[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M699JEM8QECJ3VMEEP5DS3HR":3,"skill-same:01M699JEM8QECJ3VMEEP5DS3HR":71},{"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":18,"publishedAt":35,"linkOnly":36,"markdownContent":37,"markdownBody":38,"frontMatter":39,"refName":42,"commitSha":43,"skillDirectory":44,"forksCount":45,"repositoryHtmlUrl":46,"repositoryHomepageUrl":6,"ownerHtmlUrl":47,"ownerBlogUrl":48,"ownerDescription":49,"updatedAt":50,"install":51,"resources":64},"01M699JEM8QECJ3VMEEP5DS3HR","azure-advisor",null,"Use Azure Advisor. WHEN: \"show recommendations\", \"top Advisor actions\", \"prioritize recommendations\", \"service retirements\", \"update status\". Unused-resource discovery and Cost\u002FIdleResources requests use azure-advisor-cost-optimization; generic Cost and cross-category requests stay here. DO NOT USE FOR: fixes (use azure-advisor-actionability).","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-advisor\u002Fskills\u002Fazure-advisor\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,9,34],"advisor","azure","azure advisor","fixes","when","use","service","prioritize","update","actions","recommendations","for","top","show","do","status","2026-11-10 10:12:30",false,"---\nname: azure-advisor\ndescription: \"Use Azure Advisor. WHEN: \\\"show recommendations\\\", \\\"top Advisor actions\\\", \\\"prioritize recommendations\\\", \\\"service retirements\\\", \\\"update status\\\". Unused-resource discovery and Cost\u002FIdleResources requests use azure-advisor-cost-optimization; generic Cost and cross-category requests stay here. DO NOT USE FOR: fixes (use azure-advisor-actionability).\"\nlicense: MIT\nmetadata:\n  author: Microsoft\n  version: \"1.0.3\"\n---\n\n# Azure Advisor\n\nPrefer Advisor MCP tools over Resource Graph or generic ARM calls.\nReuse supplied scope and identifiers; ask only for missing input.\n\n## Quick reference\n\nPrefer Azure Advisor MCP tools. Use their current schemas for parameters and limits; discover unfamiliar parameters rather than inventing them.\n\n| Intent | Tool |\n|---|---|\n| Counts, totals, breakdowns, or distributions | `advisor_recommendation_summary`; non-prioritized, with the requested `group-by` |\n| Broad priorities: top recommendations\u002Factions, most important, critical, or fix-first advice | `advisor_recommendation_summary`; `prioritized: true` (automatically groups by recommendation type) |\n| Individual recommendations or affected resources, including status-filtered records | `advisor_recommendation_list`; no prior summary required; for priority ordering within a known type, pass one `recommendation-type-ids` array entry and `prioritized: true` |\n| Complete, dismiss, postpone, or reactivate | `advisor_recommendation_update` |\n| Browse recommendation types | `advisor_metadata_list` |\n| Get one type by ID | `advisor_metadata_get` |\n| Fix or remediate a recommendation | `azure-advisor-actionability` skill; it owns remediation tool calls and safeguards |\n\n## Workflow\n\n- For unused-resource discovery, including \"what are we paying for that is no longer\n  being used\", or combined `category=Cost` and `sub-category=IdleResources`, load\n  `azure-advisor-cost-optimization` first. It owns scope, sequencing and response templates;\n  broad discovery must not skip to resource details.\n- Generic\u002Fprioritized Cost outside IdleResources, cross-category and other requests stay here.\n  Preserve requested filters; never silently add IdleResources.\n- Before generic calls or reporting, read [Workflow](references\u002Fworkflow.md).\n- For remediation, load `azure-advisor-actionability`; it owns execution safeguards.\n\n1. Reuse known scope and identifiers. Pass the requested count as `top`: groups for summary, records for list. \"Critical\" means priority, not an `impact` value.\n2. For savings priorities, use `category: \"Cost\"`. Top retirements use prioritized summary, not list, with `sub-category: \"ServiceUpgradeAndRetirement\"` and `retirement-date: \"le:\u003Cyyyy-MM-dd>\"` for on-or-before cutoffs.\n3. For drill-downs, preserve scope and filters; pass the selected recommendation-type group's actual GUID `key` as the sole entry in list `recommendation-type-ids`. Retain `prioritized: true` after a prioritized summary and add `category: \"Cost\"` for a Cost type. Do not copy summary `top` to list.\n4. If broad priorities require `status` or `tracking-ids`, explain that cross-type ranking is unavailable. Use filtered, non-prioritized list and explicitly label results unranked, not \"top\". Never silently drop unsupported constraints.\n5. Present returned data in server ranking order; disclose errors and truncation. Never count a capped list or filter capped results to simulate a server-side date query.\n\n\"Top actions\" and \"what should I fix first?\" ask for prioritization advice, not permission to remediate.\n\n## Safety\n\nAsk for and wait for user confirmation before recommendation-state updates. The actionability skill owns remediation safeguards.\nOn every model, visibly present results\u002Fproposals before dependent questions.\nMissing data stays `Unavailable`, not zero.\n","# Azure Advisor\n\nPrefer Advisor MCP tools over Resource Graph or generic ARM calls.\nReuse supplied scope and identifiers; ask only for missing input.\n\n## Quick reference\n\nPrefer Azure Advisor MCP tools. Use their current schemas for parameters and limits; discover unfamiliar parameters rather than inventing them.\n\n| Intent | Tool |\n|---|---|\n| Counts, totals, breakdowns, or distributions | `advisor_recommendation_summary`; non-prioritized, with the requested `group-by` |\n| Broad priorities: top recommendations\u002Factions, most important, critical, or fix-first advice | `advisor_recommendation_summary`; `prioritized: true` (automatically groups by recommendation type) |\n| Individual recommendations or affected resources, including status-filtered records | `advisor_recommendation_list`; no prior summary required; for priority ordering within a known type, pass one `recommendation-type-ids` array entry and `prioritized: true` |\n| Complete, dismiss, postpone, or reactivate | `advisor_recommendation_update` |\n| Browse recommendation types | `advisor_metadata_list` |\n| Get one type by ID | `advisor_metadata_get` |\n| Fix or remediate a recommendation | `azure-advisor-actionability` skill; it owns remediation tool calls and safeguards |\n\n## Workflow\n\n- For unused-resource discovery, including \"what are we paying for that is no longer\n  being used\", or combined `category=Cost` and `sub-category=IdleResources`, load\n  `azure-advisor-cost-optimization` first. It owns scope, sequencing and response templates;\n  broad discovery must not skip to resource details.\n- Generic\u002Fprioritized Cost outside IdleResources, cross-category and other requests stay here.\n  Preserve requested filters; never silently add IdleResources.\n- Before generic calls or reporting, read [Workflow](references\u002Fworkflow.md).\n- For remediation, load `azure-advisor-actionability`; it owns execution safeguards.\n\n1. Reuse known scope and identifiers. Pass the requested count as `top`: groups for summary, records for list. \"Critical\" means priority, not an `impact` value.\n2. For savings priorities, use `category: \"Cost\"`. Top retirements use prioritized summary, not list, with `sub-category: \"ServiceUpgradeAndRetirement\"` and `retirement-date: \"le:\u003Cyyyy-MM-dd>\"` for on-or-before cutoffs.\n3. For drill-downs, preserve scope and filters; pass the selected recommendation-type group's actual GUID `key` as the sole entry in list `recommendation-type-ids`. Retain `prioritized: true` after a prioritized summary and add `category: \"Cost\"` for a Cost type. Do not copy summary `top` to list.\n4. If broad priorities require `status` or `tracking-ids`, explain that cross-type ranking is unavailable. Use filtered, non-prioritized list and explicitly label results unranked, not \"top\". Never silently drop unsupported constraints.\n5. Present returned data in server ranking order; disclose errors and truncation. Never count a capped list or filter capped results to simulate a server-side date query.\n\n\"Top actions\" and \"what should I fix first?\" ask for prioritization advice, not permission to remediate.\n\n## Safety\n\nAsk for and wait for user confirmation before recommendation-state updates. The actionability skill owns remediation safeguards.\nOn every model, visibly present results\u002Fproposals before dependent questions.\nMissing data stays `Unavailable`, not zero.\n",{"name":5,"license":15,"metadata":40,"description":7},{"author":12,"version":41},"1.0.3","main","9aa7f618563713f47481af67b7b9dcaafdc2154a",".github\u002Fplugins\u002Fazure-advisor\u002Fskills\u002Fazure-advisor",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","2026-11-13 02:10:45",{"source":8,"skillName":5,"commands":52,"prompt":62,"zipAvailable":63},[53,56,59],{"tool":54,"command":55},"npx","npx skills add microsoft\u002Fazure-skills --skill azure-advisor",{"tool":57,"command":58},"bunx","bunx skills add microsoft\u002Fazure-skills --skill azure-advisor",{"tool":60,"command":61},"pnpm","pnpm dlx skills add microsoft\u002Fazure-skills --skill azure-advisor","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fazure-skills\u002Fblob\u002Fmain\u002F.github\u002Fplugins\u002Fazure-advisor\u002Fskills\u002Fazure-advisor\u002FSKILL.md",true,[65],{"path":66,"resourceType":67,"resourceTypeDesc":68,"sizeBytes":69,"sourceHtmlUrl":70},"references\u002Fworkflow.md","REFERENCE","参考文档",4190,"https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fazure-skills\u002Fblob\u002Fmain\u002F.github\u002Fplugins\u002Fazure-advisor\u002Fskills\u002Fazure-advisor\u002Freferences\u002Fworkflow.md",[72,99,126,148,165,182],{"skillNo":73,"name":74,"nameZh":6,"description":75,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":76,"categories":77,"keywords":83,"publishedAt":35},"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",[78],{"categoryNo":79,"categoryName":80,"taxonomyType":81,"taxonomyTypeDesc":82},"01JBSEEDCAT000000000000011","运维与部署","SCENARIO","使用场景",[84,85,86,87,88,89,33,90,30,91,20,92,93,94,24,95,23,96,97,98],"python appservice deploy","deploy","python","linux","infra","app","django","azure app service","container","iac","fastapi","apps","code","functions","fastapi app",{"skillNo":100,"name":101,"nameZh":6,"description":102,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":103,"categories":104,"keywords":109,"publishedAt":35},"01M699VDV3PT5P0YDXRT4GM2TJ","preset","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).","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fazure-skills\u002Fblob\u002Fmain\u002Fskills\u002Fmicrosoft-foundry\u002Fmodels\u002Fdeploy-model\u002Fpreset\u002FSKILL.md",[105,106],{"categoryNo":79,"categoryName":80,"taxonomyType":81,"taxonomyTypeDesc":82},{"categoryNo":107,"categoryName":108,"taxonomyType":81,"taxonomyTypeDesc":82},"01JBSEEDCAT000000000000023","Skill与智能体开发",[101,85,110,9,111,112,33,113,114,30,115,116,117,20,118,119,120,24,121,122,123,124,125],"setup","capacity","customize","quick","availability","deployment","alternatives","selection","custom","deployments","high availability","version","across","check","multi","first",{"skillNo":127,"name":112,"nameZh":6,"description":128,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":129,"categories":130,"keywords":132,"publishedAt":35},"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",[131],{"categoryNo":107,"categoryName":108,"taxonomyType":81,"taxonomyTypeDesc":82},[112,101,9,111,133,134,113,135,136,137,138,139,117,140,141,142,143,144,145,146,147,33,30,115],"policy","SET","processing","advanced","model","select","choose","configure","filter","azure openai","options","flow","openai","throughput","full",{"skillNo":149,"name":111,"nameZh":6,"description":150,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":151,"categories":152,"keywords":153,"publishedAt":35},"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",[],[111,101,85,9,112,154,137,155,156,157,158,159,122,142,160,161,145,162,163,33,114,30,164,115],"projects","project","search","analysis","listing","hand","limits","azure portal","direct","TPM","discovery",{"skillNo":166,"name":167,"nameZh":6,"description":168,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":169,"categories":170,"keywords":173,"publishedAt":35},"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",[171,172],{"categoryNo":79,"categoryName":80,"taxonomyType":81,"taxonomyTypeDesc":82},{"categoryNo":107,"categoryName":108,"taxonomyType":81,"taxonomyTypeDesc":82},[85,174,137,101,175,176,9,111,133,134,154,113,177,155,178,157,158,122,179,142,180,181,145,33,114],"deploy model","MCP","foundry","creation","up","create","intent","list",{"skillNo":183,"name":184,"nameZh":6,"description":185,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":186,"categories":187,"keywords":189,"publishedAt":35},"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",[188],{"categoryNo":107,"categoryName":108,"taxonomyType":81,"taxonomyTypeDesc":82},[184,190,85,176,191,9,192,177,137,193,194,195,196,197,198,199,200,201,33,30,202,203,115,204],"placeholder","microsoft foundry","Prompt Optimization","training","dataset","optimizer","Evaluation","tuning","grader","data","supervised","distillation","Optimization","calibrate","submission"]