このリポジトリの skills
SkillsMP は microsoft/GitHub-Copilot-for-Azure から 48 件の skill を収集しています。skill を開くとソースと詳細を確認できます。
microsoft/GitHub-Copilot-for-Azure収集済み skill 48 件中 8 件を表示しています。
Assess and upgrade Azure workloads between plans, tiers, or SKUs, or modernize Azure SDK dependencies in source code. WHEN: upgrade Consumption to Flex Consumption, upgrade Azure Functions plan, change hosting plan, function app SKU, migrate App Service to…
原文の言語: 英語
Provision Microsoft Entra Agent Identity Blueprints, BlueprintPrincipals, and per-instance Agent Identities via Microsoft Graph, and configure OAuth 2.0 token exchange (fmi_path, OBO, cross-tenant) including the Microsoft Entra SDK for AgentID sidecar. USE…
原文の言語: 英語
Guides Microsoft Entra ID app registration, OAuth 2.0 authentication, and MSAL integration. USE FOR: create app registration, register Azure AD app, configure OAuth, set up authentication, add API permissions, generate service principal, MSAL example, console…
原文の言語: 英語
Deploy Python (Flask/Django/FastAPI) code to Azure App Service Linux. WHEN: "Flask App Service", "Django App Service", "FastAPI App Service", "deploy Python to App Service". DO NOT USE FOR: Container Apps, Functions, non-Python, Terraform/Bicep/IaC, full…
原文の言語: 英語
Assess Kubernetes workloads and cluster configuration for AKS Automatic compatibility. Identifies incompatibilities, generates fixes, and guides migration from AKS Standard to AKS Automatic. WHEN: migrate to AKS Automatic, check AKS Automatic readiness,…
原文の言語: 英語
Query the integration-test storage account to find why a specific skill's tests are failing. Reads blob-stored test result files and surfaces error details. TRIGGERS: why is skill failing, skill test failures, debug skill tests, skill failing tests, analyze…
原文の言語: 英語
File a GitHub issue for local integration test failures. TRIGGERS: file test bug, report test failure, create bug for test, integration test failed, test failure issue, junit failure
原文の言語: 英語
Analyzes markdown files for token efficiency. TRIGGERS: optimize markdown, reduce tokens, token count, token bloat, too many tokens, make concise, shrink file, file too large, optimize for AI, token efficiency, verbose markdown, reduce file size
原文の言語: 英語