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Codifies Step 0 context rules, zero-hallucination signatures, and explicit LQL\u002FPromQL query requirements.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},"google-cloud","Google Cloud","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fgoogle-cloud.png","GoogleCloudPlatform",[13,17,20,23],{"name":14,"slug":15,"type":16},"Documentation","documentation","tag",{"name":18,"slug":19,"type":16},"Engineering","engineering",{"name":21,"slug":22,"type":16},"Technical Writing","technical-writing",{"name":9,"slug":8,"type":16},161,"https:\u002F\u002Fgithub.com\u002FGoogleCloudPlatform\u002Fgke-mcp","2026-07-12T07:39:50.73484",null,78,[],{"repoUrl":25,"stars":24,"forks":28,"topics":31,"description":27},[],"https:\u002F\u002Fgithub.com\u002FGoogleCloudPlatform\u002Fgke-mcp\u002Ftree\u002FHEAD\u002Fskills\u002Fgke-ai-troubleshooting-skill-creation-guide","---\nname: gke-ai-troubleshooting-skill-creation-guide\ndescription: >\n  Expert instructions for building high-quality GKE troubleshooting skills.\n  Codifies Step 0 context rules, zero-hallucination signatures, and explicit\n  LQL\u002FPromQL query requirements.\n---\n\n# Troubleshooting Skill Creation Guide\n\nUse this guide to build high-quality troubleshooting skills that enable AI\nagents to diagnose complex failures in GKE workloads.\n\n## 🏗️ Skill Structure Standard\n\n### Mandatory Components\n\n1. **`SKILL.md`**: The core diagnostic and resolution workflow.\n2. **`README.md`**: Public-facing overview and \"When to use\" guide.\n3. **`references\u002Ffailure_signatures.md`**: Authentic log\u002Fmetric signatures.\n4. **`scripts\u002Fvalidate_queries.sh`**: Automatic syntax validator for all\n   queries.\n5. **`TEST.md`**: Manual verification plan for humans.\n6. **`EVAL.yaml`**: Evaluation suite for performance tracking.\n\n### Optional Components\n\n1. **`BUILD`**: Build definition.\n\n## 🏷️ Naming Conventions\n\n- **Directory Name**: MUST be `kebab-case` (e.g.,\n  `gke-ai-troubleshooting-tpu-vbar-oom`).\n- **Skill Name**: MUST match the directory name.\n\n## 🔍 Diagnostic Workflow Standards\n\n### Step 0: Mandatory Context\n\nEvery skill MUST begin with a \"Step 0\" to acquire necessary context.\n\n- **Mandatory Fields**: `\u003Cproject_id>`, `\u003Clocation>`, `\u003Ccluster_name>`,\n  `\u003Ctimestamp>`.\n- **Optional\u002FCase-by-Case Fields**: `\u003Cnode_name>`, `\u003Cworkload_name>`,\n  `\u003Cworkload_namespace>`, `\u003Cnodepool_name>`.\n- **Time Rule**: Reject relative time (e.g., \"5 minutes ago\"). Calculate a\n  window of `[T - 30m]` to `[T + 30m]`.\n\n### Diagnostic Steps\n\n- **Explicit Queries**: Every step MUST provide a ready-to-use **Cloud Logging\n  (LQL)** or **Cloud Monitoring (PromQL)** query.\n- **Placeholder Syntax**: Use **angle brackets** like `\u003Cproject_id>` instead\n  of curly braces for placeholders to avoid template resolution errors.\n- **Risk Categorization**: Label every step as **[Low Risk]** (Read-only) or\n  **[High Risk]** (Mutative\u002FDestructive).\n- **Automation**: Specify if the agent should proceed automatically or wait\n  for user confirmation.\n\n## 🛠️ Accuracy & Validation\n\n### Zero Hallucination\n\n- Never synthesize example logs or metrics.\n- Source signatures from real incidents and anonymize where necessary.\n- **DO NOT EXTRAPOLATE**: Only include steps and queries that were verified\n  in the source conversation.\n\n### Security & Privacy\n\n- **No Raw Dumps**: Do not instruct the agent to dump raw logs into shared\n  spaces (bugs, chat).\n- **Signal Only**: Instruct the agent to summarize findings and report only\n  high-signal information (e.g., \"Found specific error pattern X on node Y\").\n\n### Automated Validation\n\n- Every skill MUST include a script (at `scripts\u002Fvalidate_queries.sh`) that\n  uses `query_logs` or `gcloud logging read ... --limit=1` to verify its LQL\n  queries.\n\n## 📋 Best Practices\n\n- **Conciseness**: Keep instructions lean. Focus on \"what to do\" and \"how to\n  verify\".\n- **Public Ready**: Remove all internal notes, personal bookmarks, or\n  project-specific jargon.\n- **Error Signatures**: Explicitly link to `references\u002Ffailure_signatures.md`\n  in relevant diagnostic steps.\n",{"data":35,"body":36},{"name":4,"description":6},{"type":37,"children":38},"root",[39,48,54,61,68,159,165,182,188,228,234,240,245,351,357,449,455,461,484,490,513,519,549,555],{"type":40,"tag":41,"props":42,"children":44},"element","h1",{"id":43},"troubleshooting-skill-creation-guide",[45],{"type":46,"value":47},"text","Troubleshooting Skill Creation Guide",{"type":40,"tag":49,"props":50,"children":51},"p",{},[52],{"type":46,"value":53},"Use this guide to build high-quality troubleshooting skills that enable AI\nagents to diagnose complex failures in GKE workloads.",{"type":40,"tag":55,"props":56,"children":58},"h2",{"id":57},"️-skill-structure-standard",[59],{"type":46,"value":60},"🏗️ Skill Structure 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Use when users ask to create GCP resources, use Fabric modules, or generate Terraform code for Google Cloud.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[654,655,658],{"name":9,"slug":8,"type":16},{"name":656,"slug":657,"type":16},"Infrastructure as Code","infrastructure-as-code",{"name":659,"slug":660,"type":16},"Terraform","terraform","2026-07-12T07:38:23.514555",{"slug":663,"name":663,"fn":664,"description":665,"org":666,"tags":667,"stars":645,"repoUrl":646,"updatedAt":672},"fast-0-org-setup-prereqs","prepare prerequisites for FAST 0-org-setup","Guides the user step-by-step through the prerequisites for the FAST 0-org-setup stage, supporting both Standard GCP and Google Cloud Dedicated (GCD) environments. 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Use when the user wants to build a CLI, apply CLI best practices, or use Go with Cobra and Viper.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[679,682,683],{"name":680,"slug":681,"type":16},"CLI","cli",{"name":18,"slug":19,"type":16},{"name":9,"slug":8,"type":16},1150,"https:\u002F\u002Fgithub.com\u002FGoogleCloudPlatform\u002Fvertex-ai-creative-studio","2026-07-12T07:39:08.41406",{"slug":688,"name":688,"fn":689,"description":690,"org":691,"tags":692,"stars":684,"repoUrl":685,"updatedAt":703},"build-mcp-genmedia","build and configure GenAI MCP servers","Builds the mcp-genmedia Go MCP servers (nanobanana, veo, lyria, gemini-multimodal, chirp3-hd, avtool) from source and wires them into settings.json. Use this skill whenever the MCP tools are missing or broken — typically at the start of a new session, after a container restart, or when \u002Ftmp has been wiped. The prebuilt binaries in \u002Fworkspace\u002F.local\u002Fbin\u002F have no exec bit and live on a noexec mount; this skill compiles fresh executables into \u002Ftmp\u002Fbin\u002F where execution is allowed.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[693,696,697,700],{"name":694,"slug":695,"type":16},"API Development","api-development",{"name":9,"slug":8,"type":16},{"name":698,"slug":699,"type":16},"LLM","llm",{"name":701,"slug":702,"type":16},"MCP","mcp","2026-07-12T07:39:10.911302",{"slug":705,"name":705,"fn":706,"description":707,"org":708,"tags":709,"stars":684,"repoUrl":685,"updatedAt":720},"genmedia-audio-engineer","synthesize and mix audio content","Expert in audio synthesis, music generation, and mixing. Use when creating podcasts, background scores, or multi-track audio layering using mcp-chirp3-go, mcp-lyria-go, mcp-gemini-go, mcp-nanobanana-go, and mcp-avtool-go.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[710,713,716,717],{"name":711,"slug":712,"type":16},"Audio","audio",{"name":714,"slug":715,"type":16},"Creative","creative",{"name":9,"slug":8,"type":16},{"name":718,"slug":719,"type":16},"Vertex AI","vertex-ai","2026-07-12T07:39:16.623879",{"slug":722,"name":722,"fn":723,"description":724,"org":725,"tags":726,"stars":684,"repoUrl":685,"updatedAt":733},"genmedia-image-artist","generate and edit AI images","Expert in AI image generation and editing. Use when the user needs high-quality textures, character-consistent visuals, or image-to-image editing using mcp-nanobanana-go.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[727,728,729,732],{"name":714,"slug":715,"type":16},{"name":9,"slug":8,"type":16},{"name":730,"slug":731,"type":16},"Image Generation","image-generation",{"name":718,"slug":719,"type":16},"2026-07-12T07:39:15.372822",{"slug":735,"name":735,"fn":736,"description":737,"org":738,"tags":739,"stars":684,"repoUrl":685,"updatedAt":749},"genmedia-producer","produce multi-step media content","Expert media production assistant. Use when requested to help with storyboarding, podcast creation, audio assembly, or complex multi-step media workflows using the GenMedia MCP servers (Veo, Lyria, Gemini TTS, NanoBanana).",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[740,741,742,743,746],{"name":711,"slug":712,"type":16},{"name":714,"slug":715,"type":16},{"name":9,"slug":8,"type":16},{"name":744,"slug":745,"type":16},"Media","media",{"name":747,"slug":748,"type":16},"Video","video","2026-07-12T07:39:09.672849",{"slug":751,"name":751,"fn":752,"description":753,"org":754,"tags":755,"stars":684,"repoUrl":685,"updatedAt":759},"genmedia-video-editor","edit and compose video content","Expert in video composition, editing, and format conversion. Use when the user wants to generate high-quality video, overlay images on video, concatenate clips, create GIFs, or sync audio to video using mcp-avtool-go and mcp-veo-go.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[756,757,758],{"name":714,"slug":715,"type":16},{"name":9,"slug":8,"type":16},{"name":747,"slug":748,"type":16},"2026-07-12T07:39:13.749081",{"slug":761,"name":761,"fn":762,"description":763,"org":764,"tags":765,"stars":684,"repoUrl":685,"updatedAt":777},"genmedia-voice-director","generate expressive text-to-speech with Gemini","Expert in casting, directing, and generating expressive text-to-speech using Gemini TTS. Use this when the user needs virtual voice actor personas, expressive speech generation, or multiple variations of a voiceover (like \"take 3 on the bounce\").",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[766,767,768,771,774],{"name":711,"slug":712,"type":16},{"name":714,"slug":715,"type":16},{"name":769,"slug":770,"type":16},"Gemini","gemini",{"name":772,"slug":773,"type":16},"Speech","speech",{"name":775,"slug":776,"type":16},"Text-to-Speech","text-to-speech","2026-07-12T07:39:17.86673",80,{"items":780,"total":868},[781,795,810,823,830,841,857],{"slug":782,"name":782,"fn":783,"description":784,"org":785,"tags":786,"stars":24,"repoUrl":25,"updatedAt":794},"custom-golden-image-discovery","discover golden base images for GKE nodes","Expert at discovering golden base images for GKE custom nodes using technical specs or context clues.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[787,790,791],{"name":788,"slug":789,"type":16},"Deployment","deployment",{"name":9,"slug":8,"type":16},{"name":792,"slug":793,"type":16},"Kubernetes","kubernetes","2026-07-12T07:39:30.888879",{"slug":796,"name":796,"fn":797,"description":798,"org":799,"tags":800,"stars":24,"repoUrl":25,"updatedAt":809},"gke-ai-troubleshooting-handle-disruption-gpu-tpu","diagnose GPU and TPU workload disruptions","Diagnose and predict node disruption during Compute Engine host maintenance for GPU and TPU workloads.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[801,804,805,806],{"name":802,"slug":803,"type":16},"Debugging","debugging",{"name":9,"slug":8,"type":16},{"name":792,"slug":793,"type":16},{"name":807,"slug":808,"type":16},"Performance","performance","2026-07-28T05:34:18.149515",{"slug":811,"name":811,"fn":812,"description":813,"org":814,"tags":815,"stars":24,"repoUrl":25,"updatedAt":822},"gke-ai-troubleshooting-jobset-interruption","diagnose GKE JobSet interruptions","Systematically diagnose GKE JobSet interruptions, restarts, and preemptions for AI\u002FML training workloads. Identifies preemption events, maintenance interruptions, bad host VMs, unhealthy pods, and coordinator worker failures.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[816,817,818,819],{"name":802,"slug":803,"type":16},{"name":9,"slug":8,"type":16},{"name":792,"slug":793,"type":16},{"name":820,"slug":821,"type":16},"Observability","observability","2026-07-12T07:40:04.511878",{"slug":4,"name":4,"fn":5,"description":6,"org":824,"tags":825,"stars":24,"repoUrl":25,"updatedAt":26},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[826,827,828,829],{"name":14,"slug":15,"type":16},{"name":18,"slug":19,"type":16},{"name":9,"slug":8,"type":16},{"name":21,"slug":22,"type":16},{"slug":831,"name":831,"fn":832,"description":833,"org":834,"tags":835,"stars":24,"repoUrl":25,"updatedAt":840},"gke-ai-troubleshooting-tpu-connection-failure-vbar-oom","diagnose GKE TPU connection failures","Diagnose and prevent `vbar_control_agent` segfaults and OOMs caused by race conditions during TPU device resets and frequent metrics collection (e.g. every 3s). Use when TPU slice initialization fails or `vbar_control_agent` crashes on TPU v6e nodes.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[836,837,838,839],{"name":802,"slug":803,"type":16},{"name":9,"slug":8,"type":16},{"name":792,"slug":793,"type":16},{"name":807,"slug":808,"type":16},"2026-07-12T07:39:49.482979",{"slug":842,"name":842,"fn":843,"description":844,"org":845,"tags":846,"stars":24,"repoUrl":25,"updatedAt":856},"gke-app-onboarding","containerize and deploy apps to GKE","Workflows for containerizing and deploying applications to GKE for the first time.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[847,850,851,852,853],{"name":848,"slug":849,"type":16},"Containers","containers",{"name":788,"slug":789,"type":16},{"name":9,"slug":8,"type":16},{"name":792,"slug":793,"type":16},{"name":854,"slug":855,"type":16},"Onboarding","onboarding","2026-07-12T07:39:41.935837",{"slug":858,"name":858,"fn":859,"description":860,"org":861,"tags":862,"stars":24,"repoUrl":25,"updatedAt":867},"gke-backup-dr","configure GKE backup and disaster recovery","Workflows for configuring Backup for GKE and disaster recovery.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[863,864,865,866],{"name":788,"slug":789,"type":16},{"name":9,"slug":8,"type":16},{"name":792,"slug":793,"type":16},{"name":670,"slug":671,"type":16},"2026-07-12T07:39:34.806995",25]