[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M699Q4B6ZE6CEXDWF5S511C3":3,"skill-same:01M699Q4B6ZE6CEXDWF5S511C3":91},{"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":47,"linkOnly":48,"markdownContent":49,"markdownBody":50,"frontMatter":51,"refName":54,"commitSha":55,"skillDirectory":56,"forksCount":57,"repositoryHtmlUrl":58,"repositoryHomepageUrl":6,"ownerHtmlUrl":59,"ownerBlogUrl":60,"ownerDescription":61,"updatedAt":62,"install":63,"resources":76},"01M699Q4B6ZE6CEXDWF5S511C3","preset",null,"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).","microsoft\u002Fazure-skills","microsoft","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F6154722?v=4","01M698VYDXZ6JW5WH3CRV650R8","Microsoft","01M699HXPKQFT1BH5KD1PG0CB4",1640,"MIT","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fazure-skills\u002Fblob\u002Fmain\u002F.github\u002Fplugins\u002Fazure-skills\u002Fskills\u002Fmicrosoft-foundry\u002Fmodels\u002Fdeploy-model\u002Fpreset\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",[5,27,28,29,30,31,32,33,34,35,36,37,9,38,39,40,41,42,43,44,45,46],"deployments","custom","alternatives","for","quick","availability","multi","high availability","across","do","selection","version","use","check","first","deployment","azure","customize","capacity","deploy","2026-11-10 10:12:30",false,"---\nname: preset\ndescription: \"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).\"\nlicense: MIT\nmetadata:\n  author: Microsoft\n  version: \"1.0.1\"\n---\n\n# Deploy Model to Optimal Region\n\nAutomates intelligent Azure OpenAI model deployment by checking capacity across regions and deploying to the best available option.\n\n## What This Skill Does\n\n1. Verifies Azure authentication and project scope\n2. Checks capacity in current project's region\n3. If no capacity: analyzes all regions and shows available alternatives\n4. Filters projects by selected region\n5. Supports creating new projects if needed\n6. Deploys model with GlobalStandard SKU\n7. Monitors deployment progress\n\n## Prerequisites\n\n- Azure CLI installed and configured\n- Active Azure subscription with Cognitive Services read\u002Fcreate permissions\n- Microsoft Foundry project resource ID (`PROJECT_RESOURCE_ID` env var or provided interactively)\n  - Format: `\u002Fsubscriptions\u002F{sub-id}\u002FresourceGroups\u002F{rg}\u002Fproviders\u002FMicrosoft.CognitiveServices\u002Faccounts\u002F{account}\u002Fprojects\u002F{project}`\n  - Found in: Microsoft Foundry portal → Project → Overview → Resource ID\n\n## Quick Workflow\n\n### Fast Path (Current Region Has Capacity)\n```\n1. Check authentication → 2. Get project → 3. Check current region capacity\n→ 4. Deploy immediately\n```\n\n### Alternative Region Path (No Capacity)\n```\n1. Check authentication → 2. Get project → 3. Check current region (no capacity)\n→ 4. Query all regions → 5. Show alternatives → 6. Select region + project\n→ 7. Deploy\n```\n\n---\n\n## Deployment Phases\n\n| Phase | Action | Key Commands |\n|-------|--------|-------------|\n| 1. Verify Auth | Check Azure CLI login and subscription | `az account show`, `az login` |\n| 2. Get Project | Parse `PROJECT_RESOURCE_ID` ARM ID, verify exists | `az cognitiveservices account show` |\n| 3. Get Model | List available models, user selects model + version | `az cognitiveservices account list-models` |\n| 4. Check Current Region | Query capacity using GlobalStandard SKU | `az rest --method GET ...\u002FmodelCapacities` |\n| 5. Multi-Region Query | If no local capacity, query all regions | Same capacity API without location filter |\n| 6. Select Region + Project | User picks region; find or create project | `az cognitiveservices account list`, `az cognitiveservices account create` |\n| 7. Deploy | Generate unique name, calculate capacity (50% available, min 50 TPM), create deployment | `az cognitiveservices account deployment create` |\n\nFor detailed step-by-step instructions, see [workflow reference](references\u002Fworkflow.md).\n\n---\n\n## Error Handling\n\n| Error | Symptom | Resolution |\n|-------|---------|------------|\n| Auth failure | `az account show` returns error | Run `az login` then `az account set --subscription \u003Cid>` |\n| No quota | All regions show 0 capacity | Defer to the [quota skill](..\u002F..\u002F..\u002Fquota\u002Fquota.md) for increase requests and troubleshooting; check existing deployments; try alternative models |\n| Model not found | Empty capacity list | Verify model name with `az cognitiveservices account list-models`; check case sensitivity |\n| Name conflict | \"deployment already exists\" | Append suffix to deployment name (handled automatically by `generate_deployment_name` script) |\n| Region unavailable | Region doesn't support model | Select a different region from the available list |\n| Permission denied | \"Forbidden\" or \"Unauthorized\" | Verify Cognitive Services Contributor role: `az role assignment list --assignee \u003Cuser>` |\n\n---\n\n## Advanced Usage\n\n```bash\n# Custom capacity\naz cognitiveservices account deployment create ... --sku-capacity \u003Cvalue>\n\n# Check deployment status\naz cognitiveservices account deployment show --name \u003Cacct> --resource-group \u003Crg> --deployment-name \u003Cname> --query \"{Status:properties.provisioningState}\"\n\n# Delete deployment\naz cognitiveservices account deployment delete --name \u003Cacct> --resource-group \u003Crg> --deployment-name \u003Cname>\n```\n\n## Notes\n\n- **SKU:** GlobalStandard only — **API Version:** 2024-10-01 (GA stable)\n\n---\n\n## Related Skills\n\n- **microsoft-foundry** - Parent skill for Microsoft Foundry operations\n- **[quota](..\u002F..\u002F..\u002Fquota\u002Fquota.md)** — For quota viewing, increase requests, and troubleshooting quota errors, defer to this skill\n- **azure-quick-review** - Review Azure resources for compliance\n- **cost-estimation** - Estimate costs through the separately installed `azure-cost` plugin\n- **azure-validate** - Validate Azure infrastructure before deployment\n","# Deploy Model to Optimal Region\n\nAutomates intelligent Azure OpenAI model deployment by checking capacity across regions and deploying to the best available option.\n\n## What This Skill Does\n\n1. Verifies Azure authentication and project scope\n2. Checks capacity in current project's region\n3. If no capacity: analyzes all regions and shows available alternatives\n4. Filters projects by selected region\n5. Supports creating new projects if needed\n6. Deploys model with GlobalStandard SKU\n7. Monitors deployment progress\n\n## Prerequisites\n\n- Azure CLI installed and configured\n- Active Azure subscription with Cognitive Services read\u002Fcreate permissions\n- Microsoft Foundry project resource ID (`PROJECT_RESOURCE_ID` env var or provided interactively)\n  - Format: `\u002Fsubscriptions\u002F{sub-id}\u002FresourceGroups\u002F{rg}\u002Fproviders\u002FMicrosoft.CognitiveServices\u002Faccounts\u002F{account}\u002Fprojects\u002F{project}`\n  - Found in: Microsoft Foundry portal → Project → Overview → Resource ID\n\n## Quick Workflow\n\n### Fast Path (Current Region Has Capacity)\n```\n1. Check authentication → 2. Get project → 3. Check current region capacity\n→ 4. Deploy immediately\n```\n\n### Alternative Region Path (No Capacity)\n```\n1. Check authentication → 2. Get project → 3. Check current region (no capacity)\n→ 4. Query all regions → 5. Show alternatives → 6. Select region + project\n→ 7. Deploy\n```\n\n---\n\n## Deployment Phases\n\n| Phase | Action | Key Commands |\n|-------|--------|-------------|\n| 1. Verify Auth | Check Azure CLI login and subscription | `az account show`, `az login` |\n| 2. Get Project | Parse `PROJECT_RESOURCE_ID` ARM ID, verify exists | `az cognitiveservices account show` |\n| 3. Get Model | List available models, user selects model + version | `az cognitiveservices account list-models` |\n| 4. Check Current Region | Query capacity using GlobalStandard SKU | `az rest --method GET ...\u002FmodelCapacities` |\n| 5. Multi-Region Query | If no local capacity, query all regions | Same capacity API without location filter |\n| 6. Select Region + Project | User picks region; find or create project | `az cognitiveservices account list`, `az cognitiveservices account create` |\n| 7. Deploy | Generate unique name, calculate capacity (50% available, min 50 TPM), create deployment | `az cognitiveservices account deployment create` |\n\nFor detailed step-by-step instructions, see [workflow reference](references\u002Fworkflow.md).\n\n---\n\n## Error Handling\n\n| Error | Symptom | Resolution |\n|-------|---------|------------|\n| Auth failure | `az account show` returns error | Run `az login` then `az account set --subscription \u003Cid>` |\n| No quota | All regions show 0 capacity | Defer to the [quota skill](..\u002F..\u002F..\u002Fquota\u002Fquota.md) for increase requests and troubleshooting; check existing deployments; try alternative models |\n| Model not found | Empty capacity list | Verify model name with `az cognitiveservices account list-models`; check case sensitivity |\n| Name conflict | \"deployment already exists\" | Append suffix to deployment name (handled automatically by `generate_deployment_name` script) |\n| Region unavailable | Region doesn't support model | Select a different region from the available list |\n| Permission denied | \"Forbidden\" or \"Unauthorized\" | Verify Cognitive Services Contributor role: `az role assignment list --assignee \u003Cuser>` |\n\n---\n\n## Advanced Usage\n\n```bash\n# Custom capacity\naz cognitiveservices account deployment create ... --sku-capacity \u003Cvalue>\n\n# Check deployment status\naz cognitiveservices account deployment show --name \u003Cacct> --resource-group \u003Crg> --deployment-name \u003Cname> --query \"{Status:properties.provisioningState}\"\n\n# Delete deployment\naz cognitiveservices account deployment delete --name \u003Cacct> --resource-group \u003Crg> --deployment-name \u003Cname>\n```\n\n## Notes\n\n- **SKU:** GlobalStandard only — **API Version:** 2024-10-01 (GA stable)\n\n---\n\n## Related Skills\n\n- **microsoft-foundry** - Parent skill for Microsoft Foundry operations\n- **[quota](..\u002F..\u002F..\u002Fquota\u002Fquota.md)** — For quota viewing, increase requests, and troubleshooting quota errors, defer to this skill\n- **azure-quick-review** - Review Azure resources for compliance\n- **cost-estimation** - Estimate costs through the separately installed `azure-cost` plugin\n- **azure-validate** - Validate Azure infrastructure before deployment\n",{"name":5,"license":15,"metadata":52,"description":7},{"author":12,"version":53},"1.0.1","main","fbda857c484a85c7ce644f56809b7f204471fb69",".github\u002Fplugins\u002Fazure-skills\u002Fskills\u002Fmicrosoft-foundry\u002Fmodels\u002Fdeploy-model\u002Fpreset",267,"https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fazure-skills","https:\u002F\u002Fgithub.com\u002Fmicrosoft","https:\u002F\u002Fopensource.microsoft.com","Open source projects and samples from Microsoft","2026-11-14 01:56:00",{"source":8,"skillName":5,"commands":64,"prompt":74,"zipAvailable":75},[65,68,71],{"tool":66,"command":67},"npx","npx skills add microsoft\u002Fazure-skills --skill preset",{"tool":69,"command":70},"bunx","bunx skills add microsoft\u002Fazure-skills --skill preset",{"tool":72,"command":73},"pnpm","pnpm dlx skills add microsoft\u002Fazure-skills --skill preset","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fazure-skills\u002Fblob\u002Fmain\u002F.github\u002Fplugins\u002Fazure-skills\u002Fskills\u002Fmicrosoft-foundry\u002Fmodels\u002Fdeploy-model\u002Fpreset\u002FSKILL.md",true,[77,83,87],{"path":78,"resourceType":79,"resourceTypeDesc":80,"sizeBytes":81,"sourceHtmlUrl":82},"EXAMPLES.md","REFERENCE","参考文档",2989,"https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fazure-skills\u002Fblob\u002Fmain\u002F.github\u002Fplugins\u002Fazure-skills\u002Fskills\u002Fmicrosoft-foundry\u002Fmodels\u002Fdeploy-model\u002Fpreset\u002FEXAMPLES.md",{"path":84,"resourceType":79,"resourceTypeDesc":80,"sizeBytes":85,"sourceHtmlUrl":86},"references\u002Fpreset-workflow.md",22492,"https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fazure-skills\u002Fblob\u002Fmain\u002F.github\u002Fplugins\u002Fazure-skills\u002Fskills\u002Fmicrosoft-foundry\u002Fmodels\u002Fdeploy-model\u002Fpreset\u002Freferences\u002Fpreset-workflow.md",{"path":88,"resourceType":79,"resourceTypeDesc":80,"sizeBytes":89,"sourceHtmlUrl":90},"references\u002Fworkflow.md",5763,"https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fazure-skills\u002Fblob\u002Fmain\u002F.github\u002Fplugins\u002Fazure-skills\u002Fskills\u002Fmicrosoft-foundry\u002Fmodels\u002Fdeploy-model\u002Fpreset\u002Freferences\u002Fworkflow.md",[92,115,123,145,162,179],{"skillNo":93,"name":94,"nameZh":6,"description":95,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":96,"categories":97,"keywords":99,"publishedAt":47},"01M699VFT1T15GFDGC4K4ZHY4N","python-appservice-deploy","Deploy Python (Flask\u002FDjango\u002FFastAPI) 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\u002FBicep\u002FIaC, full infra — use azure-prepare.","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fazure-skills\u002Fblob\u002Fmain\u002Fskills\u002Fpython-appservice-deploy\u002FSKILL.md",[98],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},[100,46,101,102,103,104,36,105,30,106,43,107,108,109,39,110,111,112,113,114],"python appservice deploy","python","linux","infra","app","django","azure app service","container","iac","fastapi","apps","when","code","functions","fastapi app",{"skillNo":116,"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":117,"categories":118,"keywords":121,"publishedAt":47},"01M699VDV3PT5P0YDXRT4GM2TJ","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fazure-skills\u002Fblob\u002Fmain\u002Fskills\u002Fmicrosoft-foundry\u002Fmodels\u002Fdeploy-model\u002Fpreset\u002FSKILL.md",[119,120],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[5,46,122,9,45,44,36,31,32,30,42,29,37,43,28,27,34,39,38,35,40,33,41],"setup",{"skillNo":124,"name":44,"nameZh":6,"description":125,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":126,"categories":127,"keywords":129,"publishedAt":47},"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",[128],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[44,5,9,45,130,131,31,132,133,134,135,136,37,137,138,139,140,141,142,143,144,36,30,42],"policy","SET","processing","advanced","model","select","choose","configure","filter","azure openai","options","flow","openai","throughput","full",{"skillNo":146,"name":45,"nameZh":6,"description":147,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":148,"categories":149,"keywords":150,"publishedAt":47},"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",[],[45,5,46,9,44,151,134,152,153,154,155,156,35,139,157,158,142,159,160,36,32,30,161,42],"projects","project","search","analysis","listing","hand","limits","azure portal","direct","TPM","discovery",{"skillNo":163,"name":164,"nameZh":6,"description":165,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":166,"categories":167,"keywords":170,"publishedAt":47},"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",[168,169],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[46,171,134,5,172,173,9,45,130,131,151,31,174,152,175,154,155,35,176,139,177,178,142,36,32],"deploy model","MCP","foundry","creation","up","create","intent","list",{"skillNo":180,"name":181,"nameZh":6,"description":182,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":183,"categories":184,"keywords":186,"publishedAt":47},"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",[185],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[181,187,46,173,188,9,189,174,134,190,191,192,193,194,195,196,197,198,36,30,199,200,42,201],"placeholder","microsoft foundry","Prompt Optimization","training","dataset","optimizer","Evaluation","tuning","grader","data","supervised","distillation","Optimization","calibrate","submission"]