review-vcpkg-prs-today

Revisar pull requests abertos e não rascunho do microsoft/vcpkg atualizados nos últimos 30 dias. Use quando solicitado para triagem em lote, relatórios de revisão por PR, um índice agrupado por…

npx skills add https://github.com/microsoft/vcpkg --skill review-vcpkg-prs-today

Inputs

InputRequiredMeaning
investigation-rootNoDirectory for workspaces and intermediate artifacts: sources, builds, installs, logs, and examples. If omitted, infer a short same-drive path when clear; otherwise ask. Never use the Copilot session directory or an arbitrary long temp path.
review-depthNoOne of no-examples, examples, or examples-and-patches. Default to no-examples.

Example invocations

  • /review-vcpkg-prs-today investigation-root D:/vcpkg-prs
  • /review-vcpkg-prs-today review-depth examples
  • /review-vcpkg-prs-today investigation-root D:/vcpkg-prs and review-depth examples

Procedure

  1. Before changing directories, resolve investigation-root, reviews/, and .github/skills/shared/review-vcpkg-pr-guide.md against the caller's original directory to absolute paths. Keep the resolved reviews directory as reviews-root; never rebase it onto a worker's workspace.
  2. Discover candidates using GitHub search (gh api or the Search API), not the generic pulls list: repo:microsoft/vcpkg is:pr is:open draft:false updated:>=<today minus 30 days>. Prefer authentication via gh or GITHUB_TOKEN to avoid low unauthenticated limits.
  3. Fetch each candidate's changed files; identify ports from ports/<portname>/.
  4. Prepare isolated workspaces as below. Review every candidate independently with a general-purpose worker using its default high-capability model; do not override it with a fast or lightweight model. Require it to read the entire guide and follow every instruction. Group competition only in the final index. Pass each worker:
    • PR number ({{PR_NUMBER}}).
    • Selected review-depth.
    • Absolute workspace and worker-local investigation-root.
    • Absolute {{REPORT_DIR}} (pr-{{PR_NUMBER}} under reviews-root).
    • Absolute guide path.
  5. Write each report when completed. Write index.md last from the final per-PR results and port-specific competition groups.

Parallel execution safety

  1. Give each concurrent worker its own writable detached worktree or equivalent detached-HEAD workspace and intermediate artifacts under investigation-root. Never share a writable repository path between workers.
  2. Create all isolated workspaces before launching workers. Copy the caller's vcpkg.exe (Windows) or vcpkg (non-Windows) into each workspace root.
  3. Use the caller's working tree only when exactly one worker is active and the user explicitly allows it.
  4. If VCPKG_DOWNLOADS is already nonempty, preserve it for all workers and review commands. Use that shared directory only through vcpkg; never clean or delete it. Otherwise, do not set it.

index.md content

index.md must include:

  1. Coverage summary, including how many PRs were reviewed, skipped, or failed.
  2. PRs grouped by the shared guide's verdicts: approve, approve-with-notes, request-changes, and unknown, with relative links to their reports.
  3. Competing PRs grouped only by the specific modified ports they share.
  4. PRs with no touched ports/<portname>/ entries.
  5. PRs that failed to review, with a short reason instead of silently omitting them.

Required output layout

Write only final deliverables under the fixed reviews-root, not under investigation-root:

  1. index.md at reviews-root.
  2. report.md in each worker's {{REPORT_DIR}}, including the guide's self-contained ## Fix handoff for use without this session's chat history.
  3. patches/*.patch in each worker's {{REPORT_DIR}} -- only for examples-and-patches; omit if no patches were produced and explain any unpatched issues in the report.

Do not stop until the index and every reviewed PR's report exist at these absolute destinations and are complete.

Mais skills de microsoft

oss-growth
microsoft
Persona de growth hacker OSS
agent-framework-azure-ai-py
microsoft
Crie agentes do Azure AI Foundry usando o SDK Python do Microsoft Agent Framework (agent-framework-azure-ai). Use ao criar agentes persistentes com AzureAIAgentsProvider, usando ferramentas hospedadas (interpretador de código, pesquisa de arquivos, pesquisa na web), integrando servidores MCP, gerenciando threads de conversa ou implementando respostas em streaming. Abrange ferramentas de função, saídas estruturadas e agentes com múltiplas ferramentas.
development
airunway-aks-setup
microsoft
Configure o AI Runway no AKS — do cluster vazio ao modelo em execução. Abrange verificação do cluster, instalação do controlador, avaliação de GPU, configuração do provedor e primeira implantação. QUANDO: "configurar AI Runway", "integrar cluster AKS", "instalar AI Runway", "configuração do airunway", "implantar modelo no AKS", "inferência GPU no AKS", "configuração KAITO no AKS", "executar LLM no AKS", "vLLM no AKS", "configurar serviço de modelo no AKS", "controlador AI Runway".
devops
appinsights-instrumentation
microsoft
Orientação para instrumentar aplicações web com Azure Application Insights. Fornece padrões de telemetria, configuração de SDK e referências de configuração. QUANDO: como instrumentar o app, SDK do App Insights, padrões de telemetria, o que é App Insights, orientação sobre Application Insights, exemplos de instrumentação, melhores práticas de APM.
devops
applicationinsights-web-ts
microsoft
Instrumente aplicativos de navegador/web com o SDK JavaScript do Application Insights (@microsoft/applicationinsights-web). Use para Real User Monitoring (RUM) — visualizações de página, cliques, dependências AJAX/fetch, exceções, eventos personalizados e rastreamentos de agentes GenAI no lado do navegador correlacionados a rastreamentos OpenTelemetry no backend. Abrange o Script de Carregamento do SDK e a configuração via npm, extensões de frameworks (React, React Native, Angular), Click Analytics, inicializadores de telemetria e convenções semânticas GenAI do OTel para spans de agente/ferramenta/modelo emitidos pelo navegador.
devops
azure-ai-anomalydetector-java
microsoft
Crie aplicativos de detecção de anomalias com o SDK do Azure AI Anomaly Detector para Java. Use ao implementar detecção de anomalias univariada/multivariada, análise de séries temporais ou monitoramento com IA.
development
azure-ai-language-conversations-py
microsoft
Implemente o reconhecimento de linguagem conversacional (CLU) usando o SDK Python azure-ai-language-conversations. Use ao trabalhar com ConversationAnalysisClient para analisar intenção e entidades de conversas, criar recursos de NLP ou integrar o reconhecimento de linguagem em aplicativos.
development
azure-ai-ml-py
microsoft
SDK v2 do Azure Machine Learning para Python. Use para workspaces de ML, jobs, modelos, conjuntos de dados, computação e pipelines. Gatilhos: "azure-ai-ml", "MLClient", "workspace", "registro de modelos", "jobs de treinamento", "conjuntos de dados".
development