microsoft

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 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".

Azure Identity library for Rust. Microsoft Entra ID authentication for all Azure SDK clients. Triggers: "azure identity rust", "DeveloperToolsCredential", "authentication rust", "managed identity rust", "credential rust", "Entra ID rust".

Azure Key Vault Certificates library for Rust. Create, manage, and use X.509 certificates including self-signed and CA-issued. Triggers: "keyvault certificates rust", "CertificateClient rust", "create certificate rust", "self-signed certificate rust", "X.509 rust".

Azure Key Vault Keys library for Rust. Create, manage, and use cryptographic keys including RSA, EC, and HSM-protected keys. Triggers: "keyvault keys rust", "KeyClient rust", "create key rust", "encrypt rust", "wrap key rust", "sign rust".

Azure Key Vault Secrets library for Rust. Store and retrieve secrets, passwords, and API keys. Triggers: "keyvault secrets rust", "SecretClient rust", "get secret rust", "set secret rust", "list secrets 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".

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.

ユーザーが実験、探索、またはチュートリアル用の Jupyter ノートブック（`.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。

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.

Microsoft-ന്റെ ഔദ്യോഗിക ഡോക്യുമെന്റേഷൻ അന്വേഷിച്ച് Azure, .NET, Agent Framework, Aspire, VS Code, GitHub എന്നിവ ഉൾപ്പെടെയുള്ള മേഖലയിലെ ആശയങ്ങൾ, ട്യൂട്ടോറിയലുകൾ, കോഡ് ഉദാഹരണങ്ങൾ എന്നിവ കണ്ടെത്തുക. ഡിഫോൾട്ട് ആയി Microsoft Learn MCP ഉപയോഗിക്കുന്നു; learn.microsoft.com-ന്റെ പുറത്തുള്ള ഉള്ളടക്കങ്ങൾക്ക് Context7യും Aspire MCPയും ഉപയോഗിക്കുന്നു.

Launch Code OSS (VS Code from sources) into an isolated throwaway profile with unique debug ports so you can drive it with @playwright/cli AND attach a Node debugger via dap-cli in the same session. Use when working on VS Code itself and you want to interact with the running workbench, automate chat or UI flows, test UI features, take screenshots, set breakpoints in the renderer / extension host / main process, or combine UI driving with debugging.

Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting session data.

Find and read logs from Code OSS dev builds. Use when: finding logs, reading log files, debugging Code OSS, checking renderer logs, extension host logs, agent host logs, main process logs, investigating errors in dev builds.

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.

Use when working on the Chat Customizations editor — the management UI for agents, skills, instructions, hooks, prompts, MCP servers, and plugins.

Investigate unexpected chat agent behavior by analyzing direct debug logs in JSONL files. Use when users ask why something happened, why a request was slow, why tools or subagents were used or skipped, or why instructions/skills/agents did not load.

OpenTelemetry instrumentation for the Copilot Chat extension — covers the four agent execution paths, the IOTelService abstraction, span/metric/event conventions, and the relationship between code and the user/developer monitoring docs. Use when adding/changing OTel spans, metrics, or events; instrumenting a new agent surface; touching the Copilot CLI bridge or Claude span emission; or updating `extensions/copilot/docs/monitoring/agent_monitoring*.md`.

Launch and automate VS Code Insiders with the Copilot Chat extension using @playwright/cli via Chrome DevTools Protocol. Use when you need to interact with the VS Code UI, automate the chat panel, test the extension UI, or take screenshots. Triggers include 'automate VS Code', 'interact with chat', 'test the UI', 'take a screenshot', 'launch with debugging'.

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

Prepare Azure apps for deployment (infra Bicep/Terraform, azure.yaml, Dockerfiles). Use for create/modernize or create+deploy; not cross-cloud migration (use azure-cloud-migrate). DO NOT USE FOR: copilot-sdk apps (use azure-hosted-copilot-sdk). WHEN: "create app", "build web app", "create API", "create serverless HTTP API", "create frontend", "create back end", "build a service", "modernize application", "update application", "add authentication", "add caching", "host on Azure", "create and deploy", "deploy to Azure", "deploy to Azure using Terraform", "deploy to Azure App Service", "deploy to Azure App Service using Terraform", "deploy to Azure Container Apps", "deploy to Azure Container Apps using Terraform", "generate Terraform", "generate Bicep", "function app", "timer trigger", "service bus trigger", "event-driven function", "containerized Node.js app", "social media app", "static portfolio website", "todo list with frontend and API", "prepare my Azure application to use Key Vault", "managed identity".

List, find, and show Azure resources across subscriptions or resource groups. Handles prompts like "list the websites in my subscription", "list my web apps", "show my app services", "list virtual machines", "list my VMs", "show storage accounts", "find container apps", and "what resources do I have". USE FOR: list websites, list web apps, list app services, show websites in subscription, resource inventory, find resources by tag, tag analysis, orphaned resource discovery (not for cost analysis), unattached disks, count resources by type, cross-subscription lookup, and Azure Resource Graph queries. DO NOT USE FOR: deploying/changing resources (use azure-deploy), cost optimization (use azure-cost), or non-Azure clouds.

Fine-tune models on Azure AI Foundry using SFT (supervised), DPO (preference), or RFT (reinforcement with graders). Covers dataset preparation, training job submission, deployment, and evaluation. USE FOR: fine-tune, SFT, DPO, RFT, training data, grader, distillation, fine-tuned model, training job, large file upload, calibrate grader, deploy fine-tuned model, evaluate fine-tuned model. DO NOT USE FOR: general model deployment without fine-tuning (use deploy-model), agent creation (use agents), prompt optimization without training (use prompt-optimizer).

Debug Azure production issues on Azure using AppLens, Azure Monitor, resource health, and safe triage. WHEN: debug production issues, troubleshoot app service, app service high CPU, app service deployment failure, troubleshoot container apps, troubleshoot functions, troubleshoot AKS, kubectl cannot connect, kube-system/CoreDNS failures, pod pending, crashloop, node not ready, upgrade failures, analyze logs, KQL, insights, image pull failures, cold start issues, health probe failures, resource health, root cause of errors, troubleshoot event hubs, troubleshoot service bus, messaging SDK error, AMQP connection failure, message lock lost, service bus dead letter.

**WORKFLOW SKILL** — Iteratively improve skill frontmatter compliance using the Ralph loop pattern. WHEN: "run sensei", "sensei help", "improve skill", "fix frontmatter", "skill compliance", "frontmatter audit", "score skill", "check skill tokens". INVOKES: token counting tools, test runners, git commands. FOR SINGLE OPERATIONS: use token CLI directly for counts/checks.

Review skill PRs with structured severity-rated feedback covering token budgets, routing conflicts, required sections, and repo conventions. WHEN: "review skill", "review skill PR", "review skill changes", "check skill quality", "skill PR feedback".

Assess and improve the reliability posture of Azure Functions: zone redundancy, ZRS storage, health probes, multi-region failover. Scans deployed resources, presents a feature-pivoted checklist, then drives staged remediation (CLI or IaC patches) end-to-end with user confirmation. WHEN: "assess reliability", "check reliability", "zone redundant", "multi-region failover", "high availability", "disaster recovery", "single points of failure", "reliability posture".

Configure the Canvas Authoring MCP server for the current coauthoring session. USE WHEN "configure MCP", "set up MCP server", "MCP not working", "connect Canvas Apps MCP", "canvas-authoring not available", "MCP not configured", "set up canvas apps". DO NOT USE WHEN prerequisites are missing — direct the user to install .NET 10 SDK first.

Creates, updates, and deploys Power Apps generative pages for model-driven apps using React v17, TypeScript, and Fluent UI V9. Orchestrates specialist agents for planning, entity creation, and code generation. Use it when user asks to build, retrieve, or update a page in an existing Microsoft Power Apps model-driven app. Use it when user mentions "generative page", "page in a model-driven", or "genux".

Creates or edits a Power Apps Canvas App through the Canvas Authoring MCP coauthoring session. Handles new app generation from requirements, simple inline edits, and complex multi-screen changes with parallel screen builders. Triggers on requests to create, build, generate, modify, update, change, or edit a Canvas App or .pa.yaml files.

[DEPRECATED — use canvas-app instead] Generate a complete Power Apps canvas app.

Activates and provisions a Power Pages website in a Power Platform environment via the Power Platform REST API. Use when the user wants to activate, provision, turn on, or enable a Power Pages website or portal.

Integrates Power Automate cloud flows into a Power Pages site. Lists available flows, suggests relevant ones based on intent, identifies scenarios and web roles, creates metadata files, and generates client-side code to call flows. Handles both new flow registration and adding already-registered flows to additional pages without re-creating metadata. Use when the user wants to add, connect, register, or link a Power Automate cloud flow to their site.

Creates, edits, and manages Power Pages Server Logic files — server-side JavaScript that runs securely on the Power Pages runtime. Orchestrates the full lifecycle: gathering requirements, fetching documentation, implementing code, configuring site settings, and deploying. Use when the user wants to add server-side code, create API endpoints, or move logic from the browser to the server in their Power Pages site.

Audits existing table permissions on a Power Pages site by analyzing them against site code and Dataverse metadata. Generates an HTML audit report with findings grouped by severity (critical, warning, info, pass) and suggests fixes for issues found. Use when the user wants to review, verify, or check table permissions for security issues.

Deep research on a given topic. Use for comprehensive topic exploration — technical subjects, market analysis, architecture deep-dives, competitive analysis, etc. Also use when the user asks to 'research', 'deep dive', 'investigate', or 'find out about' a topic that requires multi-source synthesis. You should run MULTIPLE subagents in parallel to explore multiple angles and topics.

High-signal feedback on plans, designs, implementations, and partial progress. Catches bugs, logic errors, and design flaws that may not be apparent to the original author. Call this skill for any non-trivial task to get a second opinion — the best time is after planning but before implementing. Call it early and often during development to course correct before problems compound. Will NOT comment on style, formatting, or trivial matters.

Multi-model council planning for implementation and architecture decisions. Use when the user asks to 'plan with council', 'multi-model plan', 'get different perspectives on approach', 'council plan', or wants multiple models to independently propose plans for the same task. Also use when the user asks to 'debate approaches', 'compare strategies', or 'cross-plan'.

Multi-model council review for diffs, pull requests, and risky changes. It is CRITICAL to use this skill after ANY non-trivial development phase — changes are usually not 100% correct. Development CANNOT be called done until the code has been reviewed. Use whenever the user asks for a review, PR feedback, a bug hunt in recent edits, or wants multiple models to inspect the same change independently. Also use when the user asks to 'discuss findings', 'cross-review', or 'debate' review results between models.

Monitor a pull request until CI status or Copilot review is available. Use when: monitor PR, watch PR, land PR, wait for CI, wait for checks, wait for review, check PR status. Starts two async terminal tasks (CI + Copilot review) and reacts when either completes.

Analyze VS Code rolling build health on Azure DevOps. Use when: the rolling build is red right now, you need a report for the last 100 builds, you need to identify the commit range that broke the build, you are on build champ duty, or you need a build health report.

Review an implementation plan produced by the Plan agent. It is CRITICAL to review plans before handing off to implementation — plans often have gaps, incorrect assumptions, or suboptimal sequencing that are cheaper to catch now than after coding. Use when the user asks to 'review the plan', 'check my plan', 'is this plan ready', or after the Plan agent produces a plan.md.

Read and write agent storage — memory and rules with environment-aware fallback

Implementation finalization with PR. Use when implementation is complete and you need to commit, push, or open a pull request. Includes automated reviews and technical debt tracking. Do not use during implementation (use devsquad.implement), for standalone intermediate commits (use git-commit), or for branch creation (use git-branch).

Formatting and style rules for markdown documentation. Use when generating or editing any project markdown document. Do not use for source code, code comments, or commit messages. For work item content (titles, descriptions, comments on GitHub Issues or Azure DevOps), use the Content Style section of the `work-item-creation` skill.

Capture and consult codebase-specific learnings across the lifecycle. Use when an agent encounters a correction loop, review finding, test prerequisite, or recurring pattern that future sessions should know about. Also use at the start of implement, verify, or review to check for known patterns. Do not use for architecture decisions (use ADRs), for debugging the current failure (use debugging-recovery), or for one-time context that will not recur.

Verify and create SDD Framework configuration files (.github/copilot-instructions.md, instructions, coding-guidelines, markdownlint). Use when initializing a project or checking if configuration files are up to date. Do not use for documentation templates (use init-docs) or community files (use init-scaffold).

Verify and create SDD Framework documentation templates (feature spec, migration spec, envisioning, ADR templates). Use when initializing a project or checking if documentation templates are up to date. Do not use for configuration files (use init-config) or community files (use init-scaffold).

Label-based state machine for triaging issues and work items. Manages state transitions, generates durable triage artifacts, and supports resumable sessions. Use when triaging GitHub issues or Azure DevOps work items. Do not use for creating new work items from scratch (use work-item-creation) or for managing implementation workflow of already-triaged items (use work-item-workflow).

Rules and checklist for creating work items on GitHub Issues or Azure DevOps. Use when you need to create issues, user stories, tasks, epics, or features on the board. Do not use for platform configuration (use board-config), managing workflow of existing tasks (use work-item-workflow), or for comments on work items.

Work item workflow for implementation. Use when starting work on a GitHub issue or Azure DevOps work item to verify assignee, dependencies, priority, and capacity. Do not use for creating new work items (use work-item-creation), for suggesting the next task (use next-task), or when the work source is only tasks.md without an issue/work item.

Create alerts, notifications, and automated actions on Fabric data and events via Fabric REST API and `az rest` CLI. Use when the user wants to: (1) create, update, or delete an alert or notification flow, (2) send a Teams message, send an email, or run a Fabric item when something happens, (3) connect alert logic to Eventhouse, Eventstream, Real-time Hub, or Digital Twin Builder / Ontology data, (4) adjust thresholds, filters, event triggers, or actions, (5) troubleshoot or change an existing Activator/Reflex definition. Triggers: "create an alert", "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"

Check for skills-for-fabric marketplace updates at session start. Compares local version against GitHub releases and shows changelog if updates are available. Use when the user wants to: (1) check for skill updates, (2) see what's new in skills-for-fabric, (3) verify current version. Triggers: "check for updates", "am I up to date", "what version", "update skills", "show changelog".

Develop Microsoft Fabric Spark/data engineering workflows and write code in Fabric Notebook cells with intelligent routing to specialized resources. Provides workspace/lakehouse management, notebook code authoring (PySpark, Scala, SparkR, SQL), and routes to: data engineering patterns, development workflow, or infrastructure orchestration. Use when the user wants to: (1) manage Fabric workspaces and resources, (2) write or debug code in notebook cells, (3) use notebookutils, (4) develop notebooks and PySpark applications, (5) design data pipelines, (6) provision infrastructure as code. Triggers: "develop notebook", "data engineering", "workspace setup", "pipeline design", "infrastructure provisioning", "Delta Lake patterns", "Spark development", "lakehouse configuration", "write notebook code", "notebookutils", "notebook cell", "PySpark notebook", "%%sql cell", "%%configure", "fabric notebook", "run notebook", "notebook deployment".

Inspect existing alerts, notifications, and automated actions in Fabric via read-only REST API calls using `az rest` CLI. Use when the user wants to: (1) list existing alerts in a workspace, (2) inspect how an alert or notification is configured, (3) read and decode an Activator/Reflex definition (ReflexEntities.json), (4) list rules, sources, and actions behind an alert, (5) understand why an alert fires or what action it takes. Triggers: "show my alerts", "what alerts do I have", "inspect this alert", "show me the rule", "show me the action", "show me the source", "get reflex definition", "list activators", "activator details"

Diagnose failed Spark jobs, unhealthy Livy sessions, and performance bottlenecks in Microsoft Fabric via read-only CLI triage. Use when the user wants to: (1) diagnose why a Spark job, notebook run, or Lakehouse job failed, (2) triage stuck or dead Livy sessions, (3) identify OOM, shuffle spill, or data skew, (4) retrieve driver and executor logs or Spark Advisor findings, (5) copy event logs and start a local Spark History Server, (6) diagnose all Spark activities within a failed pipeline run. Triggers: "diagnose my failed notebook", "why did my spark job fail", "triage spark failure", "diagnose pipeline run failure", "why did my pipeline fail", "livy session stuck in starting", "spark executor OOM", "check spark advisor findings", "shuffle spill diagnosis", "why did my lakehouse job fail", "diagnose lakehouse table load", "data skew diagnosis", "open spark history server locally", "analyze spark failure logs", "spark job triage".

Create, update, delete, and manage Fabric Dataflows Gen2 artifacts with Power Query M mashup definitions via CLI (az rest / curl). Uses az rest and curl against the Fabric REST API to author definitions containing base64-encoded mashup.pq, queryMetadata.json, and .platform parts. Supports creating dataflows with inline definitions, modifying mashup queries, binding connections, triggering Execute refresh jobs with typed parameter overrides, and exporting definitions for CI/CD. Use when the user wants to: (1) create a new Dataflow Gen2 with Power Query M queries, (2) update a dataflow mashup definition, (3) trigger a dataflow refresh job, (4) bind or manage dataflow connections, (5) set up CI/CD via definition export and import, (6) delete a dataflow, (7) configure staging destinations. Triggers: "create dataflow", "author dataflow", "Power Query M", "mashup document", "update dataflow definition", "refresh dataflow", "dataflow connection", "ETL dataflow", "dataflow CI/CD".

Find and discover Microsoft Fabric items across workspaces when the workspace is unknown. Use when the user wants to: (1) find an item by name across workspaces, (2) list items of specific type across workspaces, (3) identify which workspace contains an item, (4) return item/workspace IDs for downstream API calls. Triggers: "which workspace has", "where is", "what items do I have", "do I have", "find item", "find all items", "search for item", "discover items", "find across workspaces".

Assess, plan, and execute dataflow Gen1 → Gen2.1 CI/CD save-as operations via CLI (az rest / curl) against both Power BI REST and Fabric REST APIs. Scan workspaces or entire tenants for Gen1 dataflows, evaluate save-as readiness with seven risk signals (incremental refresh, BYOSA storage, Power Automate triggers, pipeline dependencies, linked entities, DirectQuery, caller-not-owner), produce a Save-As Readiness Snapshot (markdown + JSON), and invoke the SaveAsNativeArtifact API to create upgraded Gen2.1 copies of Gen1 dataflows. Use when the user wants to: (1) discover Gen1 dataflows in a workspace or tenant, (2) assess save-as readiness and risk signals, (3) upgrade or migrate Gen1 into a Gen2.1 copy, (4) validate post-save-as data integrity, (5) detect residual Gen1 references. Triggers: "save Gen1 dataflow", "convert dataflow Gen1", "upgrade dataflow", "migrate dataflow", "dataflow readiness", "Gen1 to Gen2", "dataflow save-as assessment", "saveAsNativeArtifact", "dataflow save-as scan".

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.

Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation

ALWAYS load this skill if it is not already loaded, for ANY user query or conversation - establishes the Nori workflow, protected-branch check, operating mode, tone, and coding guidelines before any other work

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes - four-phase framework (root cause investigation, pattern analysis, hypothesis testing, implementation) that ensures understanding before attempting solutions

Use when the /systems-design mode is active. 9-phase structured design methodology -- problem framing, system classification, constraints, candidate architectures, tradeoff analysis, risk review, refinement, migration planning, and documentation. Governs conversation flow, delegation patterns, and user validation checkpoints.

Use when the /systems-design-review mode is active. 7-step design review methodology -- understand the design, classify the system, evaluate against codebase, adversarial analysis, tradeoff validation, synthesis, and action items. Governs conversation flow, delegation patterns, and user validation checkpoints.

Adversarial review of a system design from 6 critical perspectives -- SRE, security, staff engineer, finance, operator, and developer advocate. Produces a unified risk assessment. Use for INTERACTIVE on-demand reviews during a design conversation (/adversarial-review). For RECIPE-DRIVEN reviews (where prior step context is needed), use the systems-design-critic agent instead.

Domain patterns for Azure cloud architecture — compute selection, managed services, identity (Entra ID), networking, data platform, messaging, deployment, cost management, and operational patterns. Use when designing or evaluating a system deployed on Microsoft Azure.

Domain patterns for peer-to-peer system architecture — network topologies, NAT traversal, peer discovery, data distribution, consistency without central authority, identity and trust, and incentive mechanisms. Use when designing or evaluating a decentralized, peer-to-peer, or mesh-networked system.

Domain patterns for single-page application architecture — client-side routing, state management, rendering strategies, authentication, performance, and offline support. Use when designing or evaluating a browser-based SPA, progressive web app, or rich client-side application.

Domain-Driven Design as a lens for system architecture — bounded contexts, aggregates, ubiquitous language, context mapping, domain events, and strategic vs tactical patterns. Use when modeling complex business domains, defining service boundaries, or evaluating whether a system's structure reflects its domain.

The Unix/Linux design philosophy as a lens for system design — mechanism vs policy, composability, small tools, text streams, convention over configuration, and the principle of least surprise. Use when evaluating designs for composability, simplicity, or separation of concerns.

Use when starting work in any repository. Auto-surface when an agent is about to write code, create a PR, or verify work. Teaches the discovery pattern for finding and applying per-repo conventions (AGENTS.md, PR templates, CONTRIBUTING.md) before acting.

Use when verifying that completed work actually works. Auto-surface during /verify mode, post-implementation review, or before claiming a task is done. Teaches the discipline of testing outcomes vs implementation, the unit/integration/smoke gradient, and what "done" actually means.

Use when building a new CLI tool that needs one-line install via uv or npm, subcommand dispatch with a default action, or 3-tier config resolution (CLI flags, config file, hardcoded defaults).

Use when designing a curl-piped install script for a project that cannot use uv tool install or npm publish — multi-service stacks (Docker Compose), raw TS/React apps, tools that bootstrap system dependencies, or installs for non-technical audiences. Documents the security trade-off, the community convention used by rustup, bun, deno, fly, ollama, and supabase, and the cases where this pattern is the wrong answer.

Use when your service needs authentication that works without friction locally but secures remote access, automatic TLS certificate setup, or token-based auth with auto-generation and localhost bypass.

Use when your tool needs persistent configuration files with safe defaults merging, atomic state writes that survive crashes, or conventional file locations for config vs state vs secrets.

Use when running tasks in Docker containers with safety limits, watchdog monitoring for resource enforcement, orphan container recovery, sidecar container provisioning, or scripting reproducible dev stack environments.

Use when processes need to communicate via the filesystem without a message broker — JSONL event logs, atomic state snapshots, async request/response via file pairs, or SSE streaming from file tailing.

**WORKFLOW SKILL** — Deploy Aspire apps from AppHost models to Docker Compose, Kubernetes, Azure, or AWS. WHEN: "deploy Aspire app", "publish Aspire artifacts", "deploy to Azure Container Apps", "generate Kubernetes artifacts", "tear down Aspire deployment". INVOKES: aspire CLI, Aspire docs, target cloud/container CLIs. FOR SINGLE OPERATIONS: use generic Azure, Kubernetes, Docker, or AWS tools only when no Aspire AppHost exists.

Use when working with an Aspire distributed application: operate an AppHost or resources through the Aspire CLI; start, stop, restart, or wait for resources; inspect app state, logs, traces, docs, or health; add integrations; manage secrets/config; publish/deploy or run pipeline steps; initialize an existing app; recover TypeScript `.aspire/modules`; find frontend URLs for Playwright; expose custom dashboard/resource commands; or understand Aspire AppHost APIs in C# or TypeScript. Use even if the user says AppHost, resources, dashboard, bootstrap, Playwright URL, or local distributed app workflow without naming Aspire. Do not use for non-Aspire .NET apps, container-only repos without an AppHost, or ordinary build/test tasks.

One-time skill for completing Aspire initialization in an existing app after `aspire init` has dropped the skeleton AppHost. Use this skill when an `aspire.config.json` exists but the AppHost has not yet been wired up.

Guide for diagnosing GitHub Actions test failures, extracting failed tests from runs, and creating or updating failing-test issues. Use this when asked to investigate GitHub Actions test failures, download failure logs, create failing-test issues, or debug CI issues.

Guide for writing Aspire CLI end-to-end tests using Hex1b terminal automation. Use this when asked to create, modify, or debug CLI E2E tests.

Measures Aspire startup profiling with CLI self-profile capture and dashboard export traces.

Downloads and tests Aspire CLI from a PR build, preferably in the repo-local container runner under eng/scripts, verifies version, and runs test scenarios based on PR changes. Use this when asked to test a pull request.

Review a GitHub pull request for problems. Use when asked to review a PR, do a code review, check a PR for issues, or review pull request changes. Focuses only on identifying problems — not style nits or praise.