framework itself (skills, agents, hooks, scripts) ships LIVE in the plugin; this skill only plants the consumer-owned files the plugin cannot carry as behavior. Triggers on "/prd-ce:init", "set up PRD lifecycle here", "scaffold a new PRD-CE project", "initialize the methodology". Outputs a seeded scaffold + a verification report.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Scaffold-time observability so a shipped product is not blind in prod from day one — error capture (Sentry), request-id structured logging, and /healthz + /readyz endpoints. stack-baseline pins Sentry but nothing wires it; this is the wiring. Loaded by app-scaffolder (bake into the scaffold), infra-provisioner (prod env + probes), and consumed by l3-support (traces) and devops (deploy gate).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Generate scaffolds supporting student self-regulation across planning, monitoring, and evaluation phases. Use when students struggle to manage their own learning during extended or independent tasks.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Modify a classroom task with language scaffolds that preserve cognitive demand for EAL learners. Use when adapting existing tasks for students at different English proficiency levels.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.