'multi-step' 검색 결과

Find and evaluate a small, compatible set of AI Agent Skills for a multi-step goal. Check existing capabilities, compare candidates for fit and safety, identify overlaps, and prepare recommendations with installation subject to user approval.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choose a set of Skills for a multi-step project
• Audit installed Skills for overlap and conflicts
• Find supporting Skills for writing quality or compliance

Build Python workflows that constrain language model output using text patterns and grammar rules. Generate structured JSON, restrict classifications to allowed labels, extract information, and combine reusable generation steps with loops and tool selection.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Generate JSON with a defined structure
• Constrain date, email, and identifier formats
• Classify text using a fixed set of labels

Build Python workflows that constrain language model output using text patterns and grammar rules. Generate structured JSON, restrict classifications to allowed labels, extract information, and combine reusable generation steps with loops and tool selection.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Generate JSON with a defined structure
• Constrain date, email, and identifier formats
• Classify text using a fixed set of labels

Build AI agents by connecting workflow blocks in AutoGPT's visual editor. This skill covers multi-step automation, scheduled runs, webhooks that start work after external events, execution monitoring, and custom agent development.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build an AI workflow in a visual editor
• Start an agent when an external event occurs
• Run a multi-step workflow on a schedule

Keeps multi-step work organized with Markdown files for the plan, research notes, and final deliverable. Tracks completed phases, decisions, and errors so the agent can revisit goals and resume work with durable records.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Tracking progress through a multi-step task
• Keeping research findings and sources on disk
• Resuming work after a pause

Designing forms with multiple steps, progress indicators, conditional logic, and save-and-resume mechanics. The discipline of breaking complex data collection into stages that respect cognitive load while maintaining completion intent. Honest about kitchen-sink-single-page (overwhelms before the user starts), progress-theater (steps without genuine staging), and genuinely-staged (each step earns its own page) patterns. Triggers on multi-step form, multi-page form, form wizard, signup wizard, lead form, application form, intake form, configurator, onboarding form. Also triggers when a long form is converting poorly, when an audience is dropping off mid-form, or when a multi-step form is being scoped for the first time.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

OpenClaw의 browser 도구로 로그인 상태와 탭을 확인하며 여러 단계의 웹 작업을 진행합니다. 오래된 조작 대상 참조와 시간 초과 문제도 다룹니다.

• 여러 단계의 웹 작업을 진행합니다
• 조작 전에 로그인 상태를 확인합니다
• 탭을 재사용하고 중복 탭을 정리합니다

여러 단계의 계획을 읽고 바로 붙여 넣을 ECC 명령을 생성합니다. 단계 식별자와 완료 조건을 포함하며, 작업 범위를 전달할 수 없는 명령은 보류로 표시합니다.

• 구현 계획을 명령으로 변환
• 기능 추가·수정·리팩터링 명령 선택
• 지정한 단계의 명령만 준비

React와 Next.js에서 드래그, 스와이프, 텍스트와 SVG 애니메이션을 구현합니다. 여러 단계의 동작과 로딩 표시를 다루며 용도에 맞는 API 선택도 안내합니다.

• 드래그로 닫는 패널과 정렬 목록 구현하기
• 단어별 텍스트 표시와 숫자 애니메이션 만들기
• SVG 선 그리기와 원형 진행 표시 구현하기

Firecrawl의 `/interact`를 앱에 통합하여 클릭, 양식 입력, 페이지 이동이 필요한 웹 콘텐츠를 가져오는 기능 구현을 돕습니다.

• 클릭 후 나타나는 콘텐츠 가져오기
• 검색 양식과 필터 조작하기
• 여러 페이지에 나뉜 결과 가져오기

Coordinate work across apps connected through Aident Loadout, such as finding issues and sharing summaries. The skill checks available actions, account connections, and costs, then obtains required approval before changing external data.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Summarizing assigned Linear issues in Slack
• Checking costs before scraping web pages
• Finding available actions for connected apps

Structure Avalonia applications with ReactiveUI and Zafiro patterns for ViewModels, the objects that manage screen state and logic. Build multi-step wizards, organize navigation, report command progress, and connect screen layouts to their supporting logic.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Design ViewModels for screen state and logic
• Build multi-step setup wizards
• Organize navigation and discover UI sections

Build repeatable evaluations for AI agent responses, tool choices, and multi-step tasks. Use reference datasets and scoring criteria to compare changes, detect quality regressions, and set automated checks that must pass before deployment.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Compare agent quality before and after prompt changes
• Test tool selection and multi-step task execution
• Evaluate resistance to prompt injection

Guide multi-step coding tasks with deepseek-v4-pro or deepseek-v4-flash in thinking mode. Verify files and symbols, write plans with confirmed file paths and line numbers, and use a verifier agent before changes spanning three or more files.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Verify that files and functions exist before editing
• Write plans with confirmed file paths and line numbers
• Check assumptions before changes spanning three or more files

Split multi-step coding, research, or testing into focused assignments for sub-agents, which are agents handling specific parts of a task. The parent agent retains design decisions, integration, and final verification while independent work runs in parallel.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Exploring separate groups of files in parallel
• Assigning code changes with clear file ownership
• Running focused tests alongside other work

Build and operate AutoGPT agents that carry out multi-step workflows. Covers a visual editor for connecting processing blocks, scheduled and webhook triggers, deployment, execution monitoring, and benchmarks for evaluating agent performance.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build an AI workflow in a visual editor
• Run agents on a schedule or external event
• Add custom agent abilities with Forge

Design workflows in which AI agents handle multiple steps or specialist tasks. Choose a suitable structure, generate starter configurations, and define information handoffs, retries, validation checks, and limits on cost and context size.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choosing between one agent and a multi-agent workflow
• Generating a starter configuration for a multi-step pipeline
• Defining information handoffs and error recovery rules

Organize multi-step research and project work with Markdown files for plans, findings, and progress. Gemini hooks, automatic actions at session events, surface planning context so the agent can resume from saved records.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Resuming research after a break
• Tracking project phases and decisions
• Recording errors and test results

Organize multi-step research and project work in Continue using Markdown files for plans, findings, and progress. When invoked, the skill reads saved planning context to support resuming work and reviewing earlier decisions.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Resuming interrupted work in Continue
• Recording findings during research
• Tracking project phases and decisions

Keep plans, research findings, and progress in Markdown files for multi-step work in Kiro. Read saved project records when resuming a task to recover goals, decisions, and recent actions.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Organizing findings during extended research
• Tracking a refactor across multiple phases
• Resuming work after a long break

Turn requirements for software or other multi-step work into a structured plan with an approach, constraints, and verification steps. It also helps develop existing plans, researching decisions before handing the work over for execution.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Planning implementation from requirements
• Breaking complex work into manageable steps
• Adding detail to an existing plan

Coordinate temporary agents for code exploration, independent implementation tasks, verification, reviews, or complex debugging. Define self-contained assignments, run independent work in parallel, and check returned evidence before combining the results.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Delegating codebase exploration to inform a decision
• Running independent implementation tasks in parallel
• Getting an independent check of a high-risk change

Build AI agents on Cloudflare Workers with the Agents SDK. Implement persistent state, real-time chat, scheduled tasks, multi-step background workflows, and MCP servers, using current Cloudflare documentation to guide implementation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build agents that retain and synchronize state
• Create real-time chat with resumable streaming
• Implement scheduled tasks and multi-step workflows

Design forms that convert, validate well, resist spam, and integrate cleanly with downstream systems. Use this skill when designing or auditing any form (contact, signup, checkout, multi-step, embedded), planning validation logic, fighting spam, choosing form tooling, or improving form conversion. Triggers on form design, form validation, form conversion, multi-step form, form spam, captcha, honeypot, form abandonment, signup form, contact form. Also triggers when form completion rates are low or spam is overwhelming.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.