[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M69916Y18RZDFYQ2S7WKMVY2":3,"skill-same:01M69916Y18RZDFYQ2S7WKMVY2":95},{"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":23,"publishedAt":45,"linkOnly":46,"markdownContent":47,"markdownBody":48,"frontMatter":49,"refName":54,"commitSha":55,"skillDirectory":56,"forksCount":57,"repositoryHtmlUrl":58,"repositoryHomepageUrl":6,"ownerHtmlUrl":59,"ownerBlogUrl":60,"ownerDescription":61,"updatedAt":62,"install":63,"resources":76},"01M69916Y18RZDFYQ2S7WKMVY2","cloud-run-alert-configuration",null,"Configures best-practice, high-signal alerting policies for Cloud Run resources on Google Cloud (services, jobs, and worker pools) based on seasoned SRE practices. Use when analyzing, recommending, writing, or deploying Terraform PromQL alerting policies to monitor Cloud Run error rates (4xx\u002F5xx), request latency, container instance saturation (warning\u002Fcritical), container CPU\u002Fmemory utilization and allocation, billable instance time, job execution status, and worker pool queue backlog. Don't use for GKE workloads (use gke-alert-configuration) or Compute Engine VMs.","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\u002Fcloud-run-alert-configuration\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000011","运维与部署","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,9],"cloud run","cloud run alert configuration","run","cloud","alert","configuration","when","writing","promql","CPU","error","resources","critical","worker","time","saturation","sre","alerting","memory","google cloud","gcloud","2026-11-10 10:12:30",false,"---\nname: cloud-run-alert-configuration\nmetadata:\n  version: \"1.0.3\"\n  category: Serverless\ndescription: >-\n  Configures best-practice, high-signal alerting policies for Cloud Run\n  resources on Google Cloud (services, jobs, and worker pools) based on seasoned\n  SRE practices. Use\n  when analyzing, recommending, writing, or deploying Terraform PromQL alerting\n  policies to monitor Cloud Run error rates (4xx\u002F5xx), request latency, container instance\n  saturation (warning\u002Fcritical), container CPU\u002Fmemory utilization and allocation, billable\n  instance time, job execution status, and worker pool queue backlog. Don't use for\n  GKE workloads (use gke-alert-configuration) or Compute Engine VMs.\nallowed-tools: terraform gcloud\n---\n\n# Cloud Run Alert Configuration\n\nProduction-grade observability for Cloud Run using Terraform and PromQL\n(Cloud Monitoring). Grounded in SRE practices, this skill focuses strictly on\nactionable user impact and scaling bounds.\n\n--------------------------------------------------------------------------------\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:cloud-run-alert-configuration)\"`\nand append `agent-skills\u002F1.0 (skill:cloud-run-alert-configuration)` to `User-Agent` headers.\n\n## CRITICAL RULES\n\n*   **Prompt-First Fast Path (Skip Discovery When Named)**:\n    *   **If the user prompt explicitly specifies the target Cloud Run service, job, or worker pool name** (e.g., `'video-encoder'`, `'nightly-reconciliation'`, `'web-frontend'`, `'catalog-service'`, `'api-gateway'`, `'order-processor'`), **SKIP all workspace `.tf` file scanning (`find_by_name`, `code_search`, `list_dir`) and `gcloud` CLI discovery commands entirely**.\n    *   Do NOT run `gcloud`, `terraform`, or file search tools when the target name is already provided in the prompt. Instead, parameterize the project ID (`variable \"scoping_project_id\" { default = \"my-gcp-project\" }`) and target resource name in Terraform variables and proceed immediately to **Step 2 (Configure Alerts)**.\n*   **Autonomous Discovery (Only When Target Name is Omitted)**:\n    *   **Never Scan Root Monorepo or Unbounded Directories**: Never run `find_by_name` or `ls` across root workspace directories.\n    *   **Config First**: Only if the prompt omits the resource name, check `.tf` files in the immediate working directory for `google_cloud_run_v2_service`, `google_cloud_run_service`, or `google_cloud_run_v2_job`.\n    *   **CLI Second (Graceful Fallback)**: Only if unconfigured in prompt or local `.tf` files, attempt `gcloud config get-value project` and `gcloud run services list`. If any `gcloud` command fails (e.g., auth or metadata errors) or `terraform` is missing, immediately stop running CLI commands and output parameterized HCL using explicit variable defaults.\n*   **Workload Routing**: Always classify the workload target and follow its\n    specific reference guide:\n    *   For HTTP Services follow [services.md](references\u002Fservices.md)\n    *   For Cloud Run Jobs follow [jobs.md](references\u002Fjobs.md)\n    *   For Worker Pools follow [worker_pools.md](references\u002Fworker_pools.md)\n*   **Explicit Defaults & User Overrides**:\n    *   Always use explicit defaults for all constants specified in\n        the target workload's reference file (SLO targets, latency thresholds,\n        SLAs, saturation ceilings, rate guards).\n    *   State the defaults being applied in the final summary output and clearly\n        notify the user that any default constant can be customized or\n        overridden via Terraform variables or prompt input.\n*   **Metric Scope Centralization**: Parameterize `project = var.scoping_project_id` in all Terraform `google_monitoring_alert_policy` resources so the policy can target either a single project or a centralized Cloud Monitoring Metrics Scope.\n*   **PromQL `duration` (Retest Window) Rules**:\n    *   **Lookbacks $\\le$ 25h**: Set `duration = \"300s\"` (5m buffer) to absorb\n        transient blips and scale-up lag (except immediate job failure alerts\n        which use `duration = \"0s\"`).\n    *   **Lookbacks $> 25$h** (e.g. 3d\u002F7d Slow Burn): **Omit `duration`\n        entirely** (or set to `0s`). Cloud Monitoring rejects PromQL queries\n        with `duration` set on lookbacks >25h (`INVALID_ARGUMENT`).\n*   **Terraform Standards & Mandatory Labels**:\n    *   Output clean, complete `.tf` configurations using `google_monitoring_alert_policy` and `condition_prometheus_query_language` directly in your response.\n    *   **Mandatory User Labels**: Every `google_monitoring_alert_policy` resource MUST include a `user_labels` block containing:\n        ```hcl\n        user_labels = {\n          created-with-google-skill = \"cloud-run-alert-configuration\"\n        }\n        ```\n    *   Include `alert_strategy { auto_close = \"604800s\" }` and parameterize `notification_channels = var.notification_channels`.\n\n## WORKFLOW STEPS\n\n### 1. Discovery & Target Identification\n\n*   **Fast Path (Target Named in Prompt)**: If the user prompt names the target Cloud Run service, job, or worker pool, **skip all discovery commands and file searches** and proceed directly to **Step 2**.\n*   **Discovery Fallback (Target Unnamed)**: Only if no resource name is provided in the prompt, check local `.tf` files or run `gcloud` to identify the target workload type and name. If `gcloud` auth fails, fall back immediately to default Terraform variables (`var.scoping_project_id`).\n\n### 2. Configure Alerts\n\n*   Route to the corresponding guide to generate the alert policies:\n    *   **HTTP Services**: Open [services.md](references\u002Fservices.md). Apply the\n        requested alerting policy or standard suite covering availability SLOs (5xx), request\n        latency (P95\u002FP99), client errors (4xx), container instance saturation,\n        container CPU\u002Fmemory utilization, traffic anomalies (drop\u002Fsurge), and billable\n        instance time.\n    *   **Batch Jobs**: Open [jobs.md](references\u002Fjobs.md). Apply immediate job\n        execution failure alerts (`duration = \"0s\"`).\n    *   **Worker Pools**: Open [worker_pools.md](references\u002Fworker_pools.md).\n        Apply the 4-policy standard suite (Task Success SLO Fast\u002FSlow Burn,\n        Backlog ETD, Message Age SLA).\n\n### 3. Terraform Generation & Review\n\n*   Provide the complete HCL configuration in your response with explicitly parameterized defaults and the mandatory `user_labels` block (`created-with-google-skill = \"cloud-run-alert-configuration\"`).\n*   State the applied defaults and remind the user of their ability to override\n    any constant.\n*   Provide a clear plain-English breakdown of the PromQL logic and triggering\n    thresholds.\n\n--------------------------------------------------------------------------------\n\n## Additional Resources\n\n*   [Cloud Run Documentation](https:\u002F\u002Fdocs.cloud.google.com\u002Frun\u002Fdocs\u002Foverview\u002Fwhat-is-cloud-run.md.txt)\n*   [Cloud Monitoring PromQL Documentation](https:\u002F\u002Fdocs.cloud.google.com\u002Fmonitoring\u002Fpromql\u002Fpromql-in-monitoring.md.txt)\n*   [Google Cloud Alerting Policies in Terraform](https:\u002F\u002Fdocs.cloud.google.com\u002Fmonitoring\u002Falerts\u002Fterraform.md.txt)\n*   [Google SRE Workbook: Alerting on SLOs](https:\u002F\u002Fsre.google\u002Fworkbook\u002Falerting-on-slos\u002F)\n","# Cloud Run Alert Configuration\n\nProduction-grade observability for Cloud Run using Terraform and PromQL\n(Cloud Monitoring). Grounded in SRE practices, this skill focuses strictly on\nactionable user impact and scaling bounds.\n\n--------------------------------------------------------------------------------\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:cloud-run-alert-configuration)\"`\nand append `agent-skills\u002F1.0 (skill:cloud-run-alert-configuration)` to `User-Agent` headers.\n\n## CRITICAL RULES\n\n*   **Prompt-First Fast Path (Skip Discovery When Named)**:\n    *   **If the user prompt explicitly specifies the target Cloud Run service, job, or worker pool name** (e.g., `'video-encoder'`, `'nightly-reconciliation'`, `'web-frontend'`, `'catalog-service'`, `'api-gateway'`, `'order-processor'`), **SKIP all workspace `.tf` file scanning (`find_by_name`, `code_search`, `list_dir`) and `gcloud` CLI discovery commands entirely**.\n    *   Do NOT run `gcloud`, `terraform`, or file search tools when the target name is already provided in the prompt. Instead, parameterize the project ID (`variable \"scoping_project_id\" { default = \"my-gcp-project\" }`) and target resource name in Terraform variables and proceed immediately to **Step 2 (Configure Alerts)**.\n*   **Autonomous Discovery (Only When Target Name is Omitted)**:\n    *   **Never Scan Root Monorepo or Unbounded Directories**: Never run `find_by_name` or `ls` across root workspace directories.\n    *   **Config First**: Only if the prompt omits the resource name, check `.tf` files in the immediate working directory for `google_cloud_run_v2_service`, `google_cloud_run_service`, or `google_cloud_run_v2_job`.\n    *   **CLI Second (Graceful Fallback)**: Only if unconfigured in prompt or local `.tf` files, attempt `gcloud config get-value project` and `gcloud run services list`. If any `gcloud` command fails (e.g., auth or metadata errors) or `terraform` is missing, immediately stop running CLI commands and output parameterized HCL using explicit variable defaults.\n*   **Workload Routing**: Always classify the workload target and follow its\n    specific reference guide:\n    *   For HTTP Services follow [services.md](references\u002Fservices.md)\n    *   For Cloud Run Jobs follow [jobs.md](references\u002Fjobs.md)\n    *   For Worker Pools follow [worker_pools.md](references\u002Fworker_pools.md)\n*   **Explicit Defaults & User Overrides**:\n    *   Always use explicit defaults for all constants specified in\n        the target workload's reference file (SLO targets, latency thresholds,\n        SLAs, saturation ceilings, rate guards).\n    *   State the defaults being applied in the final summary output and clearly\n        notify the user that any default constant can be customized or\n        overridden via Terraform variables or prompt input.\n*   **Metric Scope Centralization**: Parameterize `project = var.scoping_project_id` in all Terraform `google_monitoring_alert_policy` resources so the policy can target either a single project or a centralized Cloud Monitoring Metrics Scope.\n*   **PromQL `duration` (Retest Window) Rules**:\n    *   **Lookbacks $\\le$ 25h**: Set `duration = \"300s\"` (5m buffer) to absorb\n        transient blips and scale-up lag (except immediate job failure alerts\n        which use `duration = \"0s\"`).\n    *   **Lookbacks $> 25$h** (e.g. 3d\u002F7d Slow Burn): **Omit `duration`\n        entirely** (or set to `0s`). Cloud Monitoring rejects PromQL queries\n        with `duration` set on lookbacks >25h (`INVALID_ARGUMENT`).\n*   **Terraform Standards & Mandatory Labels**:\n    *   Output clean, complete `.tf` configurations using `google_monitoring_alert_policy` and `condition_prometheus_query_language` directly in your response.\n    *   **Mandatory User Labels**: Every `google_monitoring_alert_policy` resource MUST include a `user_labels` block containing:\n        ```hcl\n        user_labels = {\n          created-with-google-skill = \"cloud-run-alert-configuration\"\n        }\n        ```\n    *   Include `alert_strategy { auto_close = \"604800s\" }` and parameterize `notification_channels = var.notification_channels`.\n\n## WORKFLOW STEPS\n\n### 1. Discovery & Target Identification\n\n*   **Fast Path (Target Named in Prompt)**: If the user prompt names the target Cloud Run service, job, or worker pool, **skip all discovery commands and file searches** and proceed directly to **Step 2**.\n*   **Discovery Fallback (Target Unnamed)**: Only if no resource name is provided in the prompt, check local `.tf` files or run `gcloud` to identify the target workload type and name. If `gcloud` auth fails, fall back immediately to default Terraform variables (`var.scoping_project_id`).\n\n### 2. Configure Alerts\n\n*   Route to the corresponding guide to generate the alert policies:\n    *   **HTTP Services**: Open [services.md](references\u002Fservices.md). Apply the\n        requested alerting policy or standard suite covering availability SLOs (5xx), request\n        latency (P95\u002FP99), client errors (4xx), container instance saturation,\n        container CPU\u002Fmemory utilization, traffic anomalies (drop\u002Fsurge), and billable\n        instance time.\n    *   **Batch Jobs**: Open [jobs.md](references\u002Fjobs.md). Apply immediate job\n        execution failure alerts (`duration = \"0s\"`).\n    *   **Worker Pools**: Open [worker_pools.md](references\u002Fworker_pools.md).\n        Apply the 4-policy standard suite (Task Success SLO Fast\u002FSlow Burn,\n        Backlog ETD, Message Age SLA).\n\n### 3. Terraform Generation & Review\n\n*   Provide the complete HCL configuration in your response with explicitly parameterized defaults and the mandatory `user_labels` block (`created-with-google-skill = \"cloud-run-alert-configuration\"`).\n*   State the applied defaults and remind the user of their ability to override\n    any constant.\n*   Provide a clear plain-English breakdown of the PromQL logic and triggering\n    thresholds.\n\n--------------------------------------------------------------------------------\n\n## Additional Resources\n\n*   [Cloud Run Documentation](https:\u002F\u002Fdocs.cloud.google.com\u002Frun\u002Fdocs\u002Foverview\u002Fwhat-is-cloud-run.md.txt)\n*   [Cloud Monitoring PromQL Documentation](https:\u002F\u002Fdocs.cloud.google.com\u002Fmonitoring\u002Fpromql\u002Fpromql-in-monitoring.md.txt)\n*   [Google Cloud Alerting Policies in Terraform](https:\u002F\u002Fdocs.cloud.google.com\u002Fmonitoring\u002Falerts\u002Fterraform.md.txt)\n*   [Google SRE Workbook: Alerting on SLOs](https:\u002F\u002Fsre.google\u002Fworkbook\u002Falerting-on-slos\u002F)\n",{"name":5,"metadata":50,"description":7,"allowed-tools":53},{"version":51,"category":52},"1.0.3","Serverless","terraform gcloud","main","bb9b3f464aae37af360d079c1d863524955b0363","skills\u002Fcloud\u002Fcloud-run-alert-configuration",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":64,"prompt":74,"zipAvailable":75},[65,68,71],{"tool":66,"command":67},"npx","npx skills add google\u002Fskills --skill cloud-run-alert-configuration",{"tool":69,"command":70},"bunx","bunx skills add google\u002Fskills --skill cloud-run-alert-configuration",{"tool":72,"command":73},"pnpm","pnpm dlx skills add google\u002Fskills --skill cloud-run-alert-configuration","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fcloud\u002Fcloud-run-alert-configuration\u002FSKILL.md",true,[77,83,87,91],{"path":78,"resourceType":79,"resourceTypeDesc":80,"sizeBytes":81,"sourceHtmlUrl":82},"references\u002Fattribution.md","REFERENCE","参考文档",1927,"https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fcloud\u002Fcloud-run-alert-configuration\u002Freferences\u002Fattribution.md",{"path":84,"resourceType":79,"resourceTypeDesc":80,"sizeBytes":85,"sourceHtmlUrl":86},"references\u002Fjobs.md",3332,"https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fcloud\u002Fcloud-run-alert-configuration\u002Freferences\u002Fjobs.md",{"path":88,"resourceType":79,"resourceTypeDesc":80,"sizeBytes":89,"sourceHtmlUrl":90},"references\u002Fservices.md",28636,"https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fcloud\u002Fcloud-run-alert-configuration\u002Freferences\u002Fservices.md",{"path":92,"resourceType":79,"resourceTypeDesc":80,"sizeBytes":93,"sourceHtmlUrl":94},"references\u002Fworker_pools.md",12326,"https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fcloud\u002Fcloud-run-alert-configuration\u002Freferences\u002Fworker_pools.md",[96,131,162,191,217,242],{"skillNo":97,"name":98,"nameZh":6,"description":99,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":100,"categories":101,"keywords":108,"publishedAt":45},"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",[102,105],{"categoryNo":103,"categoryName":104,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000009","前端开发",{"categoryNo":106,"categoryName":107,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000010","后端与接口",[9,109,110,111,112,113,114,115,116,43,117,118,119,120,121,122,123,124,125,126,127,128,129,130],"sign in with google web","sign","with","web","android","go","security","google workspace","implement","policy","python","implementing","react","iam","permissions","buttons","secure","manager","identity","architectures","domain","runtimes",{"skillNo":132,"name":133,"nameZh":6,"description":134,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":135,"categories":136,"keywords":146,"publishedAt":45},"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",[137,138,141],{"categoryNo":106,"categoryName":107,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":139,"categoryName":140,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":142,"categoryName":143,"taxonomyType":144,"taxonomyTypeDesc":145},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[147,148,9,43,149,150,151,152,153,154,122,155,156,157,158,159,160,127,130,161,30],"dpop adoption","adoption","es6","retry","authentication","flows","challenge","code","browser","loops","at","node","token","pair","platform",{"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":174,"publishedAt":45},"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",[168,169,172,173],{"categoryNo":106,"categoryName":107,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":170,"categoryName":171,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000021","资料检索与研究",{"categoryNo":139,"categoryName":140,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":142,"categoryName":143,"taxonomyType":144,"taxonomyTypeDesc":145},[175,176,177,178,43,179,180,181,182,183,184,185,186,30,187,188,189,122,190,123],"retrieving developer knowledge","knowledge","developer","MCP","mcp server","official","developer documentation","get","search","local","choice","documents","query","api","across","documentation",{"skillNo":192,"name":193,"nameZh":6,"description":194,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":195,"categories":196,"keywords":197,"publishedAt":45},"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",[],[198,199,200,201,42,202,203,204,119,205,206,207,208,209,210,184,211,212,213,30,214,215,189,216],"migrate to rust","rust","migrate","github","performance","directory","safe","ports","llvm","soa","cycle","porting","fix","arrays","infographic","high-performance","URL","architecture","unrelated",{"skillNo":218,"name":219,"nameZh":6,"description":220,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":221,"categories":222,"keywords":226,"publishedAt":45},"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",[223,224,225],{"categoryNo":106,"categoryName":107,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":139,"categoryName":140,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":142,"categoryName":143,"taxonomyType":144,"taxonomyTypeDesc":145},[9,227,228,229,230,161,231,232,233,234,235,151,236,237,238,185,239,240,30,241,188],"finding google skills","storage","as","messaging","model","trade-offs","provider","answer","fit","catalog","up","decision","use","database","candidate",{"skillNo":243,"name":244,"nameZh":6,"description":245,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":246,"categories":247,"keywords":250,"publishedAt":45},"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",[248,249],{"categoryNo":106,"categoryName":107,"taxonomyType":21,"taxonomyTypeDesc":22},{"categoryNo":139,"categoryName":140,"taxonomyType":21,"taxonomyTypeDesc":22},[251,252,126,253,9,178,254,43,179,255,256,35,257,30,258,188,122,259,260,261,26],"workload manager basics","workload","basics","cli","review","vpc","inspect","you","create","libraries","server"]