578 个 ・ Microsoft 官方 · 按人气排序
Post or update one GitHub comment for an APM autopilot run. The skill assembles public or debug content, adds an AI-generated disclaimer, and supports previewing the assembled comment before posting.
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Get guidance on using APM, a package manager for AI agents, to install and share reusable instructions, skills, and server configurations. Covers dependencies, package creation, authentication, policy checks, CLI commands, and troubleshooting.
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Organize pull request reviews by selecting eligible labeled or explicitly named requests and distributing them to a dedicated worker pool. It records selection decisions and limits concurrent reviews, with two worker sessions by default.
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Turn a list of documentation pages affected by a code change into a precise editing plan. Identify sections and line ranges, record claims to verify, and flag information that must remain consistent across pages.
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Audit an entire documentation collection against current source code and command output. Check pages for outdated claims, obsolete options, and broken links, apply small corrections, and verify the edits before preparing changes for maintainer review.
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Assess one selected GitHub issue from user needs, security, and relevant design or documentation perspectives. Produce an advisory recommendation, a proposed scope brief, and a suggested reply for a human maintainer to consider.
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Bring one selected pull request toward a mergeable state by reviewing feedback, applying changes within scope, and checking tests and CI, the automated build checks. Bounded retries produce a readiness result or a clear blocker without merging.
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Review OpenAPM specification changes through four specialist perspectives covering schemas, registries, dependency resolution, and web architecture. The skill combines findings and mechanical checks into one advisory comment, separating immediate fixes from work deferred to later versions.
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Assess how a pull request affects documentation, classify the required updates, and coordinate writing, technical verification, and editorial review. The result is an advisory comment with proposed changes for affected pages or document structure.
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Improve how an open source project introduces itself and guides adoption. Shapes README sections, quickstarts, templates, announcements, and contributor entry points around a clear hook, a runnable example, and an explicit next step.
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Draft a pull request description that explains the problem, implementation, trade-offs, and testing. It combines source-backed reasoning, validated Mermaid diagrams, and actual validation output into one Markdown file reviewers can assess on its own.
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Select open or explicitly named issues for triage, an initial assessment and classification, then distribute them to dedicated workers. It filters ineligible items, records selection reasons, and runs two sessions concurrently by default.
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Review APM positioning, public documentation, release communication, and breaking-change decisions using GitHub evidence. Check that incompatible changes include changelog entries and migration notes, and resolve disagreements among the project's specialist reviewers.
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Select open pull requests for initial classification and distribute them to dedicated workers with a concurrency limit. Record why each request is included or excluded, without merging changes, assigning owners, or requesting reviewers.
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Review an APM pull request through specialist agent perspectives selected for the changed areas. Findings are combined into one advisory comment with follow-up priorities and a shipping recommendation, leaving the final decision to maintainers and authors.
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Prepare an APM release by assessing changes since the last tag, choosing a version increment, cleaning the changelog, updating version files, and running CI-equivalent checks before opening a release pull request.
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Remediate Azure Advisor recommendations. WHEN: "fix Advisor recommendation".
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Use Azure Advisor recommendations. WHEN: "show Advisor recommendations", "service retirements", "update recommendation status". DO NOT USE FOR: fixes or remediation (use azure-advisor-actionability).
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Collects bounded packet captures from AKS nodes and Azure network configuration for wire-level evidence. WHEN: "capture packets on an AKS node", "take a pcap", "run tcpdump on AKS", "prove where packets drop". Use for explicit packet-capture intent after read-only diagnostics, not general AKS connectivity or ingress troubleshooting.
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Debug live Azure Kubernetes Service (AKS) incidents with a read-only, evidence-first investigation. WHEN: pod crashes or Pending, CrashLoopBackOff, OOMKilled, ImagePullBackOff, node NotReady, DNS or ingress failure, connectivity timeout, network policy, SNAT exhaustion, node-pool scaling blocked by QuotaExceeded or InsufficientVCPUQuota, upgrade stuck, spot or zone disruption, a bare VMExtensionProvisioningError or AllocationFailed wrapper, an uncataloged capacity symptom, or 'investigate my AKS cluster'. DO NOT USE FOR: packet capture (use aks-network-capture); GPU or model-serving issues (use aks-gpu-inference); cluster creation or provisioning (use azure-kubernetes); cost (use cost-analysis from the optional azure-cost plugin); pod rightsizing (use azure-kubernetes); a fully qualified documented AKS signature with every required nested qualifier (use aks-known-issues); standalone failures on non-AKS Azure resources (use azure-diagnostics). Unqualified errors and open-ended incidents stay here only for AKS.
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Lookup documented AKS fixes only when the prompt includes an exact catalog signature and all of its qualifiers: VMCannotFitEphemeralOSDisk; NodePoolMcVersionIncompatible; 'NodeImageVersion is not accepted'; AKS SkuNotAvailable with size, location, and zone; ZonalAllocationFailed with insufficient zone capacity; OverconstrainedAllocationRequest with listed constraints; nested AKS vmssCSE/CSE VMExtensionError_OutboundConnFail, VMExtensionError_K8SAPIServerConnFail, or VMExtensionError_K8SAPIServerDNSLookupFail; or AllocationFailed with the full cataloged internal-error or insufficient-regional-capacity message. Never use for quota errors, code-only or bare wrappers, generic symptoms, incomplete signatures, or failures outside AKS; use aks-troubleshooting or azure-diagnostics.
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Diagnose Day-2 AKS GPU and KAITO incidents using profile-aware, read-only evidence. WHEN: 'Insufficient nvidia.com/gpu', GPU pod Pending, model-load OOM, DCGM/VRAM, KAITO Workspace not ready, or GPU autoscaling. DO NOT USE FOR: setup (airunway-aks-setup), non-GPU incidents (aks-troubleshooting), standalone VM quota (azure-quotas), or generic cost (cost-analysis or cost-optimization from the optional azure-cost plugin).
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Builds an Azure portal deep link to a specific blade/menu item for supported Microsoft.ContainerService, Microsoft.Kubernetes, and Microsoft.Compute resources using the aks-search-direct-mid semantic search API. WHEN: 'find where in the Azure portal to do something', 'search the portal for an operation', 'construct a portal link from a search query and a resource'.
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Intelligently deploys Azure OpenAI models to optimal regions by analyzing capacity across all available regions. Automatically checks current region first and shows alternatives if needed. USE FOR: quick deployment, optimal region, best region, automatic region selection, fast setup, multi-region capacity check, high availability deployment, deploy to best location. DO NOT USE FOR: custom SKU selection (use customize), specific version selection (use customize), custom capacity configuration (use customize), PTU deployments (use customize).
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