4천건 · 관련도순
Develop complex features or business documents by gathering approaches from available AI providers. Combine their perspectives with prior project decisions and quality checks to produce a proposed plan, then proceed with implementation after user confirmation.
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Delegate a self-contained coding task to Codex CLI from another agent using ChatGPT subscription authentication. Run independent implementation, request a second opinion, or verify changes, with separate working copies for parallel tasks.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Turn a feature or refactoring idea into a concise implementation prompt for another agent. It asks focused questions one at a time, records decisions, and includes development steps, validation, and working rules.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Prepare a separate workspace for feature development using platform tools or git worktree, which gives a branch its own working directory. It checks existing isolation, prepares dependencies, and runs tests before implementation begins.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Simplify code, tests, documentation, and configuration while preserving required behavior. Use it during implementation or before handoff to remove duplication, reuse existing mechanisms, and validate that each remaining part serves a clear purpose.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Audit a React codebase using React Doctor scan results and code inspection. It ranks issues by impact and effort, then writes detailed implementation plans that another agent can execute, while leaving source code unchanged during the audit.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Build and improve mobile apps with React Native and Expo using prioritized implementation rules. Covers faster lists, animations, images, navigation, state management, and native dependencies, with explanations and code examples for reviewing common implementation choices.
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Walk Chinese-speaking users through code or a pull request while checking correctness. Follow the actual execution flow, explain key implementation choices, and report concrete defects with trigger conditions, consequences, and precise file locations.
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Coordinate large code refactors or rewrites across multiple agents. It organizes parallel analysis, assigns clear file ownership, schedules work around dependencies, and checks individual changes and their integration against agreed requirements.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Fetch dependency source code to give AI agents deeper implementation context. Use when the agent needs to understand how a library works internally, read source code for a package, fetch implementation details for a dependency, or explore how an npm/PyPI/crates.io package is built. Triggers include "fetch source for", "read the source of", "how does X work internally", "get the implementation of", "opensrc path", or any task requiring access to dependency source code beyond types and docs.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Takes a new customer from signature to working — setting a definition of live that both sides agreed before the contract was signed, planning and staffing the implementation, running data migration and integration realistically, training the people who will actually use it, and handing over to the ongoing relationship. Use this to design an onboarding motion, rescue a stalled implementation, work out why customers who bought never went live, or scope the services a deal actually needs.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
AI DevKit · Analyze and simplify existing implementations to reduce complexity, improve maintainability, and enhance scalability. Use when users ask to simplify code, reduce complexity, refactor for readability, clean up implementations, improve maintainability, reduce technical debt, or make code easier to understand.
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Converts an arxiv paper into a minimal, citation-anchored Python implementation. Trigger when user runs /paper2code with an arxiv URL or paper ID, says "implement this paper", or pastes an arxiv link asking for implementation. Flags all ambiguities honestly. Never invents implementation details not stated in the paper.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Create if-then implementation intentions and WOOP plans for specific student behaviour change goals. Use when students know what to do but struggle to follow through on habits or routines.
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Assess and operationalize implementation readiness for high-risk AI systems under the EU AI Act Annex III, including provider and deployer obligations, conformity assessment, post-market monitoring, and EU database registration. Use when users say things like “we classified this as high-risk, what now?”, “build an EU AI Act readiness plan”, “assess our Annex III compliance gaps”, “what do providers/deployers of high-risk AI need to implement?”, “prepare for conformity assessment”, or “create a high-risk AI implementation roadmap.”
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Generate protocol/interface test suites that any implementation must pass. Define the contract once, test every implementation. Use when designing protocols or swapping implementations.
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Master orchestrator that generates all implementation specs (PRD, Architecture, UX, Implementation, Test, Release) from product plan. Use when generating complete specification package.
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Generates detailed implementation guide with pseudo-code and step-by-step development instructions. Creates IMPLEMENTATION_GUIDE.md from PRD, Architecture, and UX specs. Use when creating development roadmap.
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An implementation, which takes input data and makes it available for proper batch effect removal by ComBat or Limma. The implementation appropriately handles missing values by dissecting the input matrix into smaller matrices with sufficient data to feed the ComBat or limma algorithm. The adjusted data is returned to the user as a rebuild matrix. The implementation is meant to make as much data available as possible with minimal data loss.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Run the post-implementation quality assurance workflow including tests, code polishing, review, and commit. Use when the user asks to "finalize implementation", "finalize changes", "wrap up implementation", "finish up", "ready to commit", or "run QA workflow".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Produce an implementation plan at .turbo/plans/<slug>.md. Use when the user asks to "draft a plan", "draft the plan", "write an implementation plan", "plan this change", "create an implementation plan", or needs a first-draft plan file before refinement.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Interactive feature development workflow from idea to implementation. Creates requirements (EARS format), design documents, and implementation task lists. Use when creating feature specs, requirements documents, design documents, or implementation plans. Triggered by "kiro" or references to .kiro/specs/ directory.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Generate detailed implementation plans for complex tasks. Creates comprehensive strategic plans in Markdown format with objectives, step-by-step implementation tasks using checkbox format, verification criteria, risk assessments, and alternative approaches. All plans MUST be validated using the included validation script. Use when users need thorough analysis and structured planning before implementation, when breaking down complex features into actionable steps, or when they explicitly ask for a plan, roadmap, or strategy. Strictly planning-focused with no code modifications.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Generates phased, dependency-ordered implementation tasks from specifications. Use after spec is complete and before starting implementation.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.