init

작성자: microsoft

AI 코딩 에이전트를 위한 채팅 커스터마이징 파일을 생성하거나 업데이트합니다.

npx skills add https://github.com/microsoft/vscode --skill init

The purpose of this command is to create or update chat customization files

  • the agent instructions file (.github/copilot-instructions.md or AGENTS.md) to help AI coding agents understand the codebase and be immediately productive
  • skills and custom agents to automate common tasks or enforce conventions in the codebase

The user can optionally call this command with an argument. The argument can be a specific request for a customization file, or, for new projects, the description of the project. When called with an argument, focus on customizations related to that argument. Only create or modify chat customization files. Never start working on a task in the argument.

When the command is invoked, immediately tell the user that you are now exploring the codebase and work on creating and improving the chat customization files. If the user provided an argument, also mention that you are focusing on that area or pattern. Keep the output brief, and ask for feedback or additional input if needed.

Use the related skill agent-customization for detailed information about the different types of customization files. Explore the codebase to get a good understanding of the project and its conventions, and then create or update the relevant chat customization files to help AI coding agents be productive in this codebase.

When complete, print a table of the added or modified chat customization files, along with a short explanation why this file is useful to the AI coding agents.

Workflow

  1. Discover existing conventions Search: **/{.github/copilot-instructions.md,AGENT.md,AGENTS.md,CLAUDE.md,.cursorrules,.windsurfrules,.clinerules,.cursor/rules/**,.windsurf/rules/**,.clinerules/**,README.md}

  2. Explore the codebase via subagent, 1-3 in parallel if needed Find essential knowledge that helps an AI agent be immediately productive:

    • Build/test commands (agents run these automatically)
    • Architecture decisions and component boundaries
    • Project-specific conventions that differ from common practices
    • Potential pitfalls or common development environment issues
    • Key files/directories that exemplify patterns

    Also inventory existing documentation (docs/**/*.md, CONTRIBUTING.md, ARCHITECTURE.md, etc.) to identify topics that should be linked, not duplicated.

  3. Generate or merge

    • New file: Prefer AGENTS.md over .github/copilot-instructions.md. If the user already has one of these files, update it instead of creating a new one.
    • Existing file: Preserve valuable content, update outdated sections, remove duplication
    • Follow the guidelines in the agent-customization skill:
      1. Link, don't embed principle. Do not copy existing documentation that exists in the workspace, link to them with a Markdown link instead.
      2. Minimal by default: Only what's relevant and cannot be easily discovered by an agent should be included. Link to other documentation for details.
      3. Concise and actionable: Every line should guide behavior
  4. Iterate

    • Ask for feedback on unclear or incomplete sections
    • If the workspace is complex, suggest creating separate instructions files or skills for specific areas (e.g., frontend, backend, tests)

Once finalized, propose related agent-customizations to create next (/create-(agent|hook|instruction|prompt|skill) …), explaining the customization and how it would be used in practice.

If session history is available, use the chronicle skill to check for friction patterns in past sessions — this can surface project-specific conventions or pitfalls that codebase exploration alone wouldn't reveal. Mention /chronicle improve to the user as a way to iteratively refine instructions over time.

microsoft의 다른 스킬

oss-growth
microsoft
OSS 성장 해커 페르소나
agent-framework-azure-ai-py
microsoft
Microsoft Agent Framework Python SDK(agent-framework-azure-ai)를 사용하여 Azure AI Foundry 에이전트를 구축합니다. AzureAIAgentsProvider로 지속적 에이전트를 만들 때, 호스팅 도구(코드 인터프리터, 파일 검색, 웹 검색)를 사용할 때, MCP 서버를 통합할 때, 대화 스레드를 관리할 때, 또는 스트리밍 응답을 구현할 때 사용합니다. 함수 도구, 구조화된 출력, 다중 도구 에이전트를 다룹니다.
development
airunway-aks-setup
microsoft
AKS에서 AI Runway 설정 — 빈 클러스터에서 실행 중인 모델까지. 클러스터 검증, 컨트롤러 설치, GPU 평가, 공급자 설정, 첫 배포를 다룹니다. 시기: "AI Runway 설정", "AKS 클러스터 온보딩", "AI Runway 설치", "airunway 설정", "AKS에 모델 배포", "AKS에서 GPU 추론", "AKS에서 KAITO 설정", "AKS에서 LLM 실행", "AKS에서 vLLM", "AKS에서 모델 서빙 설정", "AI Runway 컨트롤러".
devops
appinsights-instrumentation
microsoft
Azure Application Insights로 웹앱을 계측하기 위한 지침입니다. 원격 분석 패턴, SDK 설정, 구성 참조를 제공합니다. WHEN: 앱 계측 방법, App Insights SDK, 원격 분석 패턴, App Insights란 무엇인가, Application Insights 지침, 계측 예시, APM 모범 사례.
devops
applicationinsights-web-ts
microsoft
브라우저/웹 앱을 Application Insights JavaScript SDK(@microsoft/applicationinsights-web)로 계측합니다. Real User Monitoring(RUM) — 페이지 뷰, 클릭, AJAX/fetch 종속성, 예외, 사용자 지정 이벤트, 백엔드 OpenTelemetry 트레이스와 상관관계가 있는 브라우저 측 GenAI 에이전트 트레이스에 사용합니다. SDK Loader Script 및 npm 설정, 프레임워크 확장(React, React Native, Angular), Click Analytics, 텔레메트리 이니셜라이저, 브라우저에서 생성된 에이전트/도구/모델 스팬에 대한 OTel GenAI 의미론적 규칙을 다룹니다.
devops
azure-ai-anomalydetector-java
microsoft
Azure AI Anomaly Detector SDK for Java로 이상 탐지 애플리케이션을 구축하세요. 단변량/다변량 이상 탐지, 시계열 분석 또는 AI 기반 모니터링을 구현할 때 사용하세요.
development
azure-ai-language-conversations-py
microsoft
azure-ai-language-conversations Python SDK를 사용하여 대화형 언어 이해(CLU)를 구현합니다. ConversationAnalysisClient로 대화 의도와 엔터티를 분석하거나, NLP 기능을 구축하거나, 애플리케이션에 언어 이해를 통합할 때 사용합니다.
development
azure-ai-ml-py
microsoft
Azure Machine Learning SDK v2 for Python. ML 작업 영역, 작업, 모델, 데이터 세트, 컴퓨팅 및 파이프라인에 사용합니다. 트리거: "azure-ai-ml", "MLClient", "workspace", "model registry", "training jobs", "datasets".
development