microsoft

Prepare azd-based Azure projects for deployment: generates azure.yaml, infrastructure (Bicep/Terraform), and Dockerfiles for the Azure Developer CLI (azd) workflow. USE ONLY when the user explicitly wants to use azd as the deployment tool, or the project already has an azure.yaml file. DO NOT USE FOR: non-azd deployments, Python App Service code-only deploys (use python-appservice-deploy), or cross-cloud migration (use azure-cloud-migrate). WHEN: prepare app for azd, create azure.yaml, set up azd infrastructure, modernize app for Azure with azd, deploy with azd, function app, timer trigger, service bus trigger, event-driven function, managed identity, generate Bicep, generate Terraform, create and deploy to Azure.

Deploy, evaluate, fine-tune, and manage Foundry agents end-to-end with azd: hosted agent scaffold/run/deploy, prompt agent create, batch eval, continuous eval, prompt optimizer, Agent Optimizer scaffold, agent.yaml, dataset curation from traces, model fine-tuning (SFT/DPO/RFT). USE FOR: azd ai agent, azd provision/deploy, deploy agent, hosted agent, create agent, add tool to agent, invoke agent, evaluate agent, continuous eval, continuous monitoring, optimize prompt, improve prompt, optimize agent instructions, agent optimizer, deploy model, Foundry project, RBAC, role assignment, permissions, quota, capacity, region, troubleshoot agent, deployment failure, AI Services, create Foundry resource, provision, knowledge index, customize deployment, onboard, availability, fine-tune, SFT, DPO, RFT, training-data, grader, distillation, fine-tuned model, large file upload. DO NOT USE FOR: Azure Functions, App Service, general Azure deploy (use azure-deploy), general Azure prep (use azure-prepare).

Unified Azure OpenAI model deployment skill with intelligent intent-based routing. Handles quick preset deployments, fully customized deployments (version/SKU/capacity/RAI policy), and capacity discovery across regions and projects. USE FOR: deploy model, deploy gpt, create deployment, model deployment, deploy openai model, set up model, provision model, find capacity, check model availability, where can I deploy, best region for model, capacity analysis. DO NOT USE FOR: listing existing deployments (use foundry_models_deployments_list MCP tool), deleting deployments, agent creation (use agent/create), project creation (use project/create).

Builds, tests, and deploys Microsoft 365 apps and agents for Teams and Copilot. Includes sub-skills for project creation, local testing, cloud deployment, troubleshooting, and Slack-to-Teams migration. USE FOR: Teams agent, bot, tab, message extension, Declarative Agents, Custom Engine Agents, local testing, Agents Playground, Azure resource provision, remote deployment, Slack to Teams migration, cross-platform bot development, Block Kit to Adaptive Cards conversion. DO NOT USE FOR: general web development, non-bot/non-Teams projects.

Guide for creating effective skills for AI coding agents working with Azure SDKs and Microsoft Foundry services. Use when creating new skills or updating existing skills.

Azure Cosmos DB library for Rust (NoSQL API). Document CRUD, containers, and globally distributed data. Triggers: "cosmos db rust", "CosmosClient rust", "document crud rust", "NoSQL rust", "partition key rust".

Azure Blob Storage library for Rust. Upload, download, and manage blobs and containers. Triggers: "blob storage rust", "BlobClient rust", "upload blob rust", "download blob rust", "storage container rust", "BlobServiceClient rust".

Azure Event Hubs library for Rust. Send and receive events for streaming data ingestion and batch processing. Triggers: "event hubs rust", "ProducerClient rust", "ConsumerClient rust", "send event rust", "streaming rust", "eventhub rust".

Migrate Python apps from Azure OpenAI Chat Completions to the Responses API. Covers AzureOpenAI/AsyncAzureOpenAI client migration to the v1 endpoint, streaming, tools, structured output, multi-turn, EntraID auth, and model compatibility checks. Python-focused, Azure OpenAI-specific. USE FOR: migrate to responses API, switch from chat completions, openai responses, upgrade openai SDK, responses API migration, move from completions to responses, gpt-5 migration, azure openai python migration, chat completions to responses, AzureOpenAI to OpenAI client, python azure openai upgrade. DO NOT USE FOR: building new apps from scratch (start with responses directly), Node/TypeScript/C#/Java/Go migrations (this skill is Python-only), Azure infrastructure setup (use azure-prepare), deploying models (use microsoft-foundry).

ユーザーが実験、探索、またはチュートリアル用の Jupyter Notebook（`.ipynb`）を作成、スキャフォールド、または編集するよう依頼したときに使用します。バンドルされたテンプレートを優先し、ヘルパースクリプト `new_notebook.py` を実行してクリーンな開始ノートブックを生成してください。

사용자가 실험, 탐색 또는 튜토리얼을 위한 Jupyter 노트북(`.ipynb`)을 생성, 스캐폴딩하거나 편집해 달라고 요청할 때 사용합니다; 번들로 제공되는 템플릿을 우선 사용하고 깨끗한 시작 노트북을 생성하기 위해 헬퍼 스크립트 `new_notebook.py`를 실행하는 것을 권장합니다.

ប្រើនៅពេលដែលអ្នកប្រើស្នើឲ្យបង្កើត រៀបចំ (scaffold) ឬកែសម្រួល Jupyter notebooks (`.ipynb`) សម្រាប់សាកល្បង ស្វែងរក ឬមេរៀន; អនុសាសន៍ឲ្យប្រើទំរង់គំរូដែលភ្ជាប់មកជាមួយ និងរត់ស្គ្រីបជំនួយ `new_notebook.py` ដើម្បីបង្កើតសៀវភៅចាប់ផ្តើមដែលស្អាត។

ស្វែងរកឯកសារផ្លូវការរបស់ Microsoft ដើម្បីរកមើល គំនិត មេរៀន និងឧទាហរណ៍កូដ នៅលើ Azure, .NET, Agent Framework, Aspire, VS Code, GitHub និងផ្សេងទៀត។ ប្រើ Microsoft Learn MCP ជាលំនាំដើម ហើយប្រើ Context7 និង Aspire MCP សម្រាប់មាតិកាដែលស្ថិតនៅខាងក្រៅ learn.microsoft.com។

ಬಳಕೆದಾರರು ಪ್ರಯೋಗಗಳು, ಅನ್ವೇಷಣೆಗಳು ಅಥವಾ ಟ್ಯುಟೋರಿಯಲ್‌ಗಳಿಗಾಗಿ Jupyter ನೋಟ್ಬುಕ್‌ಗಳು (`.ipynb`) ರಚಿಸಲು, ಮೂಲ ರಚನೆ ಸಿದ್ಧಪಡಿಸಲು ಅಥವಾ ಸಂಪಾದಿಸಲು ಕೇಳಿದಾಗ ಬಳಸಿರಿ; ಸಂಯೋಜಿತ ಟೆಂಪ್ಲೇಟ್‌ಗಳಿಗೆ ಪ್ರಾಧಾನ್ಯ ನೀಡಿ ಮತ್ತು ಪ್ರಾರಂಭಿಕ ಸ್ವಚ್ಛ ನೋಟ್ಬುಕ್ ರಚಿಸಲು ಸಹಾಯಕ ಸ್ಕ್ರಿಪ್ಟ್ `new_notebook.py` ಅನ್ನು ರನ್ ಮಾಡಿ.

ಅಧಿಕೃತ Microsoft ಡಾಕ್ಯುಮೆಂಟೇಶನ್ ಅನ್ನು ಪ್ರಶ್ನೆ ಮಾಡಿ Azure, .NET, Agent Framework, Aspire, VS Code, GitHub ಮತ್ತು ಇತರೆ ಸಂಬಂಧಿತ ವಿಷಯಗಳ ಮೇಲೆ ತತ್ವಗಳು, ಟ್ಯುಟೋರಿಯಲ್ಗಳು ಮತ್ತು ಕೋಡ್ ಉದಾಹರಣೆಗಳನ್ನು ಕಂಡುಹಿಡಿಯಿರಿ. ಡೀಫಾಲ್ಟ್‌ವಾಗಿ Microsoft Learn MCP ಅನ್ನು ಬಳಸುತ್ತದೆ; learn.microsoft.com ಹೊರಗಿನ ವಿಷಯಗಳಿಗೆ Context7 ಮತ್ತು Aspire MCP ಅನ್ನು ಬಳಸಲಾಗುತ್ತದೆ.

ഉപയോക്താവ് പരീക്ഷണങ്ങൾ, അന്വേഷണങ്ങൾ, അല്ലെങ്കിൽ ട്യൂട്ടോറിയലുകൾക്കുള്ള Jupyter നോട്ട്ബുക്കുകൾ (`.ipynb`) സൃഷ്ടിക്കാൻ, സ്‌കാഫോൾഡ് ചെയ്യാൻ, അല്ലെങ്കിൽ തിരുത്താൻ ആവശ്യപ്പെടുമ്പോൾ ഉപയോഗിക്കുക; ബണ്ടിൽ ചെയ്ത ടെംപ്ലേറ്റുകൾ പ്രാഥമ്യം നൽകുക, കൂടാതെ ശുദ്ധമായ ആരംഭ നോട്ട്ബുക്ക് സൃഷ്ടിക്കാൻ സഹായി സ്ക്രിപ്റ്റ് `new_notebook.py` ഓടിക്കുക.

Upgrade existing Aspire projects to a newer Aspire version. Also handles TFM upgrades — preferred when the solution contains Aspire projects, since the Aspire version drives the required TFM. Triggers for "upgrade Aspire", "update Aspire version", "move to latest Aspire", or any .NET upgrade request on a solution with Aspire artifacts.

Upgrade .NET Framework projects to .NET Framework 4.8.1 (net481), staying on full .NET Framework without migrating to modern .NET (net8.0+). Use when user explicitly asks to upgrade to .NET Framework 4.8.1, upgrade to the latest .NET Framework version, or stay on full/Windows .NET Framework. Preserves legacy vs SDK-style project format unless the user explicitly requests SDK-style conversion.

Upgrade .NET projects to newer .NET versions, including guidance on current release status, support lifecycle (LTS/STS), and recommended upgrade targets.

Upgrade one or more NuGet packages from their current version to a target version across a project, several projects, a folder, a solution, or the whole repository. Use when the user wants to bump, update, or upgrade a specific NuGet package (or packages) to a given version or to the latest supported version, detect breaking API changes introduced by the new version, and fix the resulting code. User-initiated — match the user's stated package(s) and version intent.

Converts Visual Studio extension (VSIX/VSSDK) projects from legacy project format to SDK-style. Handles VSSDK-specific concerns including package references, VSIX manifest, VSCT command tables, project capabilities, and solution deploy markers for F5 debugging. Use when asked to "convert VSIX to SDK style", "modernize VS extension project", "migrate VSSDK project", "SDK-style VSIX", or "update extension csproj format".

How to create plans, scenario-instructions, and progress documents

Estimate and present the token-usage budget for an upgrade before execution. Run this when the user directly requests an estimate, or to present a budget that the assessment tool already appended to its output. Never auto-run it after assessment — that path is now handled programmatically by the assessment tool.

Structures WinForms applications with Designer-compatible patterns, proper code organization, and build/runtime compatibility. Use when creating or maintaining WinForms projects, working with Form or UserControl classes, organizing InitializeComponent vs application logic, implementing Application.Run patterns, handling Program.cs and ApplicationConfiguration, managing Application.SetHighDpiMode, working with .resx resource files, or troubleshooting Designer serialization issues. Also triggers for "WinForms project structure", "Form class organization", "Designer compatibility", "Application.Run", "Program.cs setup", and "WinForms best practices". Enhancement features (dark mode, async APIs, MVVM) are in separate skills for opt-in adoption only.

Browse Power Automate environments and flows interactively. Use when the user wants to browse, list, or explore their flows and environments.

Autonomously build a complete Power Automate flow from a description. Use when you need to generate a full flow definition and create it.

Guided flow creation wizard. Use when the user wants to create a new flow interactively.

Debug a failed Power Automate flow run. Use when a flow failed, has errors, or the user wants to troubleshoot a run.

Deep autonomous diagnosis of a failed flow run. Provide environment, flow, and run IDs. Use when the user asks to diagnose or deeply investigate a specific failed flow run.

Manage and run Power Automate Desktop (RPA) flows and machine groups. Use when the user asks about desktop flows, RPA, or machine groups.

Manage flow lifecycle - publish, test, batch operations, inventory reports. Use when the user asks to publish, test, batch manage, or get an inventory of flows.

Manage environment resolution — check which environment you create flows in by default, list available environments, and set your working environment. Use when the user asks about environments, their default environment, where to create flows, or switching environments.

Agents window architecture — covers the agents-first app, layering, folder structure, chat widget, menus, contributions, entry points, and development guidelines. Use when implementing features or fixing issues in the Agents window.

The VS Code design philosophy — a shared Values→Principles→Moves vocabulary for reasoning about UI in design terms instead of raw pixels. Use when designing, building, reviewing, or giving feedback on any visual surface; when deciding a radius, spacing, type role, icon size, border, color, or motion; or when translating a "this feels off" observation into a concrete, principled fix.

Analyze Agent Host debug log exports. Use when given an ah-logs or ahp-logs zip/folder, an Export Agent Host Debug Logs bundle, events.jsonl, AHP JSONL transport logs, Agent Host.log, remote-agenthost.log, or copilot-logs.

Find and read timestamped process logs from Code OSS dev builds, including main.log, renderer.log, extension host logs, and agenthost.log. For bundles produced by Export Agent Host Debug Logs, use agent-host-logs.

Symbolicate a native VS Code crash dump (.dmp) using electron-minidump. Use when given a crash dump file, asked to symbolicate a crash, resolve missing method names in a native crash backtrace, or attach Electron/Insiders/Stable symbol files. VS Code team members only; requires macOS or Linux.

Use when writing, recording, updating, or troubleshooting the agent host end-to-end tests under src/vs/platform/agentHost/test/node/protocol (black-box tests that drive the whole agent host over the AHP protocol, using a CapiReplayProxy record/replay system for Claude/Copilot/Codex). Covers adding a cross-provider test, re-recording fixtures after an SDK bump, gating non-deterministic or platform-specific tests, and diagnosing replay cache misses.

VS Code CSS conventions, file organization, class naming, standard sizes, SplitView/Grid layout, scrollable content, responsive layout, and text overflow/ellipsis patterns. Use when writing CSS, building layouts, or fixing text truncation issues.

VS Code theming, color tokens, widget styles, focus indicators, and high-contrast theme support. Use when registering colors, styling widgets with theme tokens, or ensuring HC/focus compliance.

Author, review, or validate Copilot prompt-engineering artifacts through independent review, behavior testing, and host checks.

Test HVE artifact behavior with black-box scenarios, contained simulation or approved native execution, independent grading, and evidence reports.

Compatibility alias for read-only prompt artifact review. Routes static and behavior analysis to hve-builder review mode.

Compatibility alias for legacy prompt-building requests. Routes creation and improvement to the hve-builder skill.

Compatibility alias for behavior-preserving prompt artifact cleanup. Routes refactoring to hve-builder refactor mode.

Authors Vally conformance tests for prompts, instructions, agents, and skills, including refusals for jailbreak, prompt-injection, harmful-elicitation, TOS, CoC, and PII-extraction stimuli

Research-only RPI playbook that gathers task evidence, writes dated research artifacts under .copilot-tracking/research/, and hands off planning-ready findings. Use when the user needs evidence, alternatives, or task framing first.

Guided, conversational walkthrough that explains code, UI, UX, features, or .copilot-tracking artifacts one line or block at a time with navigable evidence links, deep subagent review, and captured change requests for RPI handoff. Use when the user wants to understand how something works or why it was changed.

Create alerts, notifications, and automated actions on Fabric data and events via Fabric REST API and `az rest` CLI. **Invoke this skill** whenever the user wants to: (1) create, update, or delete an alert or notification flow, (2) send a Teams message, email, or run a Fabric item when something happens, (3) connect alert logic to Eventhouse, Eventstream, Real-time Hub, or DTB / Ontology data, (4) adjust thresholds, filters, event triggers, or actions, (5) troubleshoot or change an existing Activator/Reflex definition. Invoke this skill **before** asking clarifying questions — clarification is part of this skill, not a preamble to it. Triggers: "create an alert", "create an activator", "create a reflex", "create an activator item", "create an alert item", "notify me when", "let me know when", "take action when", "send me an email when", "send a teams message when", "run a pipeline when", "update an alert", "delete an alert", "activator rule"

Create, update, delete, and refresh Fabric Dataflows Gen2 via write-side CLI against Fabric Items and Connections APIs. Builds mashup.pq + queryMetadata definitions, triggers parameterized refreshes, manages connections, and configures output destinations (Lakehouse, Warehouse, ADX, Azure SQL). Includes preview-driven authoring loop (executeQuery + customMashupDocument). Lists `supportedConnectionTypes`/`credentialType` per connector. For executing saved queries or reading refresh status, use `dataflows-consumption-cli`. Triggers: "create dataflow", "update dataflow", "delete dataflow", "trigger dataflow refresh", "refresh dataflow", "preview Power Query M", "preview mashup", "preview before save", "iterate dataflow M", "create Fabric data source connection", "create dataflow connection", "bind connection", "list supportedConnectionTypes", "dataflow output destination", "dataflow write to lakehouse", "dataflow write to warehouse", "dataflow write to ADX", "DataDestinations annotation".

Create and manage SQL database in Fabric items, author T-SQL DDL/DML with constraints, foreign keys, triggers, indexes, and vector columns. Deploy schema via SqlPackage (.dacpac/.bacpac), configure source control, CI/CD, and GraphQL APIs. Triggers: "sql database in Fabric create table sqlcmd ddl", "sql database in Fabric primary key default getdate sqlcmd", "create sqldb item", "create table sqldb ddl", "sqldb foreign key constraint", "sqldb stored procedure", "sqldb trigger create", "sqldb vector column", "SqlPackage dacpac deploy sqldb", "bacpac sqldb", "sqldb source control", "graphql api sqldb", "sqldb collation set", "sp_invoke_external_rest_endpoint".

Answer natural-language business questions over existing Power BI reports and dashboards through the FabricIQ MCP endpoint. Orchestrates artifact discovery, schema inspection, entity resolution, DAX generation, and query execution to return plain-language answers. Use when the user asks what, which, compare, rank, explain, or summarize questions about Power BI report or dashboard content (not raw DAX). For raw DAX execution (EVALUATE statements) or model metadata inspection (INFO functions), use `semantic-model-consumption`. For upload/download/publish/list/delete report items or PBIR definitions, use `powerbi-report-management`. For PBIR file/page/visual edits, use `powerbi-report-authoring`. Triggers: "ask power bi", "PBI question", "discover my Power BI report", "report data", "dashboard data", "what are the top", "show me the power bi data", "which products sold", "compare sales in report", "which customers churned", "ask the Power BI report".

Query SQL database in Fabric via sqlcmd: interactive exploration, vector similarity, JSON, temporal queries, and security policy inspection on the OLTP and SQL analytics endpoints. For schema changes see the sqldb-authoring-cli skill. Triggers: "sql database in Fabric query sys.tables sqlcmd", "sql database in Fabric system view list user tables sqlcmd", "list user tables sqldb", "sys.tables sqldb", "explore sqldb schema", "vector similarity sqldb", "RAG embedding sqldb", "row level security sqldb inspect", "audit log sqldb inspect", "chat with sqldb", "export sqldb rows", "temporal as of sqldb", "json openrowset sqldb".

Diagnose SQL database in Fabric performance via sqlcmd against Query Store, DMVs, sys.dm_db_resource_stats, and Extended Events on the OLTP endpoint. Identifies the top resource-consuming, slowest, or most expensive queries and handles query-performance ranking, blocking-chain, missing-index, and plan-regression diagnostics. For routine data queries use the sqldb-consumption-cli skill; for schema changes use the sqldb-authoring-cli skill. Triggers: "query store slow query analysis sqldb top queries", "top resource-consuming queries from query store sqldb", "slowest queries sql database in Fabric query store", "most expensive queries sqldb query store", "sql database in Fabric blocked sessions head blocker chain sqlcmd", "sqldb missing index recommendation", "sqldb regressed plan instability sqlcmd", "sqldb extended events trace".

Create and modify Power BI report files in PBIR/PBIP format using the `powerbi-report-author` and `powerbi-desktop` CLIs. Use when the user wants to: (1) implement an approved report spec or design brief, (2) add or edit pages, visuals, filters, slicers, bookmarks, themes, or formatting, (3) validate PBIR and verify rendering in Power BI Desktop. For open-ended visual design, use `powerbi-report-design` first. For end-to-end requirements and approval workflow, use `powerbi-report-planning` first. Triggers: "edit PBIR", "create Power BI report page", "add visual to PBIP", "format report visual", "validate Power BI report", "reload Desktop screenshot", "implement an approved PBIP report spec", "edit PBIR pages/visuals".

Generate Power BI report visual design guidance before PBIR files are written. Use when the user wants to: (1) choose tone, signature, page archetypes, chart types, layout, color, typography, theme direction, or accessibility approach, (2) redesign/restyle an existing report, apply a brand, or critique chart/layout choices, (3) produce a design contract for `powerbi-report-authoring`. For end-to-end requirements, approval, and build sequencing, use `powerbi-report-planning`. Triggers: "design Power BI report", "make dashboard look professional", "choose chart type", "apply brand to report", "redesign report", "create design brief", "Power BI report design archetype".

Activate when the user asks about APM (Agent Package Manager): installing, configuring, authoring, or troubleshooting AI-agent packages, dependencies, compilation, MCP servers, policy, or any `apm` CLI command.

Use this skill to run a multi-persona expert advisory review on a labelled pull request in microsoft/apm. The panel fans out to five mandatory specialists plus a test-coverage specialist (active on every PR that touches src/) plus three conditional specialists (auth, doc-writer, performance-expert), all running in their own agent threads, and a CEO synthesizer. The orchestrator is the sole writer to the PR: ONE recommendation comment, no verdict labels, no merge gating. The panel is advisory -- it surfaces findings, prioritizes follow-ups, and renders a ship-recommendation that the maintainer and author weigh. Activate when a non-trivial PR needs a cross-cutting recommendation (architecture, CLI logging, DevX UX, supply-chain security, growth/positioning, optionally auth, docs, perf, and test coverage, with CEO arbitration).

Activate when creating new modules, refactoring class hierarchies, introducing design patterns, or making changes spanning 3+ files in the APM CLI codebase.

Activate when creating new modules, refactoring class hierarchies, introducing design patterns, or making changes spanning 3+ files in the APM CLI codebase.

Use this skill to run a four-panel adversarial advisory review on any pull request that touches the OpenAPM specification artifact (docs/src/content/docs/specs/openapm-*.md), its inline / sidecar JSON Schemas (docs/src/content/docs/specs/schemas/*.schema.json), or the conformance fixture seed (tests/fixtures/spec-conformance/**). The panel fans out to four spec-ecosystem reviewers (swagger-openapi-editor, oci-distribution-editor, pkgmgr-registry-contract-editor, w3c-tag-architect), each running in its own agent thread, and a spec-editor synthesizer that produces a fold-now / defer-v0.1.1 / defer-v0.2 / reject list plus a ship decision keyed off a 1..10 shocked_meter scale. The orchestrator is the sole writer to the PR: ONE consolidated comment, no verdict labels, no merge gating. The panel is advisory -- it surfaces findings, prioritizes folds, and renders a ship recommendation that the maintainer weighs.

Activate for changes to project positioning, release communication, community-facing artifacts, or breaking-change decisions in microsoft/apm. Triggers on README, MANIFESTO, PRD, CHANGELOG, release workflows, and issue templates.

Activate when code touches token management, credential resolution, git auth flows, GITHUB_APM_PAT, ADO_APM_PAT, AuthResolver, HostInfo, AuthContext, or any remote host authentication -- even if 'auth' isn't mentioned explicitly.

Use this skill when editing or creating CLI output, logging, warnings, error messages, progress indicators, or diagnostic summaries in the APM codebase. Activate whenever code touches console helpers (_rich_success, _rich_warning, _rich_error, _rich_info, _rich_echo), DiagnosticCollector, STATUS_SYMBOLS, CommandLogger, or any user-facing terminal output — even if the user doesn't mention "logging" or "UX" explicitly.

Azure VM/VMSS router. WHEN: create / provision / deploy / spin-up VM, recommend VM size, compare VM pricing, VMSS, scale set, autoscale, burstable, lightweight server, website, backend, GPU, machine learning, HPC simulation, dev/test, workload, family, load balancer, Flexible orchestration, Uniform orchestration, cost estimate, can't connect / RDP / SSH, refused, black screen, reset password, reach VM, port 3389, NSG, security, Linux, troubleshoot, troubleshooting, connectivity, capacity reservation (CRG), reserve, guarantee capacity, pre-provision, CRG association, CRG disassociation, machine enrollment (EMM), Essential Machine Management, monitor. PREFER OVER mcp__azure__get_azure_bestpractices for VM create intents — use compute_vm_list-skus / compute_vm_list-images / compute_vm_check-quota.

Iteratively improve skill frontmatter to achieve good routing test coverage. WHEN: run sensei, sensei help, improve skill routing

Prepare azd-based Azure projects for deployment: generates azure.yaml, infrastructure (Bicep/Terraform), and Dockerfiles for the Azure Developer CLI (azd) workflow. USE ONLY when the user explicitly wants to use azd as the deployment tool, or the project already has an azure.yaml file. DO NOT USE FOR: non-azd deployments, Python App Service code-only deploys (use python-appservice-deploy), or cross-cloud migration (use azure-cloud-migrate). WHEN: prepare app for azd, create azure.yaml, set up azd infrastructure, modernize app for Azure with azd, deploy with azd, function app, timer trigger, service bus trigger, event-driven function, managed identity, generate Bicep, generate Terraform, create and deploy to Azure.

Deploy, evaluate, fine-tune, and manage Foundry agents end-to-end with azd: hosted agent scaffold/run/deploy, prompt agent create, batch eval, continuous eval, prompt optimizer, Agent Optimizer scaffold, agent.yaml, dataset curation from traces, model fine-tuning (SFT/DPO/RFT). USE FOR: azd ai agent, azd provision/deploy, deploy agent, hosted agent, create agent, add tool to agent, invoke agent, evaluate agent, continuous eval, continuous monitoring, optimize prompt, improve prompt, optimize agent instructions, agent optimizer, deploy model, Foundry project, RBAC, role assignment, permissions, quota, capacity, region, troubleshoot agent, deployment failure, AI Services, create Foundry resource, provision, knowledge index, customize deployment, onboard, availability, fine-tune, SFT, DPO, RFT, training-data, grader, distillation, fine-tuned model, large file upload. DO NOT USE FOR: Azure Functions, App Service, general Azure deploy (use azure-deploy), general Azure prep (use azure-prepare).

Guidelines for writing Agent Skills that comply with the agentskills.io specification. WHEN: "create a skill", "new skill", "write a skill", "skill template", "skill structure", "review skill", "skill PR", "skill compliance", "SKILL.md format", "skill frontmatter", "skill best practices".

Author, validate, and run Vally eval.yaml evaluation suites for agent skills. TRIGGERS: create eval, write eval, add eval, run eval, validate eval, vally eval, eval.yaml, add stimulus, map test to eval, migrate test to eval, eval graders, eval scoring, add eval to CI.

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 infra — use azure-prepare.

Azure cost management: query costs, forecast spending, optimize to reduce waste. WHEN: "Azure costs", "Azure bill", "cost breakdown", "how much am I spending", "forecast spending", "optimize costs", "reduce spending", "orphaned resources", "rightsize VMs", "cost spike", "reduce storage costs", "AKS cost". DO NOT USE FOR: deploying resources, provisioning, diagnostics, or security audits.

Convene the persona panel on the CURRENT conversation / work-in-progress — the plan, design, or decision you've been building in this session. The INLINE counterpart to /council (which forks and runs isolated, so it cannot see the chat). Use when you want the council to critique what we're working on right now.

Convene the persona panel (six orthogonal review lenses) on a target — cold independent fan-out, debate-to-consensus, synthesized verdict with recorded dissent and a roster manifest.

Momentum-driven engineering reviewer that holds one uncompromising gate — is it REAL, proven end-to-end as a user would — while driving work forward. Demands proof over claims, plumbing before polish, fail-loud over fallbacks, trust in the model over instructions, and protects the critical path so good-but-costly ideas don't stall the work. Warm, blunt, forward-driving — not a curmudgeon. A lens for any checkpoint — brainstorm, design, plan, implement, debug, or ship — not just the finish. Use when: pressure-testing whether an idea/design/plan is provable and on the critical path, whether you're building in the right order, whether a fix is real or a band-aid, or whether work is actually done/ready — any time the worry is "are we fooling ourselves about what's real?"

Use when building an Amplifier-powered workflow or automation tool and deciding how to expose it — as standalone .dot attractor pipelines (incl. inside the Resolve dot-graph resolver), an importable Python lib, agent-callable tool modules, or a CLI. Covers the four leverage levels, the DRY rule that keeps logic in ONE home, the judgment for which levels a real consumer actually needs (and when adding a level is just ceremony), and the maximally-DRY attractor-only specialization where the .dot pipeline is the sole logic home.

Hard-won patterns for probing, building, troubleshooting, and iterating against Microsoft Graph API endpoints -- especially from a browser SPA using delegated MSAL.js auth calling Graph directly with no backend (lessons generalize to any Graph integration). Covers the throwaway-probe-file methodology for de-risking before building, OData/query quirks, permission and admin-consent sequencing, recordings/transcripts access patterns (SharePoint REST, not Graph), CSP requirements for a pure-browser SPA, retry/pagination/backoff patterns, and the MSAL/EasyAuth auth-redirect-loop debugging saga. Use when integrating with Microsoft Graph, Teams APIs, MSAL.js, or EasyAuth; when hitting an unexpected Graph error (400/403/429), a silent missing-scope failure, an auth redirect loop, or a CSP violation that only appears in production; or when deciding how to validate a new Graph capability before committing it to a codebase.

Analyze images using LLM vision APIs (Anthropic Claude, OpenAI GPT-4, Google Gemini, Azure OpenAI). Use when tasks require: (1) Understanding image content, (2) Describing visual elements, (3) Answering questions about images, (4) Comparing images, (5) Extracting text from images (OCR). Provides ready-to-use scripts - no custom code needed for simple cases.

Simplicity-obsessed design reviewer that interrogates complexity, questions every abstraction, and insists on the minimal viable design. Sounds like a senior engineer who has watched too many systems collapse under their own weight and now treats every unnecessary layer as a personal affront. Not a generalist skeptic — a simplicity zealot. A lens for any checkpoint — brainstorm, design, plan, implement, debug, or review — not just design. Use when: anything looks more complex than the problem needs — a speculative idea, an abstraction, a layer, an over-built fix — any time the worry is "do we actually need this, or can it be deleted?"

Curmudgeonly engineering advisor that provides grounded skepticism, evidence-linked judgment, and constructive progress on architectural decisions, legacy refactors, tooling choices, and broad "how should I start?" questions. Sounds like a senior systems engineer who has reviewed too many designs to be impressed, but still cares about correctness. A lens for any checkpoint — brainstorm, design, plan, implement, debug, or review — not just up-front decisions. Use when: weighing consequences, hidden costs, or failure modes of any choice — an idea, an architecture, a tooling/legacy call, an implementation path, or a fix — any time the worry is "what will this cost us later?"

Triage test failures in an Azure DevOps pipeline run for Fluid Framework. Use when the user shares an ADO build/pipeline URL or build ID and wants failures analyzed, when they ask "why did this pipeline fail", "summarize the test failures", "is this test flaky or a real bug", "compare these runs", or wants bugs filed for genuine failures. Covers the Real Service End to End Tests pipeline as the worked example but applies to any FF test pipeline.

Use when the user explicitly asks for a CI check or to push their branch — e.g. "ci readiness", "check ci", "pre-push check", "ready for CI", "ci check", "ready to push", "push my changes", "push the branch", "let's push". Catches common CI failures before pushing — formatting, stale API reports, missing changesets, policy violations.

Fluid Framework client release group — minor releases, patch releases, and post-release type test updates. Covers release prep, branching, version bumps, changelogs, release notes, and type test baselines. In autonomous mode, auto-detects state from the schedule and repo, attempts to execute, and falls back to a GitHub issue on failure. Triggers on "release", "do the release", "release status", version bump, release notes, changelog, release branch, or release engineering.

IMMEDIATELY USE THIS SKILL when creating or develop anything and before writing code or implementation plans - refines rough ideas into fully-formed designs through structured Socratic questioning, alternative exploration, and incremental validation

Use when implementing user interfaces or user experiences - guides through exploration of design variations, frontend setup, iteration, and proper integration

Use this skill when faced with a difficult debugging task where you need to replicate some bug or behavior in order to see what is going wrong.

Use when you need to create a new custom skill for a profile - guides through gathering requirements, creating directory structure, writing SKILL.md, and optionally adding bundled scripts

Use this when you have completed some feature implementation and have written passing tests, and you are ready to create a PR.

Generate API and service communication contracts with sequence diagram

Generate architecture diagram with component relationship details from project analysis

Run application assessment for a single repository

Generate core business workflow documentation with sequence diagram

Generate comprehensive configuration and externalized settings inventory

Create a modernization plan to migrate the project to Azure

Generate task DAGs for modernization projects — select fragments from task catalog, produce initial DAG (Stage 1), and execute/validate DAG from plan artifacts (Stage 2).

Generate data architecture and persistence layer documentation with data model diagram