[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6993YEMM0A4AQ3BMHT2JJGQ":3,"skill-same:01M6993YEMM0A4AQ3BMHT2JJGQ":80},{"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":39,"linkOnly":40,"markdownContent":41,"markdownBody":42,"frontMatter":43,"refName":47,"commitSha":48,"skillDirectory":49,"forksCount":50,"repositoryHtmlUrl":51,"repositoryHomepageUrl":6,"ownerHtmlUrl":52,"ownerBlogUrl":53,"ownerDescription":54,"updatedAt":55,"install":56,"resources":69},"01M6993YEMM0A4AQ3BMHT2JJGQ","gke-cost-analysis",null,"Answer natural language questions and perform analysis on GKE cluster and workload costs using BigQuery billing exports, cost allocation data, and live cluster monitoring metrics. Use when querying GKE costs across projects, namespaces, or workloads, analyzing billing reports in BigQuery (`bq`), checking cluster cost budgets (`gcloud billing`), or diagnosing cost drivers like pod requests vs. actual utilization (`kubectl top`). Don't use for applying cost optimization changes, creating rightsizing manifests (VPA\u002FMPA), or selecting ComputeClasses (use gke-cost-optimization instead).","google\u002Fskills","google","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F1342004?v=4","01M698VYEFDM0VJBZDYYJ2T83S","Google","01M698WR0H76ENHE587T9EJT89",24122,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fcloud\u002Fgke-cost-analysis\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"gke cost analysis","cost","analysis","gke","cost analysis","monitoring","Optimization","cost optimization","projects","use","gcloud","bq","natural language","cluster","billing","answer","namespaces","manifests","for","when","2026-11-10 10:12:30",false,"---\nname: gke-cost-analysis\nmetadata:\n  version: \"1.0.1\"\n  category: CloudObservabilityAndMonitoring\ndescription: >-\n  Answer natural language questions and perform analysis on GKE cluster and\n  workload costs using BigQuery billing exports, cost allocation data, and live\n  cluster monitoring metrics. Use when querying GKE costs across projects,\n  namespaces, or workloads, analyzing billing reports in BigQuery (`bq`), checking\n  cluster cost budgets (`gcloud billing`), or diagnosing cost drivers like pod\n  requests vs. actual utilization (`kubectl top`). Don't use for applying cost\n  optimization changes, creating rightsizing manifests (VPA\u002FMPA), or selecting\n  ComputeClasses (use gke-cost-optimization instead).\n---\n\n# GKE Cost Analysis\n\nThis skill provides guidance on answering natural language questions about\nGKE-related costs, billing reports, and utilization analysis.\n\n## Attribution\n\n**MUST READ**: Before executing any `gcloud`, REST API, or MCP command, you\nMUST read [Usage Attribution](references\u002Fattribution.md). For commands executed\ndirectly in the terminal (never in generated scripts, Terraform, or user code),\nprefix `gcloud` with\n`CLOUDSDK_METRICS_REQUEST_ATTRIBUTION=\"agent-skills\u002F1.0 (skill:gke-cost-analysis)\"`\nand append `agent-skills\u002F1.0 (skill:gke-cost-analysis)` to `User-Agent` headers.\n\n## Overview\n\nWhen users ask about GKE costs (e.g., \"What are my costs across projects?\",\n\"What's my most expensive namespace?\", \"Why is my cluster cost spiking?\"), use\nthis skill to provide a structured and expert response using BigQuery billing\nexports, cost allocation metadata, and live cluster metrics.\n\n## Instructions\n\nWhen handling a cost-related question:\n\n1.  **Provide a Direct Answer**: Address the specific cost question or\n    analytical request clearly and concisely.\n2.  **Explain BigQuery Integration**: Explain how to query BigQuery for\n    historical cost breakdown. Note that GKE costs originate from the GCP\n    Billing Detailed BigQuery Export (`gcp_billing_export_resource_v1_*`).\n3.  **Check & Verify Cost Allocation**: Explain that GKE Cost Allocation must be\n    enabled on the cluster (`--enable-cost-allocation`) for namespace, label,\n    and workload-level billing granularity. If queries return empty labels,\n    provide the `gcloud` command to enable it.\n4.  **Analyze Pricing Drivers & Utilization**: When diagnosing cost drivers,\n    explain whether the cluster is in Autopilot (billed by requested pod\n    CPU\u002Fmemory) or Standard mode (billed by underlying VM node size + control\n    plane fees), and compare live utilization (`kubectl top`) against\n    provisioned requests.\n5.  **Provide Actionable Commands\u002FQueries**: Provide concrete BigQuery CLI (`bq\n    query`) commands or read-only `gcloud`\u002F`kubectl` inspection commands. Prefer\n    `bq` over BigQuery Studio when available.\n\n## Key Points & Pricing Drivers\n\n-   **Data Source**: GKE costs come from GCP Billing Detailed BigQuery Export.\n    The user must provide the full path to their BigQuery table (dataset name\n    and table name containing the Billing Account ID).\n-   **Granularity Requirement**: GKE Cost Allocation\n    (`--enable-cost-allocation`) must be enabled on the cluster to populate\n    `goog-k8s-cluster-name`, `k8s-namespace`, `k8s-workload-name`, and\n    `k8s-workload-type` labels in BigQuery.\n-   **Autopilot vs. Standard Cost Drivers**:\n    -   **Autopilot Pricing**: Billed directly on pod resource requests\n        (`requests.cpu`, `requests.memory`, ephemeral storage). Over-requested\n        pods drive up billing regardless of whether the pod actively uses those\n        CPU cycles or memory.\n    -   **Standard Pricing**: Billed on provisioned node pool VMs (`e2`, `n4`,\n        `c3`, etc.). Idle nodes or multiple low-utilization dev clusters drive\n        excess infrastructure costs.\n    -   **Cluster Management Fee**: ~$0.10\u002Fhour per cluster applies to BOTH\n        Standard and Autopilot modes. The free tier waives it for one eligible\n        cluster per billing account.\n-   **Credits & Discounts Impact**: When analyzing `cost` versus\n    `cost_before_credits`, note that Committed Use Discounts (CUDs) and Spot VMs\n    appear as credits or reduced rate charges in the billing export.\n-   **Tools & Syntax**: BigQuery CLI (`bq`) is preferred. When writing Standard\n    SQL queries, use a dot (`.`) instead of a colon (`:`) to separate the\n    project ID and dataset name (`{project_id}.{dataset_name}.{table_name}`).\n-   **Defaults**: Assume last 30 days, row limit 10, ordering by cost descending\n    (`ORDER BY cost DESC`), unless specified otherwise.\n\n## Live Cluster & Cost Monitoring\n\nUse read-only CLI commands to inspect current cluster budgets, node utilization,\nand pod resource consumption vs. requests:\n\n```bash\n# View billing budgets for an account (requires Cost Management API)\ngcloud billing budgets list --billing-account={billing_account} --quiet\n\n# View live node resource utilization across the cluster\nkubectl top nodes\n\n# View pod resource usage across namespaces (compare against requested limits to diagnose waste)\nkubectl top pods --all-namespaces --containers\n```\n\n> **Warning — cluster mutation, not read-only:** Enabling GKE cost allocation\n> modifies the cluster. Get explicit user confirmation before running it, and\n> note that namespace\u002Fworkload labels populate in the billing export only from\n> enablement onward (no historical backfill).\n>\n> ```bash\n> gcloud container clusters update {cluster_name} \\\n>     --enable-cost-allocation \\\n>     --region {region}\n> ```\n\n## Applying Cost Optimizations\n\nTo apply rightsizing changes based on analysis (such as setting up `VPA`\nrecommendation mode, adjusting CPU\u002Fmemory to `P95 * 1.2`, configuring Spot VMs\nvia `nodeSelector` or `ComputeClass`, enforcing `ResourceQuotas`, or selecting\nmachine types and CUDs), use the **`gke-cost-optimization`** skill.\n\n## BigQuery Query Templates\n\nReady-to-adapt `bq query` templates — single workload cost, per-workload\nper-cluster breakdown, per-namespace breakdown — with the placeholder policy\nand defaults (30 days, `LIMIT 10`, `ORDER BY cost DESC`) are in\n[references\u002Fbilling-queries.md](references\u002Fbilling-queries.md). All parameters\n(dataset, table, project, cluster, etc.) must be replaced with user values.\n\nNote: Checking that the `goog-k8s-cluster-name` label exists scopes the total\nbilling data specifically to GKE costs.\n","# GKE Cost Analysis\n\nThis skill provides guidance on answering natural language questions about\nGKE-related costs, billing reports, and utilization analysis.\n\n## Attribution\n\n**MUST READ**: Before executing any `gcloud`, REST API, or MCP command, you\nMUST read [Usage Attribution](references\u002Fattribution.md). For commands executed\ndirectly in the terminal (never in generated scripts, Terraform, or user code),\nprefix `gcloud` with\n`CLOUDSDK_METRICS_REQUEST_ATTRIBUTION=\"agent-skills\u002F1.0 (skill:gke-cost-analysis)\"`\nand append `agent-skills\u002F1.0 (skill:gke-cost-analysis)` to `User-Agent` headers.\n\n## Overview\n\nWhen users ask about GKE costs (e.g., \"What are my costs across projects?\",\n\"What's my most expensive namespace?\", \"Why is my cluster cost spiking?\"), use\nthis skill to provide a structured and expert response using BigQuery billing\nexports, cost allocation metadata, and live cluster metrics.\n\n## Instructions\n\nWhen handling a cost-related question:\n\n1.  **Provide a Direct Answer**: Address the specific cost question or\n    analytical request clearly and concisely.\n2.  **Explain BigQuery Integration**: Explain how to query BigQuery for\n    historical cost breakdown. Note that GKE costs originate from the GCP\n    Billing Detailed BigQuery Export (`gcp_billing_export_resource_v1_*`).\n3.  **Check & Verify Cost Allocation**: Explain that GKE Cost Allocation must be\n    enabled on the cluster (`--enable-cost-allocation`) for namespace, label,\n    and workload-level billing granularity. If queries return empty labels,\n    provide the `gcloud` command to enable it.\n4.  **Analyze Pricing Drivers & Utilization**: When diagnosing cost drivers,\n    explain whether the cluster is in Autopilot (billed by requested pod\n    CPU\u002Fmemory) or Standard mode (billed by underlying VM node size + control\n    plane fees), and compare live utilization (`kubectl top`) against\n    provisioned requests.\n5.  **Provide Actionable Commands\u002FQueries**: Provide concrete BigQuery CLI (`bq\n    query`) commands or read-only `gcloud`\u002F`kubectl` inspection commands. Prefer\n    `bq` over BigQuery Studio when available.\n\n## Key Points & Pricing Drivers\n\n-   **Data Source**: GKE costs come from GCP Billing Detailed BigQuery Export.\n    The user must provide the full path to their BigQuery table (dataset name\n    and table name containing the Billing Account ID).\n-   **Granularity Requirement**: GKE Cost Allocation\n    (`--enable-cost-allocation`) must be enabled on the cluster to populate\n    `goog-k8s-cluster-name`, `k8s-namespace`, `k8s-workload-name`, and\n    `k8s-workload-type` labels in BigQuery.\n-   **Autopilot vs. Standard Cost Drivers**:\n    -   **Autopilot Pricing**: Billed directly on pod resource requests\n        (`requests.cpu`, `requests.memory`, ephemeral storage). Over-requested\n        pods drive up billing regardless of whether the pod actively uses those\n        CPU cycles or memory.\n    -   **Standard Pricing**: Billed on provisioned node pool VMs (`e2`, `n4`,\n        `c3`, etc.). Idle nodes or multiple low-utilization dev clusters drive\n        excess infrastructure costs.\n    -   **Cluster Management Fee**: ~$0.10\u002Fhour per cluster applies to BOTH\n        Standard and Autopilot modes. The free tier waives it for one eligible\n        cluster per billing account.\n-   **Credits & Discounts Impact**: When analyzing `cost` versus\n    `cost_before_credits`, note that Committed Use Discounts (CUDs) and Spot VMs\n    appear as credits or reduced rate charges in the billing export.\n-   **Tools & Syntax**: BigQuery CLI (`bq`) is preferred. When writing Standard\n    SQL queries, use a dot (`.`) instead of a colon (`:`) to separate the\n    project ID and dataset name (`{project_id}.{dataset_name}.{table_name}`).\n-   **Defaults**: Assume last 30 days, row limit 10, ordering by cost descending\n    (`ORDER BY cost DESC`), unless specified otherwise.\n\n## Live Cluster & Cost Monitoring\n\nUse read-only CLI commands to inspect current cluster budgets, node utilization,\nand pod resource consumption vs. requests:\n\n```bash\n# View billing budgets for an account (requires Cost Management API)\ngcloud billing budgets list --billing-account={billing_account} --quiet\n\n# View live node resource utilization across the cluster\nkubectl top nodes\n\n# View pod resource usage across namespaces (compare against requested limits to diagnose waste)\nkubectl top pods --all-namespaces --containers\n```\n\n> **Warning — cluster mutation, not read-only:** Enabling GKE cost allocation\n> modifies the cluster. Get explicit user confirmation before running it, and\n> note that namespace\u002Fworkload labels populate in the billing export only from\n> enablement onward (no historical backfill).\n>\n> ```bash\n> gcloud container clusters update {cluster_name} \\\n>     --enable-cost-allocation \\\n>     --region {region}\n> ```\n\n## Applying Cost Optimizations\n\nTo apply rightsizing changes based on analysis (such as setting up `VPA`\nrecommendation mode, adjusting CPU\u002Fmemory to `P95 * 1.2`, configuring Spot VMs\nvia `nodeSelector` or `ComputeClass`, enforcing `ResourceQuotas`, or selecting\nmachine types and CUDs), use the **`gke-cost-optimization`** skill.\n\n## BigQuery Query Templates\n\nReady-to-adapt `bq query` templates — single workload cost, per-workload\nper-cluster breakdown, per-namespace breakdown — with the placeholder policy\nand defaults (30 days, `LIMIT 10`, `ORDER BY cost DESC`) are in\n[references\u002Fbilling-queries.md](references\u002Fbilling-queries.md). All parameters\n(dataset, table, project, cluster, etc.) must be replaced with user values.\n\nNote: Checking that the `goog-k8s-cluster-name` label exists scopes the total\nbilling data specifically to GKE costs.\n",{"name":5,"metadata":44,"description":7},{"version":45,"category":46},"1.0.1","CloudObservabilityAndMonitoring","main","bb9b3f464aae37af360d079c1d863524955b0363","skills\u002Fcloud\u002Fgke-cost-analysis",2005,"https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fskills","https:\u002F\u002Fgithub.com\u002Fgoogle","https:\u002F\u002Fopensource.google\u002F","Google ❤️ Open Source","2026-11-14 01:51:35",{"source":8,"skillName":5,"commands":57,"prompt":67,"zipAvailable":68},[58,61,64],{"tool":59,"command":60},"npx","npx skills add google\u002Fskills --skill gke-cost-analysis",{"tool":62,"command":63},"bunx","bunx skills add google\u002Fskills --skill gke-cost-analysis",{"tool":65,"command":66},"pnpm","pnpm dlx skills add google\u002Fskills --skill gke-cost-analysis","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fcloud\u002Fgke-cost-analysis\u002FSKILL.md",true,[70,76],{"path":71,"resourceType":72,"resourceTypeDesc":73,"sizeBytes":74,"sourceHtmlUrl":75},"references\u002Fattribution.md","REFERENCE","参考文档",1891,"https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fcloud\u002Fgke-cost-analysis\u002Freferences\u002Fattribution.md",{"path":77,"resourceType":72,"resourceTypeDesc":73,"sizeBytes":78,"sourceHtmlUrl":79},"references\u002Fbilling-queries.md",3565,"https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fcloud\u002Fgke-cost-analysis\u002Freferences\u002Fbilling-queries.md",[81,119,150,179,206,229],{"skillNo":82,"name":83,"nameZh":6,"description":84,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":85,"categories":86,"keywords":95,"publishedAt":39},"01M6998S2EZKD3GEJ7F943RZTE","sign-in-with-google-web","Implement, configure, and secure Sign In With Google (SiwG) using Google Identity Services (GIS \u002F `https:\u002F\u002Faccounts.google.com\u002Fgsi\u002Fclient`) across web architectures. Use when creating Google sign-in buttons, implementing Google One Tap with FedCM, integrating GIS in React\u002FNext.js\u002FAngular\u002FHTML, verifying ID tokens on backend runtimes (Python\u002FNode.js\u002FGo\u002FJava), enforcing Google Workspace domain restrictions (`hd`), securing client-side ID tokens via WebCrypto nonces or encrypted IndexedDB, embedding in cross-origin iframes via the Intermediate Iframe API (`https:\u002F\u002Faccounts.google.com\u002Fgsi\u002Fintermediate`), configuring Content Security Policy (CSP), COOP, and Permissions Policy (`identity-credentials-get`) headers, or handling sign-out and revocation. Don't use for legacy Google Sign-In (`gapi.auth2`), Google Cloud IAM service accounts, or Android\u002FiOS native Credential Manager.","https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fidentity\u002Fsign-in-with-google-web\u002FSKILL.md",[87,92],{"categoryNo":88,"categoryName":89,"taxonomyType":90,"taxonomyTypeDesc":91},"01JBSEEDCAT000000000000009","前端开发","SCENARIO","使用场景",{"categoryNo":93,"categoryName":94,"taxonomyType":90,"taxonomyTypeDesc":91},"01JBSEEDCAT000000000000010","后端与接口",[9,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118],"sign in with google web","sign","with","web","android","go","security","google workspace","google cloud","implement","policy","python","implementing","react","iam","permissions","buttons","secure","manager","identity","architectures","domain","runtimes",{"skillNo":120,"name":121,"nameZh":6,"description":122,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":123,"categories":124,"keywords":134,"publishedAt":39},"01M6998PHPDCAD684VW5WRG83D","dpop-adoption","Implement and debug OAuth 2.0 DPoP (RFC 9449) refresh token sender-constraining for WebCrypto, Node.js ES6, and browser runtimes integrating with Google's OAuth platform. Use when configuring non-extractable asymmetric key pairs (P-256), generating DPoP Proof JWTs for authorization code exchange and token refresh, or handling 400 use_dpop_nonce challenge retry loops at oauth2.googleapis.com\u002Ftoken. Don't use for unconstrained OAuth 2.0 flows (where refresh tokens are not bound to a client key pair), or for Google Cloud IAM \u002F service account authentication.","https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fidentity\u002Fdpop-adoption\u002FSKILL.md",[125,126,129],{"categoryNo":93,"categoryName":94,"taxonomyType":90,"taxonomyTypeDesc":91},{"categoryNo":127,"categoryName":128,"taxonomyType":90,"taxonomyTypeDesc":91},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":130,"categoryName":131,"taxonomyType":132,"taxonomyTypeDesc":133},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[135,136,9,104,137,138,139,140,141,142,110,143,144,145,146,147,148,115,118,149,38],"dpop adoption","adoption","es6","retry","authentication","flows","challenge","code","browser","loops","at","node","token","pair","platform",{"skillNo":151,"name":152,"nameZh":6,"description":153,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":154,"categories":155,"keywords":162,"publishedAt":39},"01M6998M72TC73EEAQH4XC7EXW","retrieving-developer-knowledge","Searches, retrieves, and synthesizes official Google developer documentation across Google Cloud, AI\u002FGemini, Android, Chrome, Web, Flutter, Go, Firebase, and other Google developer platforms. Integrates with the Developer Knowledge MCP server (search_documents, get_documents, answer_query) or the Developer Knowledge REST API fallback. Use when searching for gcloud CLI commands, API syntax, IAM permissions, official documentation, architectural comparisons, or product choice overviews. Don't use for local filesystem lookups or non-Google documentation.","https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fdevelopers\u002Fretrieving-developer-knowledge\u002FSKILL.md",[156,157,160,161],{"categoryNo":93,"categoryName":94,"taxonomyType":90,"taxonomyTypeDesc":91},{"categoryNo":158,"categoryName":159,"taxonomyType":90,"taxonomyTypeDesc":91},"01JBSEEDCAT000000000000021","资料检索与研究",{"categoryNo":127,"categoryName":128,"taxonomyType":90,"taxonomyTypeDesc":91},{"categoryNo":130,"categoryName":131,"taxonomyType":132,"taxonomyTypeDesc":133},[163,164,165,166,104,167,168,169,170,171,172,173,174,38,175,176,177,110,178,111],"retrieving developer knowledge","knowledge","developer","MCP","mcp server","official","developer documentation","get","search","local","choice","documents","query","api","across","documentation",{"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":185,"publishedAt":39},"01M6998J2CZEXS9BES9S3WWFKC","migrate-to-rust","Clones, analyzes, plans, and migrates legacy codebases (C++, Fortran, Java, Python, C, Shell) from a GitHub URL or local directory to a modern, high-performance, deterministic, 100% Safe Rust architecture, tracking live telemetry across every task bucket, test failure\u002Ffix cycle, and Profile-Guided Optimization (PGO) stage, and producing a first-person AI storytelling report and interactive HTML infographic. Use when migrating a GitHub repository or local codebase to Rust, porting legacy C++, Fortran, Python, or Java workloads to memory-safe Rust, designing Struct-of-Arrays (SoA) or SIMD Rust architectures, or optimizing Rust ports with LLVM PGO. Don't use for unrelated non-Rust refactoring or single-line syntax questions.","https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fdevelopers\u002Fmigrate-to-rust\u002FSKILL.md",[],[186,187,188,189,190,191,192,193,107,194,195,196,197,198,199,172,200,201,202,38,203,204,177,205],"migrate to rust","rust","migrate","github","memory","performance","directory","safe","ports","llvm","soa","cycle","porting","fix","arrays","infographic","high-performance","URL","architecture","unrelated",{"skillNo":207,"name":208,"nameZh":6,"description":209,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":210,"categories":211,"keywords":215,"publishedAt":39},"01M6998GCC3K29WZ82KXMB9E02","finding-google-skills","Google platform decision and setup guidance, loaded on demand from Google's skill catalog. Use when a developer is choosing or setting up part of their stack, such as where to run a service, a database, storage, messaging, authentication, analytics, ads, or AI model serving, and a Google product is a reasonable candidate - whether or not a vendor is named - or when a request names a Google product or API. Brings in the matching Google skill so the answer can weigh Google options, their trade-offs, and when they are not the right fit. Skip when the stack is already settled on another provider and no Google product is named, or the task involves no platform choice.","https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fdevelopers\u002Ffinding-google-skills\u002FSKILL.md",[212,213,214],{"categoryNo":93,"categoryName":94,"taxonomyType":90,"taxonomyTypeDesc":91},{"categoryNo":127,"categoryName":128,"taxonomyType":90,"taxonomyTypeDesc":91},{"categoryNo":130,"categoryName":131,"taxonomyType":132,"taxonomyTypeDesc":133},[9,216,217,218,219,149,220,221,222,34,223,139,224,225,226,173,28,227,38,228,176],"finding google skills","storage","as","messaging","model","trade-offs","provider","fit","catalog","up","decision","database","candidate",{"skillNo":230,"name":231,"nameZh":6,"description":232,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":233,"categories":234,"keywords":237,"publishedAt":39},"01M6998DWNHTH0BS6W1CY8ZXMP","workload-manager-basics","Use this skill to manage Google Cloud Workload Manager evaluations, rules, scanned resources, and validation results by using public client libraries and the REST API. Use when you need to inspect workload best-practice rules, create and run evaluations for Google Cloud general best practices, SAP, SQL Server, or custom organizational rules, review violations, export results to BigQuery, or automate Workload Manager through client libraries because no service-specific public CLI or MCP server is available. Don't use for general Google Compute Engine instance management, VPC configuration, or standard IAM auditing.","https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fcloud\u002Fworkload-manager-basics\u002FSKILL.md",[235,236],{"categoryNo":93,"categoryName":94,"taxonomyType":90,"taxonomyTypeDesc":91},{"categoryNo":127,"categoryName":128,"taxonomyType":90,"taxonomyTypeDesc":91},[238,239,114,240,9,166,241,104,167,242,243,244,245,38,246,176,110,247,248,249,250],"workload manager basics","workload","basics","cli","review","vpc","resources","inspect","you","create","libraries","server","run"]