[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M699MHW18SSBDNV7P96C4B44":3,"skill-same:01M699MHW18SSBDNV7P96C4B44":287},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":26,"publishedAt":49,"linkOnly":50,"markdownContent":51,"markdownBody":52,"frontMatter":53,"refName":56,"commitSha":57,"skillDirectory":58,"forksCount":59,"repositoryHtmlUrl":60,"repositoryHomepageUrl":6,"ownerHtmlUrl":61,"ownerBlogUrl":62,"ownerDescription":63,"updatedAt":64,"install":65,"resources":78},"01M699MHW18SSBDNV7P96C4B44","azure-enterprise-infra-planner",null,"Architect and provision enterprise Azure infrastructure from workload descriptions. For cloud architects and platform engineers planning networking, identity, security, compliance, and multi-resource topologies with WAF alignment. Generates Bicep or Terraform directly (no azd). WHEN: 'plan Azure infrastructure', 'architect Azure landing zone', 'design hub-spoke network', 'plan multi-region DR topology', 'set up VNets firewalls and private endpoints', 'subscription-scope Bicep deployment', 'Azure Backup for VM workloads'. PREFER azure-prepare FOR app-centric workflows.","microsoft\u002Fazure-skills","microsoft","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F6154722?v=4","01M698VYDXZ6JW5WH3CRV650R8","Microsoft","01M699HXPKQFT1BH5KD1PG0CB4",1636,"MIT","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fazure-skills\u002Fblob\u002Fmain\u002F.github\u002Fplugins\u002Fazure-skills\u002Fskills\u002Fazure-enterprise-infra-planner\u002FSKILL.md",[18,23],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000011","运维与部署","SCENARIO","使用场景",{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发",[27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,9,48],"infra","azure enterprise infra planner","azure","planner","Enterprise","when","design","azure backup","scope","app","alignment","up","plan","SET","network","topology","networking","workload","prepare","identity","workflows","security","2026-11-10 10:12:30",false,"---\nname: azure-enterprise-infra-planner\ndescription: \"Architect and provision enterprise Azure infrastructure from workload descriptions. For cloud architects and platform engineers planning networking, identity, security, compliance, and multi-resource topologies with WAF alignment. Generates Bicep or Terraform directly (no azd). WHEN: 'plan Azure infrastructure', 'architect Azure landing zone', 'design hub-spoke network', 'plan multi-region DR topology', 'set up VNets firewalls and private endpoints', 'subscription-scope Bicep deployment', 'Azure Backup for VM workloads'. PREFER azure-prepare FOR app-centric workflows.\"\nlicense: MIT\nmetadata:\n  author: Microsoft\n  version: \"1.4.2\"\n---\n\n# Azure Enterprise Infra Planner\n\n## When to Use This Skill\n\nActivate this skill when user wants to:\n- Plan enterprise Azure infrastructure from a workload or architecture description\n- Architect a landing zone, hub-spoke network, or multi-region topology\n- Design networking infrastructure: VNets, subnets, firewalls, private endpoints, VPN gateways\n- Plan identity, RBAC, and compliance-driven infrastructure\n- Generate Bicep or Terraform for subscription-scope or multi-resource-group deployments\n- Plan disaster recovery, failover, or cross-region high-availability topologies\n\n## Quick Reference\n\n| Property | Details |\n|---|---|\n| MCP tools | `insights_get`, `get_azure_bestpractices_get`, `wellarchitectedframework_serviceguide_get`, `microsoft_docs_fetch`, `microsoft_docs_search`, `bicepschema_get` |\n| CLI commands | `az deployment group create`, `az bicep build`, `az resource list`, `terraform init`, `terraform plan`, `terraform validate`, `terraform apply`, `checkov` |\n| Output schema | [schema.md](references\u002Fschema.md) |\n| Key references | [workflow.md](references\u002Fworkflow.md), [waf-checklist.md](references\u002Fwaf-checklist.md), [resources\u002F](references\u002Fresources\u002FREADME.md), [constraints\u002F](references\u002Fconstraints\u002FREADME.md) |\n\n## Workflow (Start Here)\n\nFollow the step-by-step instructions in [workflow.md](references\u002Fworkflow.md) to execute the 7 phases of infrastructure planning and provisioning.\n\n## Architecture\n\nThe skill runs a **7-phase, gated pipeline**. Input is triaged into one of two flows:\n\n- **Greenfield** — only new requirements; run the phases straight through.\n- **Referenced (brownfield)** — the user supplies something that already exists (a live resource \u002F\n  resource group \u002F subscription, IaC or an infra plan, or a requirements doc). The same phases run, plus\n  [referenced-workload.md](references\u002Freferenced-workload.md): existing resources are inventoried and\n  referenced (never recreated), the new workload is wired into them, and **Phase 7 deploys additively**\n  (incremental only — never modifying or destroying the referenced resources).\n\nEvery phase advances only after its gate passes. Phase 5 requires explicit user approval; **Phase 6 is a\nhardened, self-verifying gate** — the generated IaC must be secure-by-default, pass local validation\n(`az bicep build` \u002F `terraform validate`) with zero errors, pass a `checkov` security scan with no\nunresolved high\u002Fcritical findings, and the skill must **show the command output** and emit a completion\nself-check before advancing; Phase 7 requires an explicit, risk-acknowledged deploy confirmation.\n\n```mermaid\nflowchart TD\n    IN([Input]) --> TRIAGE{Existing infra\u003Cbr\u002F>referenced?}\n    TRIAGE -- \"No (greenfield)\" --> P1\n    TRIAGE -- \"Yes (referenced)\" --> RW[\u002Freferenced-workload.md:\u003Cbr\u002F>inventory + assign roles\u003Cbr\u002F>reference, never recreate\u002F]\n    RW --> P1\n\n    subgraph PIPE [7-phase gated pipeline]\n        direction TB\n        P1[Phase 1 · Extract insights] --> P2[Phase 2 · Research best practices]\n        P2 --> P3[Phase 3 · Research resources]\n        P3 --> P4[Phase 4 · Generate plan]\n        P4 --> P5{Phase 5 · Verify\u003Cbr\u002F>user approves?}\n        P5 -- \"no\" --> P4\n        P5 -- \"approved\" --> P6[Phase 6 · Generate IaC]\n        P6 --> VAL{Validate\u003Cbr\u002F>az bicep build \u002F\u003Cbr\u002F>terraform validate}\n        VAL -- \"errors\" --> P6\n        VAL -- \"clean\" --> P7{Phase 7 · Deploy\u003Cbr\u002F>risk-ack confirm?}\n    end\n\n    P7 -- \"greenfield\" --> DEP[az deployment \u002F terraform apply]\n    P7 -- \"referenced\" --> DEPADD[Additive deploy · incremental only\u003Cbr\u002F>what-if preview · no destroy of\u003Cbr\u002F>referenced resources]\n    DEP --> OUT([Deployed])\n    DEPADD --> OUT\n\n    classDef gate fill:#fff3cd,stroke:#d39e00,color:#000;\n    classDef ref fill:#e2f0d9,stroke:#548235,color:#000;\n    class P5,VAL,P7,TRIAGE gate;\n    class RW,DEPADD ref;\n```\n\n**Artifacts** (written under `\u003Cproject-root>\u002F`): `.azure\u002Finsights.json` (Phase 1),\n`.azure\u002Finfrastructure-plan.json` (Phase 4, status `draft`→`approved`→`deployed`), and\n`infra\u002Fmain.bicep` + `infra\u002Fmodules\u002F*` or `infra\u002Fmain.tf` + `infra\u002Fmodules\u002F**` (Phase 6).\n\n## MCP Tools\n\n| Tool | Purpose |\n|------|---------|\n| `insights_get` | Retrieve insights about the user's existing Azure environment to guide planning decisions |\n| `get_azure_bestpractices_get` | Azure best practices for code generation, operations, and deployment |\n| `wellarchitectedframework_serviceguide_get` | WAF service guide for a specific Azure service |\n| `microsoft_docs_search` | Search Microsoft Learn for relevant documentation chunks |\n| `microsoft_docs_fetch` | Fetch full content of a Microsoft Learn page by URL |\n| `bicepschema_get` | Bicep schema definition for any Azure resource type (latest API version) |\n\n## Error Handling\n\n| Error | Cause | Fix |\n|---|---|---|\n| MCP tool error or not available | Tool call timeout, connection error, or tool doesn't exist | Retry once; fall back to reference files and notify user if unresolved |\n| Plan approval missing | `meta.status` is not `approved` | Stop and prompt user for approval before IaC generation or deployment |\n| IaC validation failure | `az bicep build` or `terraform validate` returns errors | Fix the generated code and re-validate; notify user if unresolved |\n| Pairing constraint violation | Incompatible SKU or resource combination | Fix in plan before proceeding to IaC generation |\n| Infra plan or IaC files not found | Files written to wrong location or not created | Verify files exist at `\u003Cproject-root>\u002F.azure\u002F` and `\u003Cproject-root>\u002Finfra\u002F`; if missing, re-create the files by following [workflow.md](references\u002Fworkflow.md) exactly |\n","# Azure Enterprise Infra Planner\n\n## When to Use This Skill\n\nActivate this skill when user wants to:\n- Plan enterprise Azure infrastructure from a workload or architecture description\n- Architect a landing zone, hub-spoke network, or multi-region topology\n- Design networking infrastructure: VNets, subnets, firewalls, private endpoints, VPN gateways\n- Plan identity, RBAC, and compliance-driven infrastructure\n- Generate Bicep or Terraform for subscription-scope or multi-resource-group deployments\n- Plan disaster recovery, failover, or cross-region high-availability topologies\n\n## Quick Reference\n\n| Property | Details |\n|---|---|\n| MCP tools | `insights_get`, `get_azure_bestpractices_get`, `wellarchitectedframework_serviceguide_get`, `microsoft_docs_fetch`, `microsoft_docs_search`, `bicepschema_get` |\n| CLI commands | `az deployment group create`, `az bicep build`, `az resource list`, `terraform init`, `terraform plan`, `terraform validate`, `terraform apply`, `checkov` |\n| Output schema | [schema.md](references\u002Fschema.md) |\n| Key references | [workflow.md](references\u002Fworkflow.md), [waf-checklist.md](references\u002Fwaf-checklist.md), [resources\u002F](references\u002Fresources\u002FREADME.md), [constraints\u002F](references\u002Fconstraints\u002FREADME.md) |\n\n## Workflow (Start Here)\n\nFollow the step-by-step instructions in [workflow.md](references\u002Fworkflow.md) to execute the 7 phases of infrastructure planning and provisioning.\n\n## Architecture\n\nThe skill runs a **7-phase, gated pipeline**. Input is triaged into one of two flows:\n\n- **Greenfield** — only new requirements; run the phases straight through.\n- **Referenced (brownfield)** — the user supplies something that already exists (a live resource \u002F\n  resource group \u002F subscription, IaC or an infra plan, or a requirements doc). The same phases run, plus\n  [referenced-workload.md](references\u002Freferenced-workload.md): existing resources are inventoried and\n  referenced (never recreated), the new workload is wired into them, and **Phase 7 deploys additively**\n  (incremental only — never modifying or destroying the referenced resources).\n\nEvery phase advances only after its gate passes. Phase 5 requires explicit user approval; **Phase 6 is a\nhardened, self-verifying gate** — the generated IaC must be secure-by-default, pass local validation\n(`az bicep build` \u002F `terraform validate`) with zero errors, pass a `checkov` security scan with no\nunresolved high\u002Fcritical findings, and the skill must **show the command output** and emit a completion\nself-check before advancing; Phase 7 requires an explicit, risk-acknowledged deploy confirmation.\n\n```mermaid\nflowchart TD\n    IN([Input]) --> TRIAGE{Existing infra\u003Cbr\u002F>referenced?}\n    TRIAGE -- \"No (greenfield)\" --> P1\n    TRIAGE -- \"Yes (referenced)\" --> RW[\u002Freferenced-workload.md:\u003Cbr\u002F>inventory + assign roles\u003Cbr\u002F>reference, never recreate\u002F]\n    RW --> P1\n\n    subgraph PIPE [7-phase gated pipeline]\n        direction TB\n        P1[Phase 1 · Extract insights] --> P2[Phase 2 · Research best practices]\n        P2 --> P3[Phase 3 · Research resources]\n        P3 --> P4[Phase 4 · Generate plan]\n        P4 --> P5{Phase 5 · Verify\u003Cbr\u002F>user approves?}\n        P5 -- \"no\" --> P4\n        P5 -- \"approved\" --> P6[Phase 6 · Generate IaC]\n        P6 --> VAL{Validate\u003Cbr\u002F>az bicep build \u002F\u003Cbr\u002F>terraform validate}\n        VAL -- \"errors\" --> P6\n        VAL -- \"clean\" --> P7{Phase 7 · Deploy\u003Cbr\u002F>risk-ack confirm?}\n    end\n\n    P7 -- \"greenfield\" --> DEP[az deployment \u002F terraform apply]\n    P7 -- \"referenced\" --> DEPADD[Additive deploy · incremental only\u003Cbr\u002F>what-if preview · no destroy of\u003Cbr\u002F>referenced resources]\n    DEP --> OUT([Deployed])\n    DEPADD --> OUT\n\n    classDef gate fill:#fff3cd,stroke:#d39e00,color:#000;\n    classDef ref fill:#e2f0d9,stroke:#548235,color:#000;\n    class P5,VAL,P7,TRIAGE gate;\n    class RW,DEPADD ref;\n```\n\n**Artifacts** (written under `\u003Cproject-root>\u002F`): `.azure\u002Finsights.json` (Phase 1),\n`.azure\u002Finfrastructure-plan.json` (Phase 4, status `draft`→`approved`→`deployed`), and\n`infra\u002Fmain.bicep` + `infra\u002Fmodules\u002F*` or `infra\u002Fmain.tf` + `infra\u002Fmodules\u002F**` (Phase 6).\n\n## MCP Tools\n\n| Tool | Purpose |\n|------|---------|\n| `insights_get` | Retrieve insights about the user's existing Azure environment to guide planning decisions |\n| `get_azure_bestpractices_get` | Azure best practices for code generation, operations, and deployment |\n| `wellarchitectedframework_serviceguide_get` | WAF service guide for a specific Azure service |\n| `microsoft_docs_search` | Search Microsoft Learn for relevant documentation chunks |\n| `microsoft_docs_fetch` | Fetch full content of a Microsoft Learn page by URL |\n| `bicepschema_get` | Bicep schema definition for any Azure resource type (latest API version) |\n\n## Error Handling\n\n| Error | Cause | Fix |\n|---|---|---|\n| MCP tool error or not available | Tool call timeout, connection error, or 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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).","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fazure-skills\u002Fblob\u002Fmain\u002Fskills\u002Fmicrosoft-foundry\u002Fmodels\u002Fdeploy-model\u002Fpreset\u002FSKILL.md",[318,319],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[314,297,321,9,322,323,300,324,325,302,326,327,328,29,329,330,331,307,332,333,334,335,336],"setup","capacity","customize","quick","availability","deployment","alternatives","selection","custom","deployments","high availability","version","across","check","multi","first",{"skillNo":338,"name":323,"nameZh":6,"description":339,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":340,"categories":341,"keywords":343,"publishedAt":49},"01M699VBT6YFAKBWCK890XDB6N","Interactive guided deployment flow for Azure OpenAI models with full customization control. Step-by-step selection of model version, SKU (GlobalStandard\u002FStandard\u002FProvisionedManaged), capacity, RAI policy (content filter), and advanced options (dynamic quota, priority processing, spillover). USE FOR: custom deployment, customize model deployment, choose version, select SKU, set capacity, configure content filter, RAI policy, deployment options, detailed deployment, advanced deployment, PTU deployment, provisioned throughput. DO NOT USE FOR: quick deployment to optimal region (use preset).","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fazure-skills\u002Fblob\u002Fmain\u002Fskills\u002Fmicrosoft-foundry\u002Fmodels\u002Fdeploy-model\u002Fcustomize\u002FSKILL.md",[342],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[323,314,9,322,344,40,324,345,346,347,348,349,328,350,351,352,353,354,355,356,357,300,302,326],"policy","processing","advanced","model","select","choose","configure","filter","azure openai","options","flow","openai","throughput","full",{"skillNo":359,"name":322,"nameZh":6,"description":360,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":361,"categories":362,"keywords":363,"publishedAt":49},"01M699V9FXHBSWG3Y48057VAYZ","Discovers available Azure OpenAI model capacity across regions and projects. Analyzes quota limits, compares availability, and recommends optimal deployment locations based on capacity requirements. USE FOR: find capacity, check quota, where can I deploy, capacity discovery, best region for capacity, multi-project capacity search, quota analysis, model availability, region comparison, check TPM availability. DO NOT USE FOR: actual deployment (hand off to preset or customize after discovery), quota increase requests (direct user to Azure Portal), listing existing deployments.","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fazure-skills\u002Fblob\u002Fmain\u002Fskills\u002Fmicrosoft-foundry\u002Fmodels\u002Fdeploy-model\u002Fcapacity\u002FSKILL.md",[],[322,314,297,9,323,364,347,365,366,367,368,369,333,352,370,371,355,372,373,300,325,302,374,326],"projects","project","search","analysis","listing","hand","limits","azure portal","direct","TPM","discovery",{"skillNo":376,"name":377,"nameZh":6,"description":378,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":379,"categories":380,"keywords":383,"publishedAt":49},"01M699V7GW2RF4AB3RE3Z8Y048","deploy-model","Unified Azure OpenAI model deployment skill with intelligent intent-based routing. Handles quick preset deployments, fully customized deployments (version\u002FSKU\u002Fcapacity\u002FRAI 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\u002Fcreate), project creation (use project\u002Fcreate).","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fazure-skills\u002Fblob\u002Fmain\u002Fskills\u002Fmicrosoft-foundry\u002Fmodels\u002Fdeploy-model\u002FSKILL.md",[381,382],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[297,384,347,314,385,386,9,322,344,40,364,324,387,365,38,367,368,333,388,352,389,390,355,300,325],"deploy model","MCP","foundry","creation","create","intent","list",{"skillNo":392,"name":393,"nameZh":6,"description":394,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":395,"categories":396,"keywords":398,"publishedAt":49},"01M699V3NA4YQKCHJTVWHBQH10","finetuning","Fine-tune models on Microsoft 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).","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fazure-skills\u002Fblob\u002Fmain\u002Fskills\u002Fmicrosoft-foundry\u002Ffinetuning\u002FSKILL.md",[397],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[393,399,297,386,400,9,401,387,347,402,403,404,405,406,407,408,409,410,300,302,411,412,326,413],"placeholder","microsoft foundry","Prompt Optimization","training","dataset","optimizer","Evaluation","tuning","grader","data","supervised","distillation","Optimization","calibrate","submission"]