[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M69937319KXABPP31MBSN31V":3,"skill-same:01M69937319KXABPP31MBSN31V":76},{"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},"01M69937319KXABPP31MBSN31V","gke-ai-troubleshooting-tpu-reservation-stockout",null,"Diagnose and resolve cluster-wide GKE TPU node pool creation or scale-up failures caused by Compute Engine reservation stockouts (GCE_STOCKOUT, ZONE_RESOURCE_POOL_EXHAUSTED) when existing unhealthy or NotReady TPU node pools in the cluster have node auto-repair disabled and hold reserved TPU capacity. Use when TPU node pool creation or scale-up fails with GCE_STOCKOUT, ZONE_RESOURCE_POOL_EXHAUSTED, or ZONE_RESOURCE_POOL_EXHAUSTED_WITH_DETAILS despite having a specific Compute Engine TPU reservation. Don't use for general pod scheduling without a TPU reservation or workload-level container crashes.","google\u002Fskills","google","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F1342004?v=4","01M698VYEFDM0VJBZDYYJ2T83S","Google","01M698WR0H76ENHE587T9EJT89",24044,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fcloud\u002Fgke-ai-troubleshooting-tpu-reservation-stockout\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"gke ai troubleshooting tpu reservation stockout","tpu","gke","troubleshooting","when","containers","Existing","for","cluster","creation","repair","scheduling","general","up","container","auto","use","node","diagnose","workload","2026-11-10 10:12:30",false,"---\nname: gke-ai-troubleshooting-tpu-reservation-stockout\ndescription: >-\n  Diagnose and resolve cluster-wide GKE TPU node pool creation or scale-up\n  failures caused by Compute Engine reservation stockouts (GCE_STOCKOUT,\n  ZONE_RESOURCE_POOL_EXHAUSTED) when existing unhealthy or NotReady TPU node\n  pools in the cluster have node auto-repair disabled and hold reserved TPU\n  capacity. Use when TPU node pool creation or scale-up fails with GCE_STOCKOUT,\n  ZONE_RESOURCE_POOL_EXHAUSTED, or ZONE_RESOURCE_POOL_EXHAUSTED_WITH_DETAILS\n  despite having a specific Compute Engine TPU reservation. Don't use for\n  general pod scheduling without a TPU reservation or workload-level container\n  crashes.\nmetadata:\n  version: \"1.0.1\"\n  category: Containers\n---\n\n# Troubleshoot GKE TPU reservation stockouts caused by leaked node pool capacity\n\nUse this skill to diagnose and resolve GKE TPU node pool creation or scale-up\nfailures that fail with `GCE_STOCKOUT`, `ZONE_RESOURCE_POOL_EXHAUSTED`, or\n`ZONE_RESOURCE_POOL_EXHAUSTED_WITH_DETAILS` (or queue due to lack of capacity)\neven though they target a specific Compute Engine TPU reservation.\n\nIf node auto-repair is disabled on an existing TPU node pool, GKE doesn't repair\nits nodes when they become `NotReady`. While their VMs are still running, they\nkeep consuming slots in the reservation (`inUseCount` is the number of running\ninstances that consume the reservation). Per\n[Ensure reservation availability](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Ftpus.md.txt),\nthe reservation must have sufficient available TPU chips at the time of node\npool creation, and per\n[Multi-host TPU slice node pools](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fconcepts\u002Ftpus.md.txt),\nif GKE is unable to deploy one node in a slice, no nodes in the TPU slice node\npool are deployed. When the free slots in the reservation\n(`specificReservation.count - specificReservation.inUseCount`; see\n[Consumable instances in a reservation](https:\u002F\u002Fdocs.cloud.google.com\u002Fcompute\u002Fdocs\u002Finstances\u002Freservations-view.md.txt))\nare fewer than the number of nodes that the new TPU node pool needs, creation\nfails with `GCE_STOCKOUT` or `ZONE_RESOURCE_POOL_EXHAUSTED` (or queues due to\nlack of capacity).\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-ai-troubleshooting-tpu-reservation-stockout)\"`\nand append `agent-skills\u002F1.0 (skill:gke-ai-troubleshooting-tpu-reservation-stockout)` to `User-Agent` headers.\n\n## Prerequisites\n\n- **Required IAM Roles**:\n  - Logs Viewer (`roles\u002Flogging.viewer`): Query Cloud Audit Logs in Cloud\n    Logging.\n  - Monitoring Viewer (`roles\u002Fmonitoring.viewer`): Query GKE node readiness\n    metrics in Cloud Monitoring.\n  - Kubernetes Engine Viewer (`roles\u002Fcontainer.viewer`): Inspect GKE node pools\n    (`management.autoRepair`), cluster operations, and node conditions.\n  - Compute Viewer (`roles\u002Fcompute.viewer`): Inspect Compute Engine reservation\n    utilization (`specificReservation.inUseCount` vs\n    `specificReservation.count`), consuming instances, and VM labels (including\n    in the reservation's owner project if using a shared reservation).\n  - For remediation (`[High Risk]` steps): Kubernetes Engine Cluster Admin\n    (`roles\u002Fcontainer.clusterAdmin`)\n- **API Enablement & Billing**:\n  - Ensure the target project has an active Google Cloud billing account\n    attached: `gcloud billing projects describe {project_id}`.\n  - Enable required APIs: `container.googleapis.com`, `compute.googleapis.com`,\n    `logging.googleapis.com`, and `monitoring.googleapis.com`.\n- **CLI & Authentication Setup**:\n  - Install Google Cloud SDK (`gcloud`) and `kubectl`:\n    https:\u002F\u002Fcloud.google.com\u002Fsdk\u002Fdocs\u002Finstall.\n- **Cluster mode**: This skill applies to Standard clusters. Autopilot clusters\n  always auto-repair nodes, and you can't turn this off (see\n  [Settings for Autopilot and Standard](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Fnode-auto-repair.md.txt)).\n- **Reference Documentation**:\n  - [Auto-repair nodes](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Fnode-auto-repair.md.txt)\n    (Sections: \"Settings for Autopilot and Standard\", \"Repair criteria\", \"Node\n    repair process\", \"Verify node auto-repair is enabled for a Standard node\n    pool\", \"Node auto repair in TPU slice nodes\", \"Enable auto-repair for an\n    existing Standard node pool\", \"Get information about recent automated repair\n    events\")\n  - [Troubleshoot GKE Standard node pools](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Ftroubleshooting\u002Fnode-pools.md.txt)\n    (Sections: \"Issue: Node pool creation fails due to insufficient resources\")\n  - [Troubleshoot TPUs in GKE](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Ftroubleshooting\u002Ftpus.md.txt)\n    (Sections: \"How GKE handles capacity issues\", \"Insufficient TPU resources to\n    satisfy the TPU request\")\n  - [About TPUs in GKE](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fconcepts\u002Ftpus.md.txt)\n    (Sections: \"Multi-host TPU slice node pools\")\n  - [Consuming reserved zonal resources](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Fconsuming-reservations.md.txt)\n    (Sections: \"Consuming a specific shared reservation\")\n  - [About reservations](https:\u002F\u002Fdocs.cloud.google.com\u002Fcompute\u002Fdocs\u002Finstances\u002Freservations-overview.md.txt)\n    (Sections: \"How reservations work\")\n  - [View reservations or future reservation requests](https:\u002F\u002Fdocs.cloud.google.com\u002Fcompute\u002Fdocs\u002Finstances\u002Freservations-view.md.txt)\n    (Sections: \"Limitations\", \"View reservations\", \"Consumable instances in a\n    reservation\", \"View a list of instances that are consuming a reservation\")\n  - [Organize resources using labels](https:\u002F\u002Fdocs.cloud.google.com\u002Fcompute\u002Fdocs\u002Flabeling-resources.md.txt)\n    (Sections: \"View labels\")\n  - [Create and manage cluster and node pool labels](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Fcreating-managing-labels.md.txt)\n    (Sections: \"Automatically applied labels\")\n  - [Deploy TPU workloads in GKE Standard](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Ftpus.md.txt)\n    (Sections: \"Ensure reservation availability\", \"Monitor health metrics for\n    TPU nodes and node pools\", \"Configure auto repair for TPU slice nodes\")\n  - [Add and manage node pools](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Fnode-pools.md.txt)\n    (Sections: \"Delete a node pool\")\n\n> **Read-only rule**: Run read-only diagnostic commands only. Never drain,\n> delete, or re-create nodes, or run any other command that changes the cluster.\n> Give the user any fix to apply themselves.\n\nWhen you recommend a fix, link the doc section that describes it.\n\n---\n\n## Diagnostic workflow\n\n### Step 0: Collect context and set the investigation window\n\nIdentify the following environment parameters from the user prompt or cluster\ncontext:\n- `{project_id}`, `{cluster_name}`, `{location}`, `{failing_nodepool_name}`,\n  `{reservation_name}`, `{reservation_project_id}` (the project that owns\n  `{reservation_name}`, which defaults to `{project_id}` for a single-project\n  reservation or is the owner project for a shared reservation; see\n  [Consuming a specific shared reservation](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Fconsuming-reservations.md.txt)),\n  `{zone}` (the zone of the reservation), and `{issue_time}`.\n- **Time window**: By default, query a 60-minute window `[{issue_time} - 30m,\n  {issue_time} + 30m]` (`{start_time}` to `{end_time}`).\n\n---\n\n### Step 1: Confirm the stockout error and reservation utilization `[Low Risk]`\n\n1. **Check Cloud Audit Logs and GKE operations for stockout or capacity\n   errors**:\n   - Run the query in\n     [Issue: Node pool creation fails due to insufficient resources](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Ftroubleshooting\u002Fnode-pools.md.txt)\n     across `[{start_time}, {end_time}]` and look for the documented error\n     messages, such as `ZONE_RESOURCE_POOL_EXHAUSTED` or\n     `ZONE_RESOURCE_POOL_EXHAUSTED_WITH_DETAILS`.\n   - Per\n     [Insufficient TPU resources to satisfy the TPU request](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Ftroubleshooting\u002Ftpus.md.txt),\n     TPU errors can also contain `GCE_STOCKOUT`.\n   - Per\n     [How GKE handles capacity issues](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Ftroubleshooting\u002Ftpus.md.txt),\n     GKE sometimes queues a TPU node pool creation request instead of failing it\n     immediately, surfacing a `... cannot be created ... due to lack of\n     capacity` message instead of `GCE_STOCKOUT`. List the node pool creation\n     operation with `gcloud container operations list`\n     (`--filter=\"operationType=CREATE_NODE_POOL\"`).\n2. **Check Compute Engine reservation utilization**:\n   - Per\n     [Limitations](https:\u002F\u002Fdocs.cloud.google.com\u002Fcompute\u002Fdocs\u002Finstances\u002Freservations-view.md.txt),\n     query shared reservations in the owner project where they were created\n     (`{reservation_project_id}`).\n   - Follow the\n     [View reservations](https:\u002F\u002Fdocs.cloud.google.com\u002Fcompute\u002Fdocs\u002Finstances\u002Freservations-view.md.txt)\n     section to run `gcloud compute reservations describe {reservation_name}\n     --zone={zone} --project={reservation_project_id}` or `gcloud compute\n     reservations list --project={reservation_project_id}`, and compare\n     `specificReservation.inUseCount` against `specificReservation.count`.\n\n#### Interpret the results\n- Don't suggest deleting any node pool until you have identified which existing\n  VMs and node pools hold the reserved capacity (Step 2).\n- **Stockout confirmed**: Per\n  [Ensure reservation availability](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Ftpus.md.txt)\n  and\n  [Multi-host TPU slice node pools](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fconcepts\u002Ftpus.md.txt),\n  if GKE can't deploy one node in a multi-host slice, no nodes in the slice are\n  deployed. If a stockout or lack-of-capacity message is present and the free\n  slots (`specificReservation.count - specificReservation.inUseCount`; see\n  [Consumable instances in a reservation](https:\u002F\u002Fdocs.cloud.google.com\u002Fcompute\u002Fdocs\u002Finstances\u002Freservations-view.md.txt))\n  are fewer than the number of nodes that `{failing_nodepool_name}` needs,\n  proceed to Step 2.\n\n---\n\n### Step 2: Find which VMs and node pools hold the reservation `[Low Risk]`\n\n1. **Check which VMs are consuming `{reservation_name}`**:\n   - Per\n     [How reservations work](https:\u002F\u002Fdocs.cloud.google.com\u002Fcompute\u002Fdocs\u002Finstances\u002Freservations-overview.md.txt),\n     a specifically targeted reservation can be used by VMs in the reservation's\n     project (`{reservation_project_id}`) or, for a shared reservation, in any\n     project that it's shared with.\n   - Follow\n     [View a list of instances that are consuming a reservation](https:\u002F\u002Fdocs.cloud.google.com\u002Fcompute\u002Fdocs\u002Finstances\u002Freservations-view.md.txt)\n     to list the VMs that use `{reservation_name}`.\n   - Follow\n     [View labels](https:\u002F\u002Fdocs.cloud.google.com\u002Fcompute\u002Fdocs\u002Flabeling-resources.md.txt)\n     to view each VM's labels, and check the GKE labels in\n     [Automatically applied labels](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Fcreating-managing-labels.md.txt)\n     (`goog-k8s-cluster-name`, `goog-k8s-cluster-location`, and\n     `goog-k8s-node-pool-name`) to find each VM's cluster and node pool.\n2. **Check node readiness in `{cluster_name}`**:\n   - Query the Cloud Monitoring metric `kubernetes_io:node_status_condition`\n     (`monitored_resource=\"k8s_node\"`, `cluster_name=\"{cluster_name}\"`,\n     `condition=\"Ready\"`) described in\n     [Monitor health metrics for TPU nodes and node pools](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Ftpus.md.txt).\n     The `status` label value is `True`, `False`, or `Unknown` (capitalized);\n     use `status!=\"True\"` to find nodes whose `Ready` condition is `False` or\n     `Unknown`.\n   - List TPU nodes and their node pool labels with `kubectl get nodes -l\n     cloud.google.com\u002Fgke-tpu-accelerator -L cloud.google.com\u002Fgke-nodepool`.\n3. **Exclude the failing node pool**: Leave `{failing_nodepool_name}` out of the\n   unhealthy list. It's the node pool that couldn't get capacity, not the one\n   holding it.\n\n#### Interpret the results\n- **VMs outside `{cluster_name}`**: If some of the VMs consuming\n  `{reservation_name}` aren't nodes in `{cluster_name}` (for example, their\n  labels show another GKE cluster or they are Compute Engine VMs without GKE\n  labels), tell the user which VMs or other clusters hold those reservation\n  slots.\n- **Fewer listed VMs than `specificReservation.inUseCount`**: Per\n  [View a list of instances that are consuming a reservation](https:\u002F\u002Fdocs.cloud.google.com\u002Fcompute\u002Fdocs\u002Finstances\u002Freservations-view.md.txt),\n  the list only includes VMs in one project. If the list has fewer VMs than\n  `specificReservation.inUseCount`, tell the user that VMs in other projects\n  that share `{reservation_name}` are consuming the remaining slots.\n- **Unhealthy node pool in `{cluster_name}` (`{leaking_nodepool_name}`)**: If\n  the VMs consuming `{reservation_name}` belong to an existing `NotReady` node\n  pool in `{cluster_name}` (`{leaking_nodepool_name}`), proceed to Step 3.\n- **Healthy reservation (rule out a leak)**: If the reserved slots are held by\n  healthy, in-use node pools, there is no leak. Explain that healthy node pools\n  hold the reserved slots, so too few slots are free for\n  `{failing_nodepool_name}`. Tell the user not to delete or restart those\n  healthy node pools, and point the user to the consumption options in\n  [Insufficient TPU resources to satisfy the TPU request](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Ftroubleshooting\u002Ftpus.md.txt).\n\n---\n\n### Step 3: Verify node auto-repair on the leaking node pool `[Low Risk]`\n\nFollow\n[Verify node auto-repair is enabled for a Standard node pool](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Fnode-auto-repair.md.txt)\nfor `{leaking_nodepool_name}`:\n- **Auto-repair is disabled (`management.autoRepair: false`)**: GKE doesn't\n  repair the `NotReady` nodes in `{leaking_nodepool_name}`. Their running VMs\n  keep counting toward `specificReservation.inUseCount` in `{reservation_name}`,\n  so `{failing_nodepool_name}` can't get reserved capacity. Proceed to Step 4.\n- **Auto-repair is enabled (`management.autoRepair: true`), but nodes are still\n  `NotReady`**:\n  - Check whether the nodes have been `NotReady` for less than the repair time\n    threshold (approximately 10 minutes), per\n    [Repair criteria](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Fnode-auto-repair.md.txt).\n  - Check the repair status and the failure reason in the operation history, per\n    [Configure auto repair for TPU slice nodes](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Ftpus.md.txt)\n    and\n    [Get information about recent automated repair events](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Fnode-auto-repair.md.txt).\n\n---\n\n### Step 4: Recover or release the reservation capacity `[High Risk]`\n\n> **Guardrail**: Don't modify GKE-managed instance groups or VMs directly\n> through Compute Engine. Manage node pools through GKE. Never delete healthy\n> node pools that run active jobs.\n\n1. **If the user wants to repair `{leaking_nodepool_name}` in place, enable node\n   auto-repair (doesn't free slots for `{failing_nodepool_name}`)**:\n   - Per\n     [Node repair process](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Fnode-auto-repair.md.txt),\n     GKE drains and re-creates an unhealthy node.\n   - Per\n     [Node auto repair in TPU slice nodes](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Fnode-auto-repair.md.txt)\n     and\n     [Configure auto repair for TPU slice nodes](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Ftpus.md.txt),\n     GKE re-creates the entire multi-host TPU slice node pool when a node in it\n     needs repair. The re-created VMs still consume `{reservation_name}`, so\n     `specificReservation.inUseCount` doesn't drop: enabling auto-repair makes\n     the nodes in `{leaking_nodepool_name}` healthy again, **but\n     `{failing_nodepool_name}` still can't get their slots**.\n   - Link the user to\n     [Enable auto-repair for an existing Standard node pool](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Fnode-auto-repair.md.txt)\n     to turn on auto-repair for `{leaking_nodepool_name}`.\n2. **If `{leaking_nodepool_name}` is stale or the user wants to free its slots\n   for `{failing_nodepool_name}`, delete it through GKE**: Link the user to\n   [Delete a node pool](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Fnode-pools.md.txt)\n   to delete `{leaking_nodepool_name}`, which frees the reserved slots its VMs\n   use.\n3. **After the user deletes `{leaking_nodepool_name}`, verify that enough\n   reservation slots are free**: Follow\n   [View reservations](https:\u002F\u002Fdocs.cloud.google.com\u002Fcompute\u002Fdocs\u002Finstances\u002Freservations-view.md.txt)\n   to run `gcloud compute reservations describe {reservation_name} --zone={zone}\n   --project={reservation_project_id}` and confirm that\n   `specificReservation.inUseCount` drops so the free slots\n   (`specificReservation.count - specificReservation.inUseCount`) are at least\n   the number of nodes that `{failing_nodepool_name}` needs before retrying\n   `{failing_nodepool_name}`.\n","# Troubleshoot GKE TPU reservation stockouts caused by leaked node pool capacity\n\nUse this skill to diagnose and resolve GKE TPU node pool creation or scale-up\nfailures that fail with `GCE_STOCKOUT`, `ZONE_RESOURCE_POOL_EXHAUSTED`, or\n`ZONE_RESOURCE_POOL_EXHAUSTED_WITH_DETAILS` (or queue due to lack of capacity)\neven though they target a specific Compute Engine TPU reservation.\n\nIf node auto-repair is disabled on an existing TPU node pool, GKE doesn't repair\nits nodes when they become `NotReady`. While their VMs are still running, they\nkeep consuming slots in the reservation (`inUseCount` is the number of running\ninstances that consume the reservation). Per\n[Ensure reservation availability](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Ftpus.md.txt),\nthe reservation must have sufficient available TPU chips at the time of node\npool creation, and per\n[Multi-host TPU slice node pools](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fconcepts\u002Ftpus.md.txt),\nif GKE is unable to deploy one node in a slice, no nodes in the TPU slice node\npool are deployed. When the free slots in the reservation\n(`specificReservation.count - specificReservation.inUseCount`; see\n[Consumable instances in a reservation](https:\u002F\u002Fdocs.cloud.google.com\u002Fcompute\u002Fdocs\u002Finstances\u002Freservations-view.md.txt))\nare fewer than the number of nodes that the new TPU node pool needs, creation\nfails with `GCE_STOCKOUT` or `ZONE_RESOURCE_POOL_EXHAUSTED` (or queues due to\nlack of capacity).\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-ai-troubleshooting-tpu-reservation-stockout)\"`\nand append `agent-skills\u002F1.0 (skill:gke-ai-troubleshooting-tpu-reservation-stockout)` to `User-Agent` headers.\n\n## Prerequisites\n\n- **Required IAM Roles**:\n  - Logs Viewer (`roles\u002Flogging.viewer`): Query Cloud Audit Logs in Cloud\n    Logging.\n  - Monitoring Viewer (`roles\u002Fmonitoring.viewer`): Query GKE node readiness\n    metrics in Cloud Monitoring.\n  - Kubernetes Engine Viewer (`roles\u002Fcontainer.viewer`): Inspect GKE node pools\n    (`management.autoRepair`), cluster operations, and node conditions.\n  - Compute Viewer (`roles\u002Fcompute.viewer`): Inspect Compute Engine reservation\n    utilization (`specificReservation.inUseCount` vs\n    `specificReservation.count`), consuming instances, and VM labels (including\n    in the reservation's owner project if using a shared reservation).\n  - For remediation (`[High Risk]` steps): Kubernetes Engine Cluster Admin\n    (`roles\u002Fcontainer.clusterAdmin`)\n- **API Enablement & Billing**:\n  - Ensure the target project has an active Google Cloud billing account\n    attached: `gcloud billing projects describe {project_id}`.\n  - Enable required APIs: `container.googleapis.com`, `compute.googleapis.com`,\n    `logging.googleapis.com`, and `monitoring.googleapis.com`.\n- **CLI & Authentication Setup**:\n  - Install Google Cloud SDK (`gcloud`) and `kubectl`:\n    https:\u002F\u002Fcloud.google.com\u002Fsdk\u002Fdocs\u002Finstall.\n- **Cluster mode**: This skill applies to Standard clusters. Autopilot clusters\n  always auto-repair nodes, and you can't turn this off (see\n  [Settings for Autopilot and Standard](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Fnode-auto-repair.md.txt)).\n- **Reference Documentation**:\n  - [Auto-repair nodes](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Fnode-auto-repair.md.txt)\n    (Sections: \"Settings for Autopilot and Standard\", \"Repair criteria\", \"Node\n    repair process\", \"Verify node auto-repair is enabled for a Standard node\n    pool\", \"Node auto repair in TPU slice nodes\", \"Enable auto-repair for an\n    existing Standard node pool\", \"Get information about recent automated repair\n    events\")\n  - [Troubleshoot GKE Standard node pools](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Ftroubleshooting\u002Fnode-pools.md.txt)\n    (Sections: \"Issue: Node pool creation fails due to insufficient resources\")\n  - [Troubleshoot TPUs in GKE](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Ftroubleshooting\u002Ftpus.md.txt)\n    (Sections: \"How GKE handles capacity issues\", \"Insufficient TPU resources to\n    satisfy the TPU request\")\n  - [About TPUs in GKE](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fconcepts\u002Ftpus.md.txt)\n    (Sections: \"Multi-host TPU slice node pools\")\n  - [Consuming reserved zonal resources](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Fconsuming-reservations.md.txt)\n    (Sections: \"Consuming a specific shared reservation\")\n  - [About reservations](https:\u002F\u002Fdocs.cloud.google.com\u002Fcompute\u002Fdocs\u002Finstances\u002Freservations-overview.md.txt)\n    (Sections: \"How reservations work\")\n  - [View reservations or future reservation requests](https:\u002F\u002Fdocs.cloud.google.com\u002Fcompute\u002Fdocs\u002Finstances\u002Freservations-view.md.txt)\n    (Sections: \"Limitations\", \"View reservations\", \"Consumable instances in a\n    reservation\", \"View a list of instances that are consuming a reservation\")\n  - [Organize resources using labels](https:\u002F\u002Fdocs.cloud.google.com\u002Fcompute\u002Fdocs\u002Flabeling-resources.md.txt)\n    (Sections: \"View labels\")\n  - [Create and manage cluster and node pool labels](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Fcreating-managing-labels.md.txt)\n    (Sections: \"Automatically applied labels\")\n  - [Deploy TPU workloads in GKE Standard](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Ftpus.md.txt)\n    (Sections: \"Ensure reservation availability\", \"Monitor health metrics for\n    TPU nodes and node pools\", \"Configure auto repair for TPU slice nodes\")\n  - [Add and manage node pools](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Fnode-pools.md.txt)\n    (Sections: \"Delete a node pool\")\n\n> **Read-only rule**: Run read-only diagnostic commands only. Never drain,\n> delete, or re-create nodes, or run any other command that changes the cluster.\n> Give the user any fix to apply themselves.\n\nWhen you recommend a fix, link the doc section that describes it.\n\n---\n\n## Diagnostic workflow\n\n### Step 0: Collect context and set the investigation window\n\nIdentify the following environment parameters from the user prompt or cluster\ncontext:\n- `{project_id}`, `{cluster_name}`, `{location}`, `{failing_nodepool_name}`,\n  `{reservation_name}`, `{reservation_project_id}` (the project that owns\n  `{reservation_name}`, which defaults to `{project_id}` for a single-project\n  reservation or is the owner project for a shared reservation; see\n  [Consuming a specific shared reservation](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Fconsuming-reservations.md.txt)),\n  `{zone}` (the zone of the reservation), and `{issue_time}`.\n- **Time window**: By default, query a 60-minute window `[{issue_time} - 30m,\n  {issue_time} + 30m]` (`{start_time}` to `{end_time}`).\n\n---\n\n### Step 1: Confirm the stockout error and reservation utilization `[Low Risk]`\n\n1. **Check Cloud Audit Logs and GKE operations for stockout or capacity\n   errors**:\n   - Run the query in\n     [Issue: Node pool creation fails due to insufficient resources](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Ftroubleshooting\u002Fnode-pools.md.txt)\n     across `[{start_time}, {end_time}]` and look for the documented error\n     messages, such as `ZONE_RESOURCE_POOL_EXHAUSTED` or\n     `ZONE_RESOURCE_POOL_EXHAUSTED_WITH_DETAILS`.\n   - Per\n     [Insufficient TPU resources to satisfy the TPU request](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Ftroubleshooting\u002Ftpus.md.txt),\n     TPU errors can also contain `GCE_STOCKOUT`.\n   - Per\n     [How GKE handles capacity issues](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Ftroubleshooting\u002Ftpus.md.txt),\n     GKE sometimes queues a TPU node pool creation request instead of failing it\n     immediately, surfacing a `... cannot be created ... due to lack of\n     capacity` message instead of `GCE_STOCKOUT`. List the node pool creation\n     operation with `gcloud container operations list`\n     (`--filter=\"operationType=CREATE_NODE_POOL\"`).\n2. **Check Compute Engine reservation utilization**:\n   - Per\n     [Limitations](https:\u002F\u002Fdocs.cloud.google.com\u002Fcompute\u002Fdocs\u002Finstances\u002Freservations-view.md.txt),\n     query shared reservations in the owner project where they were created\n     (`{reservation_project_id}`).\n   - Follow the\n     [View reservations](https:\u002F\u002Fdocs.cloud.google.com\u002Fcompute\u002Fdocs\u002Finstances\u002Freservations-view.md.txt)\n     section to run `gcloud compute reservations describe {reservation_name}\n     --zone={zone} --project={reservation_project_id}` or `gcloud compute\n     reservations list --project={reservation_project_id}`, and compare\n     `specificReservation.inUseCount` against `specificReservation.count`.\n\n#### Interpret the results\n- Don't suggest deleting any node pool until you have identified which existing\n  VMs and node pools hold the reserved capacity (Step 2).\n- **Stockout confirmed**: Per\n  [Ensure reservation availability](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Ftpus.md.txt)\n  and\n  [Multi-host TPU slice node pools](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fconcepts\u002Ftpus.md.txt),\n  if GKE can't deploy one node in a multi-host slice, no nodes in the slice are\n  deployed. If a stockout or lack-of-capacity message is present and the free\n  slots (`specificReservation.count - specificReservation.inUseCount`; see\n  [Consumable instances in a reservation](https:\u002F\u002Fdocs.cloud.google.com\u002Fcompute\u002Fdocs\u002Finstances\u002Freservations-view.md.txt))\n  are fewer than the number of nodes that `{failing_nodepool_name}` needs,\n  proceed to Step 2.\n\n---\n\n### Step 2: Find which VMs and node pools hold the reservation `[Low Risk]`\n\n1. **Check which VMs are consuming `{reservation_name}`**:\n   - Per\n     [How reservations work](https:\u002F\u002Fdocs.cloud.google.com\u002Fcompute\u002Fdocs\u002Finstances\u002Freservations-overview.md.txt),\n     a specifically targeted reservation can be used by VMs in the reservation's\n     project (`{reservation_project_id}`) or, for a shared reservation, in any\n     project that it's shared with.\n   - Follow\n     [View a list of instances that are consuming a reservation](https:\u002F\u002Fdocs.cloud.google.com\u002Fcompute\u002Fdocs\u002Finstances\u002Freservations-view.md.txt)\n     to list the VMs that use `{reservation_name}`.\n   - Follow\n     [View labels](https:\u002F\u002Fdocs.cloud.google.com\u002Fcompute\u002Fdocs\u002Flabeling-resources.md.txt)\n     to view each VM's labels, and check the GKE labels in\n     [Automatically applied labels](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Fcreating-managing-labels.md.txt)\n     (`goog-k8s-cluster-name`, `goog-k8s-cluster-location`, and\n     `goog-k8s-node-pool-name`) to find each VM's cluster and node pool.\n2. **Check node readiness in `{cluster_name}`**:\n   - Query the Cloud Monitoring metric `kubernetes_io:node_status_condition`\n     (`monitored_resource=\"k8s_node\"`, `cluster_name=\"{cluster_name}\"`,\n     `condition=\"Ready\"`) described in\n     [Monitor health metrics for TPU nodes and node pools](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Ftpus.md.txt).\n     The `status` label value is `True`, `False`, or `Unknown` (capitalized);\n     use `status!=\"True\"` to find nodes whose `Ready` condition is `False` or\n     `Unknown`.\n   - List TPU nodes and their node pool labels with `kubectl get nodes -l\n     cloud.google.com\u002Fgke-tpu-accelerator -L cloud.google.com\u002Fgke-nodepool`.\n3. **Exclude the failing node pool**: Leave `{failing_nodepool_name}` out of the\n   unhealthy list. It's the node pool that couldn't get capacity, not the one\n   holding it.\n\n#### Interpret the results\n- **VMs outside `{cluster_name}`**: If some of the VMs consuming\n  `{reservation_name}` aren't nodes in `{cluster_name}` (for example, their\n  labels show another GKE cluster or they are Compute Engine VMs without GKE\n  labels), tell the user which VMs or other clusters hold those reservation\n  slots.\n- **Fewer listed VMs than `specificReservation.inUseCount`**: Per\n  [View a list of instances that are consuming a reservation](https:\u002F\u002Fdocs.cloud.google.com\u002Fcompute\u002Fdocs\u002Finstances\u002Freservations-view.md.txt),\n  the list only includes VMs in one project. If the list has fewer VMs than\n  `specificReservation.inUseCount`, tell the user that VMs in other projects\n  that share `{reservation_name}` are consuming the remaining slots.\n- **Unhealthy node pool in `{cluster_name}` (`{leaking_nodepool_name}`)**: If\n  the VMs consuming `{reservation_name}` belong to an existing `NotReady` node\n  pool in `{cluster_name}` (`{leaking_nodepool_name}`), proceed to Step 3.\n- **Healthy reservation (rule out a leak)**: If the reserved slots are held by\n  healthy, in-use node pools, there is no leak. Explain that healthy node pools\n  hold the reserved slots, so too few slots are free for\n  `{failing_nodepool_name}`. Tell the user not to delete or restart those\n  healthy node pools, and point the user to the consumption options in\n  [Insufficient TPU resources to satisfy the TPU request](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Ftroubleshooting\u002Ftpus.md.txt).\n\n---\n\n### Step 3: Verify node auto-repair on the leaking node pool `[Low Risk]`\n\nFollow\n[Verify node auto-repair is enabled for a Standard node pool](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Fnode-auto-repair.md.txt)\nfor `{leaking_nodepool_name}`:\n- **Auto-repair is disabled (`management.autoRepair: false`)**: GKE doesn't\n  repair the `NotReady` nodes in `{leaking_nodepool_name}`. Their running VMs\n  keep counting toward `specificReservation.inUseCount` in `{reservation_name}`,\n  so `{failing_nodepool_name}` can't get reserved capacity. Proceed to Step 4.\n- **Auto-repair is enabled (`management.autoRepair: true`), but nodes are still\n  `NotReady`**:\n  - Check whether the nodes have been `NotReady` for less than the repair time\n    threshold (approximately 10 minutes), per\n    [Repair criteria](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Fnode-auto-repair.md.txt).\n  - Check the repair status and the failure reason in the operation history, per\n    [Configure auto repair for TPU slice nodes](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Ftpus.md.txt)\n    and\n    [Get information about recent automated repair events](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Fnode-auto-repair.md.txt).\n\n---\n\n### Step 4: Recover or release the reservation capacity `[High Risk]`\n\n> **Guardrail**: Don't modify GKE-managed instance groups or VMs directly\n> through Compute Engine. Manage node pools through GKE. Never delete healthy\n> node pools that run active jobs.\n\n1. **If the user wants to repair `{leaking_nodepool_name}` in place, enable node\n   auto-repair (doesn't free slots for `{failing_nodepool_name}`)**:\n   - Per\n     [Node repair process](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Fnode-auto-repair.md.txt),\n     GKE drains and re-creates an unhealthy node.\n   - Per\n     [Node auto repair in TPU slice nodes](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Fnode-auto-repair.md.txt)\n     and\n     [Configure auto repair for TPU slice nodes](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Ftpus.md.txt),\n     GKE re-creates the entire multi-host TPU slice node pool when a node in it\n     needs repair. The re-created VMs still consume `{reservation_name}`, so\n     `specificReservation.inUseCount` doesn't drop: enabling auto-repair makes\n     the nodes in `{leaking_nodepool_name}` healthy again, **but\n     `{failing_nodepool_name}` still can't get their slots**.\n   - Link the user to\n     [Enable auto-repair for an existing Standard node pool](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Fnode-auto-repair.md.txt)\n     to turn on auto-repair for `{leaking_nodepool_name}`.\n2. **If `{leaking_nodepool_name}` is stale or the user wants to free its slots\n   for `{failing_nodepool_name}`, delete it through GKE**: Link the user to\n   [Delete a node pool](https:\u002F\u002Fdocs.cloud.google.com\u002Fkubernetes-engine\u002Fdocs\u002Fhow-to\u002Fnode-pools.md.txt)\n   to delete `{leaking_nodepool_name}`, which frees the reserved slots its VMs\n   use.\n3. **After the user deletes `{leaking_nodepool_name}`, verify that enough\n   reservation slots are free**: Follow\n   [View reservations](https:\u002F\u002Fdocs.cloud.google.com\u002Fcompute\u002Fdocs\u002Finstances\u002Freservations-view.md.txt)\n   to run `gcloud compute reservations describe {reservation_name} --zone={zone}\n   --project={reservation_project_id}` and confirm that\n   `specificReservation.inUseCount` drops so the free slots\n   (`specificReservation.count - specificReservation.inUseCount`) are at least\n   the number of nodes that `{failing_nodepool_name}` needs before retrying\n   `{failing_nodepool_name}`.\n",{"name":5,"metadata":44,"description":7},{"version":45,"category":46},"1.0.1","Containers","main","bb9b3f464aae37af360d079c1d863524955b0363","skills\u002Fcloud\u002Fgke-ai-troubleshooting-tpu-reservation-stockout",2002,"https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fskills","https:\u002F\u002Fgithub.com\u002Fgoogle","https:\u002F\u002Fopensource.google\u002F","Google ❤️ Open Source","2026-11-13 02:42:47",{"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-ai-troubleshooting-tpu-reservation-stockout",{"tool":62,"command":63},"bunx","bunx skills add google\u002Fskills --skill gke-ai-troubleshooting-tpu-reservation-stockout",{"tool":65,"command":66},"pnpm","pnpm dlx skills add google\u002Fskills --skill gke-ai-troubleshooting-tpu-reservation-stockout","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fcloud\u002Fgke-ai-troubleshooting-tpu-reservation-stockout\u002FSKILL.md",true,[70],{"path":71,"resourceType":72,"resourceTypeDesc":73,"sizeBytes":74,"sourceHtmlUrl":75},"references\u002Fattribution.md","REFERENCE","参考文档",1989,"https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fcloud\u002Fgke-ai-troubleshooting-tpu-reservation-stockout\u002Freferences\u002Fattribution.md",[77,115,145,174,201,224],{"skillNo":78,"name":79,"nameZh":6,"description":80,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":81,"categories":82,"keywords":91,"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",[83,88],{"categoryNo":84,"categoryName":85,"taxonomyType":86,"taxonomyTypeDesc":87},"01JBSEEDCAT000000000000009","前端开发","SCENARIO","使用场景",{"categoryNo":89,"categoryName":90,"taxonomyType":86,"taxonomyTypeDesc":87},"01JBSEEDCAT000000000000010","后端与接口",[9,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114],"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":116,"name":117,"nameZh":6,"description":118,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":119,"categories":120,"keywords":130,"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",[121,122,125],{"categoryNo":89,"categoryName":90,"taxonomyType":86,"taxonomyTypeDesc":87},{"categoryNo":123,"categoryName":124,"taxonomyType":86,"taxonomyTypeDesc":87},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":126,"categoryName":127,"taxonomyType":128,"taxonomyTypeDesc":129},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[131,132,9,100,133,134,135,136,137,138,106,139,140,141,36,142,143,111,114,144,23],"dpop adoption","adoption","es6","retry","authentication","flows","challenge","code","browser","loops","at","token","pair","platform",{"skillNo":146,"name":147,"nameZh":6,"description":148,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":149,"categories":150,"keywords":157,"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",[151,152,155,156],{"categoryNo":89,"categoryName":90,"taxonomyType":86,"taxonomyTypeDesc":87},{"categoryNo":153,"categoryName":154,"taxonomyType":86,"taxonomyTypeDesc":87},"01JBSEEDCAT000000000000021","资料检索与研究",{"categoryNo":123,"categoryName":124,"taxonomyType":86,"taxonomyTypeDesc":87},{"categoryNo":126,"categoryName":127,"taxonomyType":128,"taxonomyTypeDesc":129},[158,159,160,161,100,162,163,164,165,166,167,168,169,23,170,171,172,106,173,107],"retrieving developer knowledge","knowledge","developer","MCP","mcp server","official","developer documentation","get","search","local","choice","documents","query","api","across","documentation",{"skillNo":175,"name":176,"nameZh":6,"description":177,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":178,"categories":179,"keywords":180,"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",[],[181,182,183,184,185,186,187,188,103,189,190,191,192,193,194,167,195,196,197,23,198,199,172,200],"migrate to rust","rust","migrate","github","memory","performance","directory","safe","ports","llvm","soa","cycle","porting","fix","arrays","infographic","high-performance","URL","architecture","unrelated",{"skillNo":202,"name":203,"nameZh":6,"description":204,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":205,"categories":206,"keywords":210,"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",[207,208,209],{"categoryNo":89,"categoryName":90,"taxonomyType":86,"taxonomyTypeDesc":87},{"categoryNo":123,"categoryName":124,"taxonomyType":86,"taxonomyTypeDesc":87},{"categoryNo":126,"categoryName":127,"taxonomyType":128,"taxonomyTypeDesc":129},[9,211,212,213,214,144,215,216,217,218,219,135,220,32,221,168,35,222,23,223,171],"finding google skills","storage","as","messaging","model","trade-offs","provider","answer","fit","catalog","decision","database","candidate",{"skillNo":225,"name":226,"nameZh":6,"description":227,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":228,"categories":229,"keywords":232,"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",[230,231],{"categoryNo":89,"categoryName":90,"taxonomyType":86,"taxonomyTypeDesc":87},{"categoryNo":123,"categoryName":124,"taxonomyType":86,"taxonomyTypeDesc":87},[233,38,110,234,9,161,235,100,162,236,237,238,239,23,240,171,106,241,242,243,244],"workload manager basics","basics","cli","review","vpc","resources","inspect","you","create","libraries","server","run"]